Price manipulation in the Bitcoin ecosystem, VOX, CEPR’s Policy Portal

VOX CEPR’s Policy Portal

Research-based policy analysis and commentary from leading economists

Price manipulation in the Bitcoin ecosystem

Neil Gandal, JT Hamrick, Tyler Moore, Tali Oberman twenty two June two thousand seventeen

The cryptocurrency Bitcoin has attracted widespread interest, in large part due to wild swings in its valuation. This column considers an earlier rise in the Bitcoin price to investigate what is driving the currency’s price spikes. The two thousand thirteen rise was caused by fraudulent trades taking place at the largest Bitcoin currency exchange at the time. This finding has implications for policymakers as they weigh what, if anything, to do about regulating cryptocurrencies in light of the record high Bitcoin valuation that many fear is a bubble.

Related

The digital currency Bitcoin was introduced in 2009. Bitcoin and the many other digital currencies are primarily online currencies. The key currencies are those based primarily on cryptography, and Bitcoin is the leading ‘cryptocurrency’.

Bitcoin has experienced a meteoric rise in popularity since its introduction. While digital currencies were proposed as early as the 1980s, Bitcoin was the very first to catch on. The total value of all Bitcoins in circulation reached $45 billion in June 2017. Its success has inspired scores of contesting cryptocurrencies that go after a similar design. Bitcoin and most other cryptocurrencies do not require a central authority to validate and lodge transactions. Instead, these currencies use cryptography (and an internal incentive system) to control transactions, manage the supply, and prevent fraud. Payments are validated by a decentralised network. Once confirmed, all transactions are stored digitally and recorded in a public ‘blockchain’,’ which can be thought of as a distributed accounting system.

While Bitcoin’s algorithm provides safeguards against ‘counterfeiting’ of the currency, the eco-system is still vulnerable to theft. Users keep keys to their Bitcoins and make transactions with the help of wallets. Exchanges facilitate trade inbetween Bitcoins and fiat currencies, and also permit for storing Bitcoins. Bitcoins can be stolen through wallets or exchanges. Exchanges have been targeted more frequently than wallets because many wallets are located on users’ (local) computers, while exchanges frequently store customer deposits in their own (much larger) wallets.

The supply of most cryptocurrencies increases at a predetermined rate, and cannot be switched by any central authority. There are about fifteen million Bitcoins presently in circulation, with the ultimate number eventually reaching twenty one million. The motionless supply in the long run creates concerns about the deflationary aspect of the currency.

While Bitcoin shows superb promise to disrupt existing payment systems through innovations in its technical design, the Bitcoin ecosystem one has been the frequent target of attacks by financially motivated criminals. Due to the unregulated, decentralised environment in which they operate, cryptocurrencies are under constant threat of attack.

Bitcoin only recently became a subject of research in economics. However, the topic has been of interest for longer in computer science (for early work by computer scientists on incentives, see Babaioff et al. 2012, and Eyal and Sirer 2014.) Numerous researchers have conducted studies in order to document and combat threats such as Ponzi schemes, money laundering, mining botnets, and the theft of cryptocurrency wallets (Moeser et al. 2013, Vasek and Moore 2015, Vasek et al. 2016, Yuxing et al. 2014). Ron and Shamir (2013) attempt to identify suspicious trading activity by building a graph of Bitcoin transactions found in the public ledger. None of these papers can associate individual transactions with specific users of the currency exchanges.

In latest work, we display that the very first time Bitcoin reached an exchange rate of more than $1,000, the meteoric rise was driven by fraud (Gandal et al. 2017). We leverage a unique and very detailed dataset to examine suspicious trading activity that occurred over a ten-month period in two thousand thirteen on Mt. Gox, the leading Bitcoin currency exchange at the time. We very first quantify the extent of the suspicious/fraudulent trading activity and showcase that it constitutes a large fraction of trading on the days the activity occurred. We then showcase how this trading activity affected the exchange rates at Mt. Gox and other leading currency exchanges.

Figure 1 Bitcoin–US dollar exchange rate, with periods of suspicious activity shaded

While it was the superior currency exchange when Bitcoin very first shot to prominence in early 2013, behind the scenes, Tokyo-based Mt. Gox was in trouble. In addition to suffering from repeated denial-of-service attacks and Bitcoin thefts, two unauthorised traders were able to transact on the exchange without spending real money. In the very first case, a trader dubbed ‘Markus’ was credited with Bitcoins by duplicating previously finished transactions. In the 2nd case, a trader dubbed ‘Willy’ bought Bitcoins from traders by ‘crediting’ the sellers’ accounts with fiat currencies that, in many cases, could not be withdrawn. Figure one shows when these fraudulent traders were active, along with the Bitcoin–US dollar exchange rate. Most noteworthy is that Willy’s operation coincided with an unprecedented leap in the price of Bitcoin: from around $150 to over $1000. In early 2014, Mt. Gox collapsed, and the Bitcoin price fell with it. Only recently, in early 2017, has Bitcoin surpassed the levels of the earlier rise.

However, how do we know that the rise was caused by the fraudulent trades? Fortunately for us as researchers, the unauthorised trades did not take place every day. Table one shows the daily switch in the Bitcoin–US dollar exchange rate for various time periods on Mt. Gox. In the two quarters before unauthorised trading commenced, the daily price increase was, on average, positive but relatively puny: a $0.21 increase in the very first period and a $1 increase in the 2nd period. During the third quarter, when unauthorised trading began, the price rose by an average of $Three.15 on the seventeen days in which Markus traded, but fell on average by $0.51 on the seventy five days he did not trade. However, it is during the final quarter, when Willy began trading, that the difference became stark. On the fifty days in which Willy traded, the Bitcoin price rose by an average of $21.85. On the forty one days in which Willy did not make unauthorizsed purchases, the price fell by $0.88 on average. (Table one is very similar for the other leading exchanges as well.)

Table 1 Average daily switch in BTC/USD exchange rate as a function of fraudulent activity Two

In our total paper, we conduct a regression analysis to examine whether other factors such as the relatively numerous and varied attacks on the Mt. Gox exchange could explain the switch in the daily Bitcoin price, both at Mt. Gox and other leading exchanges (Gandal et al. 2017).

The analysis confirms that only Willy’s trading presence affected the price. The estimated coefficient (on the dummy variable for whether Willy was active) is virtually the same ($21.65) as in Table 1. We conclude that the suspicious trading activity of a single actor was the primary cause of the massive spike in the Bitcoin–US dollar exchange rate, in which the rate rose from around $150 to over $1,000 in just two months in late 2013. The fall was almost as precipitous: the Mt. Gox exchange folded due to insolvency in early 2014, and it has taken more than three years for Bitcoin to match the rise triggered by fraudulent transactions.

Why should we care about the Bitcoin manipulation that took place in 2013? After all, the Bitcoin ecosystem is not almost as significant as the Fresh York Stock Exchange. Nonetheless, latest trends indicate that Bitcoin is becoming an significant asset in the financial system.

Trading in cryptocurrency assets has exploded recently. In the case of Bitcoin, during the one year period ending in mid-June 2017, the market capitalisation enlargened massively from around $7 billion to $45 billion; that is an increase of over 500% in one year. The market cap of other cryptocurrencies surged by even more. In the one-year period ending in mid-May 2017, the market value of cryptocurrencies excluding Bitcoin surged from $1.7 billion to more than $29 billion; that is an increase of more than 1,900%. The markets for these other cryptocurrencies are very skinny and subject to manipulation. Given that we now know the Bitcoin price has been artificially inflated by unauthorised trades in the past, we must view the present rise with excellent caution, and not necessarily consider it a ‘healthy bubble’, as recently claimed in The Economist (2017).

As mainstream finance invests in cryptocurrency assets and as countries take steps toward legalising Bitcoin as a payment system (as Japan did in April 2017), it is significant to understand how susceptible cryptocurrency markets are to manipulation. We encourage the nascent cryptocurrency industry to work with regulators and researchers to share anonymised transaction data so that more confidence can be placed in the veracity of exchange rates.

References

Babaioff, M, S Dobzinski, S Oren and A Zohar (2012), “On bitcoin and crimson balloons” in Proceedings of the 13th ACM Conference on Electronic Commerce, pp. 56-73.

Eyal, I and E Sirer (2014), “Majority is not Enough: Bitcoin Mining is Vulnerable”, paper introduced at the Eighteenth International Conference on Financial Cryptography and Data Security, Barbados, 3-7 March.

Gandal, N, J Hamrick, T Moore and T Oberman (2017), “Price Manipulation in the Bitcoin Ecosystem,” CEPR Discussion Paper No. 12061.

Mooser, M, R Bohme and D Breuker (2013), “An inquiry into money laundering devices in the Bitcoin ecosystem”, in Proceedings of the Seventh APWG eCrime Re-searcher’s Summit, pp. 1-14.

Ron, D and A Shamir (2013), “Quantitative analysis of the total Bitcoin transaction graph”, in Financial Cryptography and Data Security, Vol. Seven thousand eight hundred fifty nine of Lecture Notes in Computer Science, pp. 6-24.

Vasek, M and T Moore (2015), “There’s no free lunch, even using Bitcoin: Tracking the popularity and profits of virtual currency scams”, in R Bohme and T Okamoto (eds), Financial Cryptography and Data Security, volume eight thousand nine hundred seventy five of Lecture Notes in Computer Science, pp. 44-61.

Vasek, M, J Bonneau, R Castellucci, C Keith and T Moore (2016), “The Bitcoin brain drain: a brief paper on the use and manhandle of bitcoin brain wallets”, in Financial Cryptography and Data Security, Lecture Notes in Computer Science.

Yuxing Huang, D, H Dharmdasani, S Meiklejohn, V Dave, C Grier, D McCoy, S Savage, N Weaver, A Snoeren and K Levchenko (2014), “Botcoin: Monetizing stolen cycles”, in Proceedings of the Network and Distributed System Security Symposium.

Endnotes

[1] The Bitcoin ecosystem includes the core network for propagating transactions, the blockchain, and many intermediaries such as currency exchanges, mining pools, and payment processors that facilitate trade.

[Two] Markus was primarily active in period Trio, but he was also active a few days during periods 1,Two, and Four. He was not active on the same days as Willy, who was only active in period Four.

Price manipulation in the Bitcoin ecosystem, VOX, CEPR’s Policy Portal

VOX CEPR’s Policy Portal

Research-based policy analysis and commentary from leading economists

Price manipulation in the Bitcoin ecosystem

Neil Gandal, JT Hamrick, Tyler Moore, Tali Oberman twenty two June two thousand seventeen

The cryptocurrency Bitcoin has attracted widespread interest, in large part due to wild swings in its valuation. This column considers an earlier rise in the Bitcoin price to investigate what is driving the currency’s price spikes. The two thousand thirteen rise was caused by fraudulent trades taking place at the largest Bitcoin currency exchange at the time. This finding has implications for policymakers as they weigh what, if anything, to do about regulating cryptocurrencies in light of the record high Bitcoin valuation that many fear is a bubble.

Related

The digital currency Bitcoin was introduced in 2009. Bitcoin and the many other digital currencies are primarily online currencies. The key currencies are those based primarily on cryptography, and Bitcoin is the leading ‘cryptocurrency’.

Bitcoin has experienced a meteoric rise in popularity since its introduction. While digital currencies were proposed as early as the 1980s, Bitcoin was the very first to catch on. The total value of all Bitcoins in circulation reached $45 billion in June 2017. Its success has inspired scores of rivaling cryptocurrencies that go after a similar design. Bitcoin and most other cryptocurrencies do not require a central authority to validate and lodge transactions. Instead, these currencies use cryptography (and an internal incentive system) to control transactions, manage the supply, and prevent fraud. Payments are validated by a decentralised network. Once confirmed, all transactions are stored digitally and recorded in a public ‘blockchain’,’ which can be thought of as a distributed accounting system.

While Bitcoin’s algorithm provides safeguards against ‘counterfeiting’ of the currency, the eco-system is still vulnerable to theft. Users keep keys to their Bitcoins and make transactions with the help of wallets. Exchanges facilitate trade inbetween Bitcoins and fiat currencies, and also permit for storing Bitcoins. Bitcoins can be stolen through wallets or exchanges. Exchanges have been targeted more frequently than wallets because many wallets are located on users’ (local) computers, while exchanges frequently store customer deposits in their own (much larger) wallets.

The supply of most cryptocurrencies increases at a predetermined rate, and cannot be switched by any central authority. There are about fifteen million Bitcoins presently in circulation, with the ultimate number eventually reaching twenty one million. The immovable supply in the long run creates concerns about the deflationary aspect of the currency.

While Bitcoin shows superb promise to disrupt existing payment systems through innovations in its technical design, the Bitcoin ecosystem one has been the frequent target of attacks by financially motivated criminals. Due to the unregulated, decentralised environment in which they operate, cryptocurrencies are under constant threat of attack.

Bitcoin only recently became a subject of research in economics. However, the topic has been of interest for longer in computer science (for early work by computer scientists on incentives, see Babaioff et al. 2012, and Eyal and Sirer 2014.) Numerous researchers have conducted studies in order to document and combat threats such as Ponzi schemes, money laundering, mining botnets, and the theft of cryptocurrency wallets (Moeser et al. 2013, Vasek and Moore 2015, Vasek et al. 2016, Yuxing et al. 2014). Ron and Shamir (2013) attempt to identify suspicious trading activity by building a graph of Bitcoin transactions found in the public ledger. None of these papers can associate individual transactions with specific users of the currency exchanges.

In latest work, we showcase that the very first time Bitcoin reached an exchange rate of more than $1,000, the meteoric rise was driven by fraud (Gandal et al. 2017). We leverage a unique and very detailed dataset to examine suspicious trading activity that occurred over a ten-month period in two thousand thirteen on Mt. Gox, the leading Bitcoin currency exchange at the time. We very first quantify the extent of the suspicious/fraudulent trading activity and showcase that it constitutes a large fraction of trading on the days the activity occurred. We then demonstrate how this trading activity affected the exchange rates at Mt. Gox and other leading currency exchanges.

Figure 1 Bitcoin–US dollar exchange rate, with periods of suspicious activity shaded

While it was the superior currency exchange when Bitcoin very first shot to prominence in early 2013, behind the scenes, Tokyo-based Mt. Gox was in trouble. In addition to suffering from repeated denial-of-service attacks and Bitcoin thefts, two unauthorised traders were able to transact on the exchange without spending real money. In the very first case, a trader dubbed ‘Markus’ was credited with Bitcoins by duplicating previously finished transactions. In the 2nd case, a trader dubbed ‘Willy’ bought Bitcoins from traders by ‘crediting’ the sellers’ accounts with fiat currencies that, in many cases, could not be withdrawn. Figure one shows when these fraudulent traders were active, along with the Bitcoin–US dollar exchange rate. Most noteworthy is that Willy’s operation coincided with an unprecedented leap in the price of Bitcoin: from around $150 to over $1000. In early 2014, Mt. Gox collapsed, and the Bitcoin price fell with it. Only recently, in early 2017, has Bitcoin surpassed the levels of the earlier rise.

However, how do we know that the rise was caused by the fraudulent trades? Fortunately for us as researchers, the unauthorised trades did not take place every day. Table one shows the daily switch in the Bitcoin–US dollar exchange rate for various time periods on Mt. Gox. In the two quarters before unauthorised trading commenced, the daily price increase was, on average, positive but relatively puny: a $0.21 increase in the very first period and a $1 increase in the 2nd period. During the third quarter, when unauthorised trading embarked, the price rose by an average of $Trio.15 on the seventeen days in which Markus traded, but fell on average by $0.51 on the seventy five days he did not trade. However, it is during the final quarter, when Willy began trading, that the difference became stark. On the fifty days in which Willy traded, the Bitcoin price rose by an average of $21.85. On the forty one days in which Willy did not make unauthorizsed purchases, the price fell by $0.88 on average. (Table one is very similar for the other leading exchanges as well.)

Table 1 Average daily switch in BTC/USD exchange rate as a function of fraudulent activity Two

In our utter paper, we conduct a regression analysis to examine whether other factors such as the relatively numerous and varied attacks on the Mt. Gox exchange could explain the switch in the daily Bitcoin price, both at Mt. Gox and other leading exchanges (Gandal et al. 2017).

The analysis confirms that only Willy’s trading presence affected the price. The estimated coefficient (on the dummy variable for whether Willy was active) is virtually the same ($21.65) as in Table 1. We conclude that the suspicious trading activity of a single actor was the primary cause of the massive spike in the Bitcoin–US dollar exchange rate, in which the rate rose from around $150 to over $1,000 in just two months in late 2013. The fall was almost as precipitous: the Mt. Gox exchange folded due to insolvency in early 2014, and it has taken more than three years for Bitcoin to match the rise triggered by fraudulent transactions.

Why should we care about the Bitcoin manipulation that took place in 2013? After all, the Bitcoin ecosystem is not almost as significant as the Fresh York Stock Exchange. Nonetheless, latest trends indicate that Bitcoin is becoming an significant asset in the financial system.

Trading in cryptocurrency assets has exploded recently. In the case of Bitcoin, during the one year period ending in mid-June 2017, the market capitalisation enlargened massively from around $7 billion to $45 billion; that is an increase of over 500% in one year. The market cap of other cryptocurrencies surged by even more. In the one-year period ending in mid-May 2017, the market value of cryptocurrencies excluding Bitcoin surged from $1.7 billion to more than $29 billion; that is an increase of more than 1,900%. The markets for these other cryptocurrencies are very skinny and subject to manipulation. Given that we now know the Bitcoin price has been artificially inflated by unauthorised trades in the past, we must view the present rise with good caution, and not necessarily consider it a ‘healthy bubble’, as recently claimed in The Economist (2017).

As mainstream finance invests in cryptocurrency assets and as countries take steps toward legalising Bitcoin as a payment system (as Japan did in April 2017), it is significant to understand how susceptible cryptocurrency markets are to manipulation. We encourage the nascent cryptocurrency industry to work with regulators and researchers to share anonymised transaction data so that more confidence can be placed in the veracity of exchange rates.

References

Babaioff, M, S Dobzinski, S Oren and A Zohar (2012), “On bitcoin and crimson balloons” in Proceedings of the 13th ACM Conference on Electronic Commerce, pp. 56-73.

Eyal, I and E Sirer (2014), “Majority is not Enough: Bitcoin Mining is Vulnerable”, paper introduced at the Eighteenth International Conference on Financial Cryptography and Data Security, Barbados, 3-7 March.

Gandal, N, J Hamrick, T Moore and T Oberman (2017), “Price Manipulation in the Bitcoin Ecosystem,” CEPR Discussion Paper No. 12061.

Mooser, M, R Bohme and D Breuker (2013), “An inquiry into money laundering implements in the Bitcoin ecosystem”, in Proceedings of the Seventh APWG eCrime Re-searcher’s Summit, pp. 1-14.

Ron, D and A Shamir (2013), “Quantitative analysis of the total Bitcoin transaction graph”, in Financial Cryptography and Data Security, Vol. Seven thousand eight hundred fifty nine of Lecture Notes in Computer Science, pp. 6-24.

Vasek, M and T Moore (2015), “There’s no free lunch, even using Bitcoin: Tracking the popularity and profits of virtual currency scams”, in R Bohme and T Okamoto (eds), Financial Cryptography and Data Security, volume eight thousand nine hundred seventy five of Lecture Notes in Computer Science, pp. 44-61.

Vasek, M, J Bonneau, R Castellucci, C Keith and T Moore (2016), “The Bitcoin brain drain: a brief paper on the use and manhandle of bitcoin brain wallets”, in Financial Cryptography and Data Security, Lecture Notes in Computer Science.

Yuxing Huang, D, H Dharmdasani, S Meiklejohn, V Dave, C Grier, D McCoy, S Savage, N Weaver, A Snoeren and K Levchenko (2014), “Botcoin: Monetizing stolen cycles”, in Proceedings of the Network and Distributed System Security Symposium.

Endnotes

[1] The Bitcoin ecosystem includes the core network for propagating transactions, the blockchain, and many intermediaries such as currency exchanges, mining pools, and payment processors that facilitate trade.

[Two] Markus was primarily active in period Trio, but he was also active a few days during periods 1,Two, and Four. He was not active on the same days as Willy, who was only active in period Four.

Price manipulation in the Bitcoin ecosystem, VOX, CEPR’s Policy Portal

VOX CEPR’s Policy Portal

Research-based policy analysis and commentary from leading economists

Price manipulation in the Bitcoin ecosystem

Neil Gandal, JT Hamrick, Tyler Moore, Tali Oberman twenty two June two thousand seventeen

The cryptocurrency Bitcoin has attracted widespread interest, in large part due to wild swings in its valuation. This column considers an earlier rise in the Bitcoin price to investigate what is driving the currency’s price spikes. The two thousand thirteen rise was caused by fraudulent trades taking place at the largest Bitcoin currency exchange at the time. This finding has implications for policymakers as they weigh what, if anything, to do about regulating cryptocurrencies in light of the record high Bitcoin valuation that many fear is a bubble.

Related

The digital currency Bitcoin was introduced in 2009. Bitcoin and the many other digital currencies are primarily online currencies. The key currencies are those based primarily on cryptography, and Bitcoin is the leading ‘cryptocurrency’.

Bitcoin has experienced a meteoric rise in popularity since its introduction. While digital currencies were proposed as early as the 1980s, Bitcoin was the very first to catch on. The total value of all Bitcoins in circulation reached $45 billion in June 2017. Its success has inspired scores of rivaling cryptocurrencies that go after a similar design. Bitcoin and most other cryptocurrencies do not require a central authority to validate and lodge transactions. Instead, these currencies use cryptography (and an internal incentive system) to control transactions, manage the supply, and prevent fraud. Payments are validated by a decentralised network. Once confirmed, all transactions are stored digitally and recorded in a public ‘blockchain’,’ which can be thought of as a distributed accounting system.

While Bitcoin’s algorithm provides safeguards against ‘counterfeiting’ of the currency, the eco-system is still vulnerable to theft. Users keep keys to their Bitcoins and make transactions with the help of wallets. Exchanges facilitate trade inbetween Bitcoins and fiat currencies, and also permit for storing Bitcoins. Bitcoins can be stolen through wallets or exchanges. Exchanges have been targeted more frequently than wallets because many wallets are located on users’ (local) computers, while exchanges frequently store customer deposits in their own (much larger) wallets.

The supply of most cryptocurrencies increases at a predetermined rate, and cannot be switched by any central authority. There are about fifteen million Bitcoins presently in circulation, with the ultimate number eventually reaching twenty one million. The stationary supply in the long run creates concerns about the deflationary aspect of the currency.

While Bitcoin shows fine promise to disrupt existing payment systems through innovations in its technical design, the Bitcoin ecosystem one has been the frequent target of attacks by financially motivated criminals. Due to the unregulated, decentralised environment in which they operate, cryptocurrencies are under constant threat of attack.

Bitcoin only recently became a subject of research in economics. However, the topic has been of interest for longer in computer science (for early work by computer scientists on incentives, see Babaioff et al. 2012, and Eyal and Sirer 2014.) Numerous researchers have conducted studies in order to document and combat threats such as Ponzi schemes, money laundering, mining botnets, and the theft of cryptocurrency wallets (Moeser et al. 2013, Vasek and Moore 2015, Vasek et al. 2016, Yuxing et al. 2014). Ron and Shamir (2013) attempt to identify suspicious trading activity by building a graph of Bitcoin transactions found in the public ledger. None of these papers can associate individual transactions with specific users of the currency exchanges.

In latest work, we demonstrate that the very first time Bitcoin reached an exchange rate of more than $1,000, the meteoric rise was driven by fraud (Gandal et al. 2017). We leverage a unique and very detailed dataset to examine suspicious trading activity that occurred over a ten-month period in two thousand thirteen on Mt. Gox, the leading Bitcoin currency exchange at the time. We very first quantify the extent of the suspicious/fraudulent trading activity and display that it constitutes a large fraction of trading on the days the activity occurred. We then showcase how this trading activity affected the exchange rates at Mt. Gox and other leading currency exchanges.

Figure 1 Bitcoin–US dollar exchange rate, with periods of suspicious activity shaded

While it was the superior currency exchange when Bitcoin very first shot to prominence in early 2013, behind the scenes, Tokyo-based Mt. Gox was in trouble. In addition to suffering from repeated denial-of-service attacks and Bitcoin thefts, two unauthorised traders were able to transact on the exchange without spending real money. In the very first case, a trader dubbed ‘Markus’ was credited with Bitcoins by duplicating previously finished transactions. In the 2nd case, a trader dubbed ‘Willy’ bought Bitcoins from traders by ‘crediting’ the sellers’ accounts with fiat currencies that, in many cases, could not be withdrawn. Figure one shows when these fraudulent traders were active, along with the Bitcoin–US dollar exchange rate. Most noteworthy is that Willy’s operation coincided with an unprecedented leap in the price of Bitcoin: from around $150 to over $1000. In early 2014, Mt. Gox collapsed, and the Bitcoin price fell with it. Only recently, in early 2017, has Bitcoin surpassed the levels of the earlier rise.

However, how do we know that the rise was caused by the fraudulent trades? Fortunately for us as researchers, the unauthorised trades did not take place every day. Table one shows the daily switch in the Bitcoin–US dollar exchange rate for various time periods on Mt. Gox. In the two quarters before unauthorised trading commenced, the daily price increase was, on average, positive but relatively puny: a $0.21 increase in the very first period and a $1 increase in the 2nd period. During the third quarter, when unauthorised trading embarked, the price rose by an average of $Trio.15 on the seventeen days in which Markus traded, but fell on average by $0.51 on the seventy five days he did not trade. However, it is during the final quarter, when Willy began trading, that the difference became stark. On the fifty days in which Willy traded, the Bitcoin price rose by an average of $21.85. On the forty one days in which Willy did not make unauthorizsed purchases, the price fell by $0.88 on average. (Table one is very similar for the other leading exchanges as well.)

Table 1 Average daily switch in BTC/USD exchange rate as a function of fraudulent activity Two

In our utter paper, we conduct a regression analysis to examine whether other factors such as the relatively numerous and varied attacks on the Mt. Gox exchange could explain the switch in the daily Bitcoin price, both at Mt. Gox and other leading exchanges (Gandal et al. 2017).

The analysis confirms that only Willy’s trading presence affected the price. The estimated coefficient (on the dummy variable for whether Willy was active) is virtually the same ($21.65) as in Table 1. We conclude that the suspicious trading activity of a single actor was the primary cause of the massive spike in the Bitcoin–US dollar exchange rate, in which the rate rose from around $150 to over $1,000 in just two months in late 2013. The fall was almost as precipitous: the Mt. Gox exchange folded due to insolvency in early 2014, and it has taken more than three years for Bitcoin to match the rise triggered by fraudulent transactions.

Why should we care about the Bitcoin manipulation that took place in 2013? After all, the Bitcoin ecosystem is not almost as significant as the Fresh York Stock Exchange. Nonetheless, latest trends indicate that Bitcoin is becoming an significant asset in the financial system.

Trading in cryptocurrency assets has exploded recently. In the case of Bitcoin, during the one year period ending in mid-June 2017, the market capitalisation enhanced massively from around $7 billion to $45 billion; that is an increase of over 500% in one year. The market cap of other cryptocurrencies surged by even more. In the one-year period ending in mid-May 2017, the market value of cryptocurrencies excluding Bitcoin surged from $1.7 billion to more than $29 billion; that is an increase of more than 1,900%. The markets for these other cryptocurrencies are very skinny and subject to manipulation. Given that we now know the Bitcoin price has been artificially inflated by unauthorised trades in the past, we must view the present rise with superb caution, and not necessarily consider it a ‘healthy bubble’, as recently claimed in The Economist (2017).

As mainstream finance invests in cryptocurrency assets and as countries take steps toward legalising Bitcoin as a payment system (as Japan did in April 2017), it is significant to understand how susceptible cryptocurrency markets are to manipulation. We encourage the nascent cryptocurrency industry to work with regulators and researchers to share anonymised transaction data so that more confidence can be placed in the veracity of exchange rates.

References

Babaioff, M, S Dobzinski, S Oren and A Zohar (2012), “On bitcoin and crimson balloons” in Proceedings of the 13th ACM Conference on Electronic Commerce, pp. 56-73.

Eyal, I and E Sirer (2014), “Majority is not Enough: Bitcoin Mining is Vulnerable”, paper introduced at the Eighteenth International Conference on Financial Cryptography and Data Security, Barbados, 3-7 March.

Gandal, N, J Hamrick, T Moore and T Oberman (2017), “Price Manipulation in the Bitcoin Ecosystem,” CEPR Discussion Paper No. 12061.

Mooser, M, R Bohme and D Breuker (2013), “An inquiry into money laundering devices in the Bitcoin ecosystem”, in Proceedings of the Seventh APWG eCrime Re-searcher’s Summit, pp. 1-14.

Ron, D and A Shamir (2013), “Quantitative analysis of the utter Bitcoin transaction graph”, in Financial Cryptography and Data Security, Vol. Seven thousand eight hundred fifty nine of Lecture Notes in Computer Science, pp. 6-24.

Vasek, M and T Moore (2015), “There’s no free lunch, even using Bitcoin: Tracking the popularity and profits of virtual currency scams”, in R Bohme and T Okamoto (eds), Financial Cryptography and Data Security, volume eight thousand nine hundred seventy five of Lecture Notes in Computer Science, pp. 44-61.

Vasek, M, J Bonneau, R Castellucci, C Keith and T Moore (2016), “The Bitcoin brain drain: a brief paper on the use and manhandle of bitcoin brain wallets”, in Financial Cryptography and Data Security, Lecture Notes in Computer Science.

Yuxing Huang, D, H Dharmdasani, S Meiklejohn, V Dave, C Grier, D McCoy, S Savage, N Weaver, A Snoeren and K Levchenko (2014), “Botcoin: Monetizing stolen cycles”, in Proceedings of the Network and Distributed System Security Symposium.

Endnotes

[1] The Bitcoin ecosystem includes the core network for propagating transactions, the blockchain, and many intermediaries such as currency exchanges, mining pools, and payment processors that facilitate trade.

[Two] Markus was primarily active in period Three, but he was also active a few days during periods 1,Two, and Four. He was not active on the same days as Willy, who was only active in period Four.

Price manipulation in the Bitcoin ecosystem, VOX, CEPR’s Policy Portal

VOX CEPR’s Policy Portal

Research-based policy analysis and commentary from leading economists

Price manipulation in the Bitcoin ecosystem

Neil Gandal, JT Hamrick, Tyler Moore, Tali Oberman twenty two June two thousand seventeen

The cryptocurrency Bitcoin has attracted widespread interest, in large part due to wild swings in its valuation. This column considers an earlier rise in the Bitcoin price to investigate what is driving the currency’s price spikes. The two thousand thirteen rise was caused by fraudulent trades taking place at the largest Bitcoin currency exchange at the time. This finding has implications for policymakers as they weigh what, if anything, to do about regulating cryptocurrencies in light of the record high Bitcoin valuation that many fear is a bubble.

Related

The digital currency Bitcoin was introduced in 2009. Bitcoin and the many other digital currencies are primarily online currencies. The key currencies are those based primarily on cryptography, and Bitcoin is the leading ‘cryptocurrency’.

Bitcoin has experienced a meteoric rise in popularity since its introduction. While digital currencies were proposed as early as the 1980s, Bitcoin was the very first to catch on. The total value of all Bitcoins in circulation reached $45 billion in June 2017. Its success has inspired scores of contesting cryptocurrencies that go after a similar design. Bitcoin and most other cryptocurrencies do not require a central authority to validate and lodge transactions. Instead, these currencies use cryptography (and an internal incentive system) to control transactions, manage the supply, and prevent fraud. Payments are validated by a decentralised network. Once confirmed, all transactions are stored digitally and recorded in a public ‘blockchain’,’ which can be thought of as a distributed accounting system.

While Bitcoin’s algorithm provides safeguards against ‘counterfeiting’ of the currency, the eco-system is still vulnerable to theft. Users keep keys to their Bitcoins and make transactions with the help of wallets. Exchanges facilitate trade inbetween Bitcoins and fiat currencies, and also permit for storing Bitcoins. Bitcoins can be stolen through wallets or exchanges. Exchanges have been targeted more frequently than wallets because many wallets are located on users’ (local) computers, while exchanges frequently store customer deposits in their own (much larger) wallets.

The supply of most cryptocurrencies increases at a predetermined rate, and cannot be switched by any central authority. There are about fifteen million Bitcoins presently in circulation, with the ultimate number eventually reaching twenty one million. The stationary supply in the long run creates concerns about the deflationary aspect of the currency.

While Bitcoin shows excellent promise to disrupt existing payment systems through innovations in its technical design, the Bitcoin ecosystem one has been the frequent target of attacks by financially motivated criminals. Due to the unregulated, decentralised environment in which they operate, cryptocurrencies are under constant threat of attack.

Bitcoin only recently became a subject of research in economics. However, the topic has been of interest for longer in computer science (for early work by computer scientists on incentives, see Babaioff et al. 2012, and Eyal and Sirer 2014.) Numerous researchers have conducted studies in order to document and combat threats such as Ponzi schemes, money laundering, mining botnets, and the theft of cryptocurrency wallets (Moeser et al. 2013, Vasek and Moore 2015, Vasek et al. 2016, Yuxing et al. 2014). Ron and Shamir (2013) attempt to identify suspicious trading activity by building a graph of Bitcoin transactions found in the public ledger. None of these papers can associate individual transactions with specific users of the currency exchanges.

In latest work, we display that the very first time Bitcoin reached an exchange rate of more than $1,000, the meteoric rise was driven by fraud (Gandal et al. 2017). We leverage a unique and very detailed dataset to examine suspicious trading activity that occurred over a ten-month period in two thousand thirteen on Mt. Gox, the leading Bitcoin currency exchange at the time. We very first quantify the extent of the suspicious/fraudulent trading activity and demonstrate that it constitutes a large fraction of trading on the days the activity occurred. We then demonstrate how this trading activity affected the exchange rates at Mt. Gox and other leading currency exchanges.

Figure 1 Bitcoin–US dollar exchange rate, with periods of suspicious activity shaded

While it was the superior currency exchange when Bitcoin very first shot to prominence in early 2013, behind the scenes, Tokyo-based Mt. Gox was in trouble. In addition to suffering from repeated denial-of-service attacks and Bitcoin thefts, two unauthorised traders were able to transact on the exchange without spending real money. In the very first case, a trader dubbed ‘Markus’ was credited with Bitcoins by duplicating previously ended transactions. In the 2nd case, a trader dubbed ‘Willy’ bought Bitcoins from traders by ‘crediting’ the sellers’ accounts with fiat currencies that, in many cases, could not be withdrawn. Figure one shows when these fraudulent traders were active, along with the Bitcoin–US dollar exchange rate. Most noteworthy is that Willy’s operation coincided with an unprecedented hop in the price of Bitcoin: from around $150 to over $1000. In early 2014, Mt. Gox collapsed, and the Bitcoin price fell with it. Only recently, in early 2017, has Bitcoin surpassed the levels of the earlier rise.

However, how do we know that the rise was caused by the fraudulent trades? Fortunately for us as researchers, the unauthorised trades did not take place every day. Table one shows the daily switch in the Bitcoin–US dollar exchange rate for various time periods on Mt. Gox. In the two quarters before unauthorised trading commenced, the daily price increase was, on average, positive but relatively petite: a $0.21 increase in the very first period and a $1 increase in the 2nd period. During the third quarter, when unauthorised trading embarked, the price rose by an average of $Trio.15 on the seventeen days in which Markus traded, but fell on average by $0.51 on the seventy five days he did not trade. However, it is during the final quarter, when Willy began trading, that the difference became stark. On the fifty days in which Willy traded, the Bitcoin price rose by an average of $21.85. On the forty one days in which Willy did not make unauthorizsed purchases, the price fell by $0.88 on average. (Table one is very similar for the other leading exchanges as well.)

Table 1 Average daily switch in BTC/USD exchange rate as a function of fraudulent activity Two

In our total paper, we conduct a regression analysis to examine whether other factors such as the relatively numerous and varied attacks on the Mt. Gox exchange could explain the switch in the daily Bitcoin price, both at Mt. Gox and other leading exchanges (Gandal et al. 2017).

The analysis confirms that only Willy’s trading presence affected the price. The estimated coefficient (on the dummy variable for whether Willy was active) is virtually the same ($21.65) as in Table 1. We conclude that the suspicious trading activity of a single actor was the primary cause of the massive spike in the Bitcoin–US dollar exchange rate, in which the rate rose from around $150 to over $1,000 in just two months in late 2013. The fall was almost as precipitous: the Mt. Gox exchange folded due to insolvency in early 2014, and it has taken more than three years for Bitcoin to match the rise triggered by fraudulent transactions.

Why should we care about the Bitcoin manipulation that took place in 2013? After all, the Bitcoin ecosystem is not almost as significant as the Fresh York Stock Exchange. Nonetheless, latest trends indicate that Bitcoin is becoming an significant asset in the financial system.

Trading in cryptocurrency assets has exploded recently. In the case of Bitcoin, during the one year period ending in mid-June 2017, the market capitalisation enlargened massively from around $7 billion to $45 billion; that is an increase of over 500% in one year. The market cap of other cryptocurrencies surged by even more. In the one-year period ending in mid-May 2017, the market value of cryptocurrencies excluding Bitcoin surged from $1.7 billion to more than $29 billion; that is an increase of more than 1,900%. The markets for these other cryptocurrencies are very lean and subject to manipulation. Given that we now know the Bitcoin price has been artificially inflated by unauthorised trades in the past, we must view the present rise with fine caution, and not necessarily consider it a ‘healthy bubble’, as recently claimed in The Economist (2017).

As mainstream finance invests in cryptocurrency assets and as countries take steps toward legalising Bitcoin as a payment system (as Japan did in April 2017), it is significant to understand how susceptible cryptocurrency markets are to manipulation. We encourage the nascent cryptocurrency industry to work with regulators and researchers to share anonymised transaction data so that more confidence can be placed in the veracity of exchange rates.

References

Babaioff, M, S Dobzinski, S Oren and A Zohar (2012), “On bitcoin and crimson balloons” in Proceedings of the 13th ACM Conference on Electronic Commerce, pp. 56-73.

Eyal, I and E Sirer (2014), “Majority is not Enough: Bitcoin Mining is Vulnerable”, paper introduced at the Eighteenth International Conference on Financial Cryptography and Data Security, Barbados, 3-7 March.

Gandal, N, J Hamrick, T Moore and T Oberman (2017), “Price Manipulation in the Bitcoin Ecosystem,” CEPR Discussion Paper No. 12061.

Mooser, M, R Bohme and D Breuker (2013), “An inquiry into money laundering instruments in the Bitcoin ecosystem”, in Proceedings of the Seventh APWG eCrime Re-searcher’s Summit, pp. 1-14.

Ron, D and A Shamir (2013), “Quantitative analysis of the total Bitcoin transaction graph”, in Financial Cryptography and Data Security, Vol. Seven thousand eight hundred fifty nine of Lecture Notes in Computer Science, pp. 6-24.

Vasek, M and T Moore (2015), “There’s no free lunch, even using Bitcoin: Tracking the popularity and profits of virtual currency scams”, in R Bohme and T Okamoto (eds), Financial Cryptography and Data Security, volume eight thousand nine hundred seventy five of Lecture Notes in Computer Science, pp. 44-61.

Vasek, M, J Bonneau, R Castellucci, C Keith and T Moore (2016), “The Bitcoin brain drain: a brief paper on the use and manhandle of bitcoin brain wallets”, in Financial Cryptography and Data Security, Lecture Notes in Computer Science.

Yuxing Huang, D, H Dharmdasani, S Meiklejohn, V Dave, C Grier, D McCoy, S Savage, N Weaver, A Snoeren and K Levchenko (2014), “Botcoin: Monetizing stolen cycles”, in Proceedings of the Network and Distributed System Security Symposium.

Endnotes

[1] The Bitcoin ecosystem includes the core network for propagating transactions, the blockchain, and many intermediaries such as currency exchanges, mining pools, and payment processors that facilitate trade.

[Two] Markus was primarily active in period Trio, but he was also active a few days during periods 1,Two, and Four. He was not active on the same days as Willy, who was only active in period Four.

Price manipulation in the Bitcoin ecosystem, VOX, CEPR’s Policy Portal

VOX CEPR’s Policy Portal

Research-based policy analysis and commentary from leading economists

Price manipulation in the Bitcoin ecosystem

Neil Gandal, JT Hamrick, Tyler Moore, Tali Oberman twenty two June two thousand seventeen

The cryptocurrency Bitcoin has attracted widespread interest, in large part due to wild swings in its valuation. This column considers an earlier rise in the Bitcoin price to investigate what is driving the currency’s price spikes. The two thousand thirteen rise was caused by fraudulent trades taking place at the largest Bitcoin currency exchange at the time. This finding has implications for policymakers as they weigh what, if anything, to do about regulating cryptocurrencies in light of the record high Bitcoin valuation that many fear is a bubble.

Related

The digital currency Bitcoin was introduced in 2009. Bitcoin and the many other digital currencies are primarily online currencies. The key currencies are those based primarily on cryptography, and Bitcoin is the leading ‘cryptocurrency’.

Bitcoin has experienced a meteoric rise in popularity since its introduction. While digital currencies were proposed as early as the 1980s, Bitcoin was the very first to catch on. The total value of all Bitcoins in circulation reached $45 billion in June 2017. Its success has inspired scores of rivaling cryptocurrencies that go after a similar design. Bitcoin and most other cryptocurrencies do not require a central authority to validate and lodge transactions. Instead, these currencies use cryptography (and an internal incentive system) to control transactions, manage the supply, and prevent fraud. Payments are validated by a decentralised network. Once confirmed, all transactions are stored digitally and recorded in a public ‘blockchain’,’ which can be thought of as a distributed accounting system.

While Bitcoin’s algorithm provides safeguards against ‘counterfeiting’ of the currency, the eco-system is still vulnerable to theft. Users keep keys to their Bitcoins and make transactions with the help of wallets. Exchanges facilitate trade inbetween Bitcoins and fiat currencies, and also permit for storing Bitcoins. Bitcoins can be stolen through wallets or exchanges. Exchanges have been targeted more frequently than wallets because many wallets are located on users’ (local) computers, while exchanges frequently store customer deposits in their own (much larger) wallets.

The supply of most cryptocurrencies increases at a predetermined rate, and cannot be switched by any central authority. There are about fifteen million Bitcoins presently in circulation, with the ultimate number eventually reaching twenty one million. The immovable supply in the long run creates concerns about the deflationary aspect of the currency.

While Bitcoin shows excellent promise to disrupt existing payment systems through innovations in its technical design, the Bitcoin ecosystem one has been the frequent target of attacks by financially motivated criminals. Due to the unregulated, decentralised environment in which they operate, cryptocurrencies are under constant threat of attack.

Bitcoin only recently became a subject of research in economics. However, the topic has been of interest for longer in computer science (for early work by computer scientists on incentives, see Babaioff et al. 2012, and Eyal and Sirer 2014.) Numerous researchers have conducted studies in order to document and combat threats such as Ponzi schemes, money laundering, mining botnets, and the theft of cryptocurrency wallets (Moeser et al. 2013, Vasek and Moore 2015, Vasek et al. 2016, Yuxing et al. 2014). Ron and Shamir (2013) attempt to identify suspicious trading activity by building a graph of Bitcoin transactions found in the public ledger. None of these papers can associate individual transactions with specific users of the currency exchanges.

In latest work, we demonstrate that the very first time Bitcoin reached an exchange rate of more than $1,000, the meteoric rise was driven by fraud (Gandal et al. 2017). We leverage a unique and very detailed dataset to examine suspicious trading activity that occurred over a ten-month period in two thousand thirteen on Mt. Gox, the leading Bitcoin currency exchange at the time. We very first quantify the extent of the suspicious/fraudulent trading activity and showcase that it constitutes a large fraction of trading on the days the activity occurred. We then showcase how this trading activity affected the exchange rates at Mt. Gox and other leading currency exchanges.

Figure 1 Bitcoin–US dollar exchange rate, with periods of suspicious activity shaded

While it was the superior currency exchange when Bitcoin very first shot to prominence in early 2013, behind the scenes, Tokyo-based Mt. Gox was in trouble. In addition to suffering from repeated denial-of-service attacks and Bitcoin thefts, two unauthorised traders were able to transact on the exchange without spending real money. In the very first case, a trader dubbed ‘Markus’ was credited with Bitcoins by duplicating previously finished transactions. In the 2nd case, a trader dubbed ‘Willy’ bought Bitcoins from traders by ‘crediting’ the sellers’ accounts with fiat currencies that, in many cases, could not be withdrawn. Figure one shows when these fraudulent traders were active, along with the Bitcoin–US dollar exchange rate. Most noteworthy is that Willy’s operation coincided with an unprecedented leap in the price of Bitcoin: from around $150 to over $1000. In early 2014, Mt. Gox collapsed, and the Bitcoin price fell with it. Only recently, in early 2017, has Bitcoin surpassed the levels of the earlier rise.

However, how do we know that the rise was caused by the fraudulent trades? Fortunately for us as researchers, the unauthorised trades did not take place every day. Table one shows the daily switch in the Bitcoin–US dollar exchange rate for various time periods on Mt. Gox. In the two quarters before unauthorised trading commenced, the daily price increase was, on average, positive but relatively petite: a $0.21 increase in the very first period and a $1 increase in the 2nd period. During the third quarter, when unauthorised trading commenced, the price rose by an average of $Trio.15 on the seventeen days in which Markus traded, but fell on average by $0.51 on the seventy five days he did not trade. However, it is during the final quarter, when Willy began trading, that the difference became stark. On the fifty days in which Willy traded, the Bitcoin price rose by an average of $21.85. On the forty one days in which Willy did not make unauthorizsed purchases, the price fell by $0.88 on average. (Table one is very similar for the other leading exchanges as well.)

Table 1 Average daily switch in BTC/USD exchange rate as a function of fraudulent activity Two

In our utter paper, we conduct a regression analysis to examine whether other factors such as the relatively numerous and varied attacks on the Mt. Gox exchange could explain the switch in the daily Bitcoin price, both at Mt. Gox and other leading exchanges (Gandal et al. 2017).

The analysis confirms that only Willy’s trading presence affected the price. The estimated coefficient (on the dummy variable for whether Willy was active) is virtually the same ($21.65) as in Table 1. We conclude that the suspicious trading activity of a single actor was the primary cause of the massive spike in the Bitcoin–US dollar exchange rate, in which the rate rose from around $150 to over $1,000 in just two months in late 2013. The fall was almost as precipitous: the Mt. Gox exchange folded due to insolvency in early 2014, and it has taken more than three years for Bitcoin to match the rise triggered by fraudulent transactions.

Why should we care about the Bitcoin manipulation that took place in 2013? After all, the Bitcoin ecosystem is not almost as significant as the Fresh York Stock Exchange. Nonetheless, latest trends indicate that Bitcoin is becoming an significant asset in the financial system.

Trading in cryptocurrency assets has exploded recently. In the case of Bitcoin, during the one year period ending in mid-June 2017, the market capitalisation enhanced massively from around $7 billion to $45 billion; that is an increase of over 500% in one year. The market cap of other cryptocurrencies surged by even more. In the one-year period ending in mid-May 2017, the market value of cryptocurrencies excluding Bitcoin surged from $1.7 billion to more than $29 billion; that is an increase of more than 1,900%. The markets for these other cryptocurrencies are very skinny and subject to manipulation. Given that we now know the Bitcoin price has been artificially inflated by unauthorised trades in the past, we must view the present rise with superb caution, and not necessarily consider it a ‘healthy bubble’, as recently claimed in The Economist (2017).

As mainstream finance invests in cryptocurrency assets and as countries take steps toward legalising Bitcoin as a payment system (as Japan did in April 2017), it is significant to understand how susceptible cryptocurrency markets are to manipulation. We encourage the nascent cryptocurrency industry to work with regulators and researchers to share anonymised transaction data so that more confidence can be placed in the veracity of exchange rates.

References

Babaioff, M, S Dobzinski, S Oren and A Zohar (2012), “On bitcoin and crimson balloons” in Proceedings of the 13th ACM Conference on Electronic Commerce, pp. 56-73.

Eyal, I and E Sirer (2014), “Majority is not Enough: Bitcoin Mining is Vulnerable”, paper introduced at the Eighteenth International Conference on Financial Cryptography and Data Security, Barbados, 3-7 March.

Gandal, N, J Hamrick, T Moore and T Oberman (2017), “Price Manipulation in the Bitcoin Ecosystem,” CEPR Discussion Paper No. 12061.

Mooser, M, R Bohme and D Breuker (2013), “An inquiry into money laundering implements in the Bitcoin ecosystem”, in Proceedings of the Seventh APWG eCrime Re-searcher’s Summit, pp. 1-14.

Ron, D and A Shamir (2013), “Quantitative analysis of the utter Bitcoin transaction graph”, in Financial Cryptography and Data Security, Vol. Seven thousand eight hundred fifty nine of Lecture Notes in Computer Science, pp. 6-24.

Vasek, M and T Moore (2015), “There’s no free lunch, even using Bitcoin: Tracking the popularity and profits of virtual currency scams”, in R Bohme and T Okamoto (eds), Financial Cryptography and Data Security, volume eight thousand nine hundred seventy five of Lecture Notes in Computer Science, pp. 44-61.

Vasek, M, J Bonneau, R Castellucci, C Keith and T Moore (2016), “The Bitcoin brain drain: a brief paper on the use and manhandle of bitcoin brain wallets”, in Financial Cryptography and Data Security, Lecture Notes in Computer Science.

Yuxing Huang, D, H Dharmdasani, S Meiklejohn, V Dave, C Grier, D McCoy, S Savage, N Weaver, A Snoeren and K Levchenko (2014), “Botcoin: Monetizing stolen cycles”, in Proceedings of the Network and Distributed System Security Symposium.

Endnotes

[1] The Bitcoin ecosystem includes the core network for propagating transactions, the blockchain, and many intermediaries such as currency exchanges, mining pools, and payment processors that facilitate trade.

[Two] Markus was primarily active in period Trio, but he was also active a few days during periods 1,Two, and Four. He was not active on the same days as Willy, who was only active in period Four.

Price manipulation in the Bitcoin ecosystem, VOX, CEPR’s Policy Portal

VOX CEPR’s Policy Portal

Research-based policy analysis and commentary from leading economists

Price manipulation in the Bitcoin ecosystem

Neil Gandal, JT Hamrick, Tyler Moore, Tali Oberman twenty two June two thousand seventeen

The cryptocurrency Bitcoin has attracted widespread interest, in large part due to wild swings in its valuation. This column considers an earlier rise in the Bitcoin price to investigate what is driving the currency’s price spikes. The two thousand thirteen rise was caused by fraudulent trades taking place at the largest Bitcoin currency exchange at the time. This finding has implications for policymakers as they weigh what, if anything, to do about regulating cryptocurrencies in light of the record high Bitcoin valuation that many fear is a bubble.

Related

The digital currency Bitcoin was introduced in 2009. Bitcoin and the many other digital currencies are primarily online currencies. The key currencies are those based primarily on cryptography, and Bitcoin is the leading ‘cryptocurrency’.

Bitcoin has experienced a meteoric rise in popularity since its introduction. While digital currencies were proposed as early as the 1980s, Bitcoin was the very first to catch on. The total value of all Bitcoins in circulation reached $45 billion in June 2017. Its success has inspired scores of challenging cryptocurrencies that go after a similar design. Bitcoin and most other cryptocurrencies do not require a central authority to validate and lodge transactions. Instead, these currencies use cryptography (and an internal incentive system) to control transactions, manage the supply, and prevent fraud. Payments are validated by a decentralised network. Once confirmed, all transactions are stored digitally and recorded in a public ‘blockchain’,’ which can be thought of as a distributed accounting system.

While Bitcoin’s algorithm provides safeguards against ‘counterfeiting’ of the currency, the eco-system is still vulnerable to theft. Users keep keys to their Bitcoins and make transactions with the help of wallets. Exchanges facilitate trade inbetween Bitcoins and fiat currencies, and also permit for storing Bitcoins. Bitcoins can be stolen through wallets or exchanges. Exchanges have been targeted more frequently than wallets because many wallets are located on users’ (local) computers, while exchanges frequently store customer deposits in their own (much larger) wallets.

The supply of most cryptocurrencies increases at a predetermined rate, and cannot be switched by any central authority. There are about fifteen million Bitcoins presently in circulation, with the ultimate number eventually reaching twenty one million. The stationary supply in the long run creates concerns about the deflationary aspect of the currency.

While Bitcoin shows excellent promise to disrupt existing payment systems through innovations in its technical design, the Bitcoin ecosystem one has been the frequent target of attacks by financially motivated criminals. Due to the unregulated, decentralised environment in which they operate, cryptocurrencies are under constant threat of attack.

Bitcoin only recently became a subject of research in economics. However, the topic has been of interest for longer in computer science (for early work by computer scientists on incentives, see Babaioff et al. 2012, and Eyal and Sirer 2014.) Numerous researchers have conducted studies in order to document and combat threats such as Ponzi schemes, money laundering, mining botnets, and the theft of cryptocurrency wallets (Moeser et al. 2013, Vasek and Moore 2015, Vasek et al. 2016, Yuxing et al. 2014). Ron and Shamir (2013) attempt to identify suspicious trading activity by building a graph of Bitcoin transactions found in the public ledger. None of these papers can associate individual transactions with specific users of the currency exchanges.

In latest work, we demonstrate that the very first time Bitcoin reached an exchange rate of more than $1,000, the meteoric rise was driven by fraud (Gandal et al. 2017). We leverage a unique and very detailed dataset to examine suspicious trading activity that occurred over a ten-month period in two thousand thirteen on Mt. Gox, the leading Bitcoin currency exchange at the time. We very first quantify the extent of the suspicious/fraudulent trading activity and showcase that it constitutes a large fraction of trading on the days the activity occurred. We then showcase how this trading activity affected the exchange rates at Mt. Gox and other leading currency exchanges.

Figure 1 Bitcoin–US dollar exchange rate, with periods of suspicious activity shaded

While it was the superior currency exchange when Bitcoin very first shot to prominence in early 2013, behind the scenes, Tokyo-based Mt. Gox was in trouble. In addition to suffering from repeated denial-of-service attacks and Bitcoin thefts, two unauthorised traders were able to transact on the exchange without spending real money. In the very first case, a trader dubbed ‘Markus’ was credited with Bitcoins by duplicating previously finished transactions. In the 2nd case, a trader dubbed ‘Willy’ bought Bitcoins from traders by ‘crediting’ the sellers’ accounts with fiat currencies that, in many cases, could not be withdrawn. Figure one shows when these fraudulent traders were active, along with the Bitcoin–US dollar exchange rate. Most noteworthy is that Willy’s operation coincided with an unprecedented leap in the price of Bitcoin: from around $150 to over $1000. In early 2014, Mt. Gox collapsed, and the Bitcoin price fell with it. Only recently, in early 2017, has Bitcoin surpassed the levels of the earlier rise.

However, how do we know that the rise was caused by the fraudulent trades? Fortunately for us as researchers, the unauthorised trades did not take place every day. Table one shows the daily switch in the Bitcoin–US dollar exchange rate for various time periods on Mt. Gox. In the two quarters before unauthorised trading commenced, the daily price increase was, on average, positive but relatively petite: a $0.21 increase in the very first period and a $1 increase in the 2nd period. During the third quarter, when unauthorised trading began, the price rose by an average of $Trio.15 on the seventeen days in which Markus traded, but fell on average by $0.51 on the seventy five days he did not trade. However, it is during the final quarter, when Willy began trading, that the difference became stark. On the fifty days in which Willy traded, the Bitcoin price rose by an average of $21.85. On the forty one days in which Willy did not make unauthorizsed purchases, the price fell by $0.88 on average. (Table one is very similar for the other leading exchanges as well.)

Table 1 Average daily switch in BTC/USD exchange rate as a function of fraudulent activity Two

In our utter paper, we conduct a regression analysis to examine whether other factors such as the relatively numerous and varied attacks on the Mt. Gox exchange could explain the switch in the daily Bitcoin price, both at Mt. Gox and other leading exchanges (Gandal et al. 2017).

The analysis confirms that only Willy’s trading presence affected the price. The estimated coefficient (on the dummy variable for whether Willy was active) is virtually the same ($21.65) as in Table 1. We conclude that the suspicious trading activity of a single actor was the primary cause of the massive spike in the Bitcoin–US dollar exchange rate, in which the rate rose from around $150 to over $1,000 in just two months in late 2013. The fall was almost as precipitous: the Mt. Gox exchange folded due to insolvency in early 2014, and it has taken more than three years for Bitcoin to match the rise triggered by fraudulent transactions.

Why should we care about the Bitcoin manipulation that took place in 2013? After all, the Bitcoin ecosystem is not almost as significant as the Fresh York Stock Exchange. Nonetheless, latest trends indicate that Bitcoin is becoming an significant asset in the financial system.

Trading in cryptocurrency assets has exploded recently. In the case of Bitcoin, during the one year period ending in mid-June 2017, the market capitalisation enhanced massively from around $7 billion to $45 billion; that is an increase of over 500% in one year. The market cap of other cryptocurrencies surged by even more. In the one-year period ending in mid-May 2017, the market value of cryptocurrencies excluding Bitcoin surged from $1.7 billion to more than $29 billion; that is an increase of more than 1,900%. The markets for these other cryptocurrencies are very skinny and subject to manipulation. Given that we now know the Bitcoin price has been artificially inflated by unauthorised trades in the past, we must view the present rise with fine caution, and not necessarily consider it a ‘healthy bubble’, as recently claimed in The Economist (2017).

As mainstream finance invests in cryptocurrency assets and as countries take steps toward legalising Bitcoin as a payment system (as Japan did in April 2017), it is significant to understand how susceptible cryptocurrency markets are to manipulation. We encourage the nascent cryptocurrency industry to work with regulators and researchers to share anonymised transaction data so that more confidence can be placed in the veracity of exchange rates.

References

Babaioff, M, S Dobzinski, S Oren and A Zohar (2012), “On bitcoin and crimson balloons” in Proceedings of the 13th ACM Conference on Electronic Commerce, pp. 56-73.

Eyal, I and E Sirer (2014), “Majority is not Enough: Bitcoin Mining is Vulnerable”, paper introduced at the Eighteenth International Conference on Financial Cryptography and Data Security, Barbados, 3-7 March.

Gandal, N, J Hamrick, T Moore and T Oberman (2017), “Price Manipulation in the Bitcoin Ecosystem,” CEPR Discussion Paper No. 12061.

Mooser, M, R Bohme and D Breuker (2013), “An inquiry into money laundering devices in the Bitcoin ecosystem”, in Proceedings of the Seventh APWG eCrime Re-searcher’s Summit, pp. 1-14.

Ron, D and A Shamir (2013), “Quantitative analysis of the total Bitcoin transaction graph”, in Financial Cryptography and Data Security, Vol. Seven thousand eight hundred fifty nine of Lecture Notes in Computer Science, pp. 6-24.

Vasek, M and T Moore (2015), “There’s no free lunch, even using Bitcoin: Tracking the popularity and profits of virtual currency scams”, in R Bohme and T Okamoto (eds), Financial Cryptography and Data Security, volume eight thousand nine hundred seventy five of Lecture Notes in Computer Science, pp. 44-61.

Vasek, M, J Bonneau, R Castellucci, C Keith and T Moore (2016), “The Bitcoin brain drain: a brief paper on the use and manhandle of bitcoin brain wallets”, in Financial Cryptography and Data Security, Lecture Notes in Computer Science.

Yuxing Huang, D, H Dharmdasani, S Meiklejohn, V Dave, C Grier, D McCoy, S Savage, N Weaver, A Snoeren and K Levchenko (2014), “Botcoin: Monetizing stolen cycles”, in Proceedings of the Network and Distributed System Security Symposium.

Endnotes

[1] The Bitcoin ecosystem includes the core network for propagating transactions, the blockchain, and many intermediaries such as currency exchanges, mining pools, and payment processors that facilitate trade.

[Two] Markus was primarily active in period Trio, but he was also active a few days during periods 1,Two, and Four. He was not active on the same days as Willy, who was only active in period Four.

Price manipulation in the Bitcoin ecosystem, VOX, CEPR’s Policy Portal

VOX CEPR’s Policy Portal

Research-based policy analysis and commentary from leading economists

Price manipulation in the Bitcoin ecosystem

Neil Gandal, JT Hamrick, Tyler Moore, Tali Oberman twenty two June two thousand seventeen

The cryptocurrency Bitcoin has attracted widespread interest, in large part due to wild swings in its valuation. This column considers an earlier rise in the Bitcoin price to investigate what is driving the currency’s price spikes. The two thousand thirteen rise was caused by fraudulent trades taking place at the largest Bitcoin currency exchange at the time. This finding has implications for policymakers as they weigh what, if anything, to do about regulating cryptocurrencies in light of the record high Bitcoin valuation that many fear is a bubble.

Related

The digital currency Bitcoin was introduced in 2009. Bitcoin and the many other digital currencies are primarily online currencies. The key currencies are those based primarily on cryptography, and Bitcoin is the leading ‘cryptocurrency’.

Bitcoin has experienced a meteoric rise in popularity since its introduction. While digital currencies were proposed as early as the 1980s, Bitcoin was the very first to catch on. The total value of all Bitcoins in circulation reached $45 billion in June 2017. Its success has inspired scores of rivaling cryptocurrencies that go after a similar design. Bitcoin and most other cryptocurrencies do not require a central authority to validate and lodge transactions. Instead, these currencies use cryptography (and an internal incentive system) to control transactions, manage the supply, and prevent fraud. Payments are validated by a decentralised network. Once confirmed, all transactions are stored digitally and recorded in a public ‘blockchain’,’ which can be thought of as a distributed accounting system.

While Bitcoin’s algorithm provides safeguards against ‘counterfeiting’ of the currency, the eco-system is still vulnerable to theft. Users keep keys to their Bitcoins and make transactions with the help of wallets. Exchanges facilitate trade inbetween Bitcoins and fiat currencies, and also permit for storing Bitcoins. Bitcoins can be stolen through wallets or exchanges. Exchanges have been targeted more frequently than wallets because many wallets are located on users’ (local) computers, while exchanges frequently store customer deposits in their own (much larger) wallets.

The supply of most cryptocurrencies increases at a predetermined rate, and cannot be switched by any central authority. There are about fifteen million Bitcoins presently in circulation, with the ultimate number eventually reaching twenty one million. The motionless supply in the long run creates concerns about the deflationary aspect of the currency.

While Bitcoin shows fine promise to disrupt existing payment systems through innovations in its technical design, the Bitcoin ecosystem one has been the frequent target of attacks by financially motivated criminals. Due to the unregulated, decentralised environment in which they operate, cryptocurrencies are under constant threat of attack.

Bitcoin only recently became a subject of research in economics. However, the topic has been of interest for longer in computer science (for early work by computer scientists on incentives, see Babaioff et al. 2012, and Eyal and Sirer 2014.) Numerous researchers have conducted studies in order to document and combat threats such as Ponzi schemes, money laundering, mining botnets, and the theft of cryptocurrency wallets (Moeser et al. 2013, Vasek and Moore 2015, Vasek et al. 2016, Yuxing et al. 2014). Ron and Shamir (2013) attempt to identify suspicious trading activity by building a graph of Bitcoin transactions found in the public ledger. None of these papers can associate individual transactions with specific users of the currency exchanges.

In latest work, we showcase that the very first time Bitcoin reached an exchange rate of more than $1,000, the meteoric rise was driven by fraud (Gandal et al. 2017). We leverage a unique and very detailed dataset to examine suspicious trading activity that occurred over a ten-month period in two thousand thirteen on Mt. Gox, the leading Bitcoin currency exchange at the time. We very first quantify the extent of the suspicious/fraudulent trading activity and display that it constitutes a large fraction of trading on the days the activity occurred. We then display how this trading activity affected the exchange rates at Mt. Gox and other leading currency exchanges.

Figure 1 Bitcoin–US dollar exchange rate, with periods of suspicious activity shaded

While it was the superior currency exchange when Bitcoin very first shot to prominence in early 2013, behind the scenes, Tokyo-based Mt. Gox was in trouble. In addition to suffering from repeated denial-of-service attacks and Bitcoin thefts, two unauthorised traders were able to transact on the exchange without spending real money. In the very first case, a trader dubbed ‘Markus’ was credited with Bitcoins by duplicating previously finished transactions. In the 2nd case, a trader dubbed ‘Willy’ bought Bitcoins from traders by ‘crediting’ the sellers’ accounts with fiat currencies that, in many cases, could not be withdrawn. Figure one shows when these fraudulent traders were active, along with the Bitcoin–US dollar exchange rate. Most noteworthy is that Willy’s operation coincided with an unprecedented leap in the price of Bitcoin: from around $150 to over $1000. In early 2014, Mt. Gox collapsed, and the Bitcoin price fell with it. Only recently, in early 2017, has Bitcoin surpassed the levels of the earlier rise.

However, how do we know that the rise was caused by the fraudulent trades? Fortunately for us as researchers, the unauthorised trades did not take place every day. Table one shows the daily switch in the Bitcoin–US dollar exchange rate for various time periods on Mt. Gox. In the two quarters before unauthorised trading commenced, the daily price increase was, on average, positive but relatively petite: a $0.21 increase in the very first period and a $1 increase in the 2nd period. During the third quarter, when unauthorised trading began, the price rose by an average of $Three.15 on the seventeen days in which Markus traded, but fell on average by $0.51 on the seventy five days he did not trade. However, it is during the final quarter, when Willy began trading, that the difference became stark. On the fifty days in which Willy traded, the Bitcoin price rose by an average of $21.85. On the forty one days in which Willy did not make unauthorizsed purchases, the price fell by $0.88 on average. (Table one is very similar for the other leading exchanges as well.)

Table 1 Average daily switch in BTC/USD exchange rate as a function of fraudulent activity Two

In our total paper, we conduct a regression analysis to examine whether other factors such as the relatively numerous and varied attacks on the Mt. Gox exchange could explain the switch in the daily Bitcoin price, both at Mt. Gox and other leading exchanges (Gandal et al. 2017).

The analysis confirms that only Willy’s trading presence affected the price. The estimated coefficient (on the dummy variable for whether Willy was active) is virtually the same ($21.65) as in Table 1. We conclude that the suspicious trading activity of a single actor was the primary cause of the massive spike in the Bitcoin–US dollar exchange rate, in which the rate rose from around $150 to over $1,000 in just two months in late 2013. The fall was almost as precipitous: the Mt. Gox exchange folded due to insolvency in early 2014, and it has taken more than three years for Bitcoin to match the rise triggered by fraudulent transactions.

Why should we care about the Bitcoin manipulation that took place in 2013? After all, the Bitcoin ecosystem is not almost as significant as the Fresh York Stock Exchange. Nonetheless, latest trends indicate that Bitcoin is becoming an significant asset in the financial system.

Trading in cryptocurrency assets has exploded recently. In the case of Bitcoin, during the one year period ending in mid-June 2017, the market capitalisation enlargened massively from around $7 billion to $45 billion; that is an increase of over 500% in one year. The market cap of other cryptocurrencies surged by even more. In the one-year period ending in mid-May 2017, the market value of cryptocurrencies excluding Bitcoin surged from $1.7 billion to more than $29 billion; that is an increase of more than 1,900%. The markets for these other cryptocurrencies are very lean and subject to manipulation. Given that we now know the Bitcoin price has been artificially inflated by unauthorised trades in the past, we must view the present rise with excellent caution, and not necessarily consider it a ‘healthy bubble’, as recently claimed in The Economist (2017).

As mainstream finance invests in cryptocurrency assets and as countries take steps toward legalising Bitcoin as a payment system (as Japan did in April 2017), it is significant to understand how susceptible cryptocurrency markets are to manipulation. We encourage the nascent cryptocurrency industry to work with regulators and researchers to share anonymised transaction data so that more confidence can be placed in the veracity of exchange rates.

References

Babaioff, M, S Dobzinski, S Oren and A Zohar (2012), “On bitcoin and crimson balloons” in Proceedings of the 13th ACM Conference on Electronic Commerce, pp. 56-73.

Eyal, I and E Sirer (2014), “Majority is not Enough: Bitcoin Mining is Vulnerable”, paper introduced at the Eighteenth International Conference on Financial Cryptography and Data Security, Barbados, 3-7 March.

Gandal, N, J Hamrick, T Moore and T Oberman (2017), “Price Manipulation in the Bitcoin Ecosystem,” CEPR Discussion Paper No. 12061.

Mooser, M, R Bohme and D Breuker (2013), “An inquiry into money laundering instruments in the Bitcoin ecosystem”, in Proceedings of the Seventh APWG eCrime Re-searcher’s Summit, pp. 1-14.

Ron, D and A Shamir (2013), “Quantitative analysis of the utter Bitcoin transaction graph”, in Financial Cryptography and Data Security, Vol. Seven thousand eight hundred fifty nine of Lecture Notes in Computer Science, pp. 6-24.

Vasek, M and T Moore (2015), “There’s no free lunch, even using Bitcoin: Tracking the popularity and profits of virtual currency scams”, in R Bohme and T Okamoto (eds), Financial Cryptography and Data Security, volume eight thousand nine hundred seventy five of Lecture Notes in Computer Science, pp. 44-61.

Vasek, M, J Bonneau, R Castellucci, C Keith and T Moore (2016), “The Bitcoin brain drain: a brief paper on the use and manhandle of bitcoin brain wallets”, in Financial Cryptography and Data Security, Lecture Notes in Computer Science.

Yuxing Huang, D, H Dharmdasani, S Meiklejohn, V Dave, C Grier, D McCoy, S Savage, N Weaver, A Snoeren and K Levchenko (2014), “Botcoin: Monetizing stolen cycles”, in Proceedings of the Network and Distributed System Security Symposium.

Endnotes

[1] The Bitcoin ecosystem includes the core network for propagating transactions, the blockchain, and many intermediaries such as currency exchanges, mining pools, and payment processors that facilitate trade.

[Two] Markus was primarily active in period Three, but he was also active a few days during periods 1,Two, and Four. He was not active on the same days as Willy, who was only active in period Four.

Price manipulation in the Bitcoin ecosystem, VOX, CEPR’s Policy Portal

VOX CEPR’s Policy Portal

Research-based policy analysis and commentary from leading economists

Price manipulation in the Bitcoin ecosystem

Neil Gandal, JT Hamrick, Tyler Moore, Tali Oberman twenty two June two thousand seventeen

The cryptocurrency Bitcoin has attracted widespread interest, in large part due to wild swings in its valuation. This column considers an earlier rise in the Bitcoin price to investigate what is driving the currency’s price spikes. The two thousand thirteen rise was caused by fraudulent trades taking place at the largest Bitcoin currency exchange at the time. This finding has implications for policymakers as they weigh what, if anything, to do about regulating cryptocurrencies in light of the record high Bitcoin valuation that many fear is a bubble.

Related

The digital currency Bitcoin was introduced in 2009. Bitcoin and the many other digital currencies are primarily online currencies. The key currencies are those based primarily on cryptography, and Bitcoin is the leading ‘cryptocurrency’.

Bitcoin has experienced a meteoric rise in popularity since its introduction. While digital currencies were proposed as early as the 1980s, Bitcoin was the very first to catch on. The total value of all Bitcoins in circulation reached $45 billion in June 2017. Its success has inspired scores of challenging cryptocurrencies that go after a similar design. Bitcoin and most other cryptocurrencies do not require a central authority to validate and lodge transactions. Instead, these currencies use cryptography (and an internal incentive system) to control transactions, manage the supply, and prevent fraud. Payments are validated by a decentralised network. Once confirmed, all transactions are stored digitally and recorded in a public ‘blockchain’,’ which can be thought of as a distributed accounting system.

While Bitcoin’s algorithm provides safeguards against ‘counterfeiting’ of the currency, the eco-system is still vulnerable to theft. Users keep keys to their Bitcoins and make transactions with the help of wallets. Exchanges facilitate trade inbetween Bitcoins and fiat currencies, and also permit for storing Bitcoins. Bitcoins can be stolen through wallets or exchanges. Exchanges have been targeted more frequently than wallets because many wallets are located on users’ (local) computers, while exchanges frequently store customer deposits in their own (much larger) wallets.

The supply of most cryptocurrencies increases at a predetermined rate, and cannot be switched by any central authority. There are about fifteen million Bitcoins presently in circulation, with the ultimate number eventually reaching twenty one million. The immobile supply in the long run creates concerns about the deflationary aspect of the currency.

While Bitcoin shows good promise to disrupt existing payment systems through innovations in its technical design, the Bitcoin ecosystem one has been the frequent target of attacks by financially motivated criminals. Due to the unregulated, decentralised environment in which they operate, cryptocurrencies are under constant threat of attack.

Bitcoin only recently became a subject of research in economics. However, the topic has been of interest for longer in computer science (for early work by computer scientists on incentives, see Babaioff et al. 2012, and Eyal and Sirer 2014.) Numerous researchers have conducted studies in order to document and combat threats such as Ponzi schemes, money laundering, mining botnets, and the theft of cryptocurrency wallets (Moeser et al. 2013, Vasek and Moore 2015, Vasek et al. 2016, Yuxing et al. 2014). Ron and Shamir (2013) attempt to identify suspicious trading activity by building a graph of Bitcoin transactions found in the public ledger. None of these papers can associate individual transactions with specific users of the currency exchanges.

In latest work, we display that the very first time Bitcoin reached an exchange rate of more than $1,000, the meteoric rise was driven by fraud (Gandal et al. 2017). We leverage a unique and very detailed dataset to examine suspicious trading activity that occurred over a ten-month period in two thousand thirteen on Mt. Gox, the leading Bitcoin currency exchange at the time. We very first quantify the extent of the suspicious/fraudulent trading activity and showcase that it constitutes a large fraction of trading on the days the activity occurred. We then demonstrate how this trading activity affected the exchange rates at Mt. Gox and other leading currency exchanges.

Figure 1 Bitcoin–US dollar exchange rate, with periods of suspicious activity shaded

While it was the superior currency exchange when Bitcoin very first shot to prominence in early 2013, behind the scenes, Tokyo-based Mt. Gox was in trouble. In addition to suffering from repeated denial-of-service attacks and Bitcoin thefts, two unauthorised traders were able to transact on the exchange without spending real money. In the very first case, a trader dubbed ‘Markus’ was credited with Bitcoins by duplicating previously finished transactions. In the 2nd case, a trader dubbed ‘Willy’ bought Bitcoins from traders by ‘crediting’ the sellers’ accounts with fiat currencies that, in many cases, could not be withdrawn. Figure one shows when these fraudulent traders were active, along with the Bitcoin–US dollar exchange rate. Most noteworthy is that Willy’s operation coincided with an unprecedented leap in the price of Bitcoin: from around $150 to over $1000. In early 2014, Mt. Gox collapsed, and the Bitcoin price fell with it. Only recently, in early 2017, has Bitcoin surpassed the levels of the earlier rise.

However, how do we know that the rise was caused by the fraudulent trades? Fortunately for us as researchers, the unauthorised trades did not take place every day. Table one shows the daily switch in the Bitcoin–US dollar exchange rate for various time periods on Mt. Gox. In the two quarters before unauthorised trading commenced, the daily price increase was, on average, positive but relatively puny: a $0.21 increase in the very first period and a $1 increase in the 2nd period. During the third quarter, when unauthorised trading embarked, the price rose by an average of $Trio.15 on the seventeen days in which Markus traded, but fell on average by $0.51 on the seventy five days he did not trade. However, it is during the final quarter, when Willy began trading, that the difference became stark. On the fifty days in which Willy traded, the Bitcoin price rose by an average of $21.85. On the forty one days in which Willy did not make unauthorizsed purchases, the price fell by $0.88 on average. (Table one is very similar for the other leading exchanges as well.)

Table 1 Average daily switch in BTC/USD exchange rate as a function of fraudulent activity Two

In our total paper, we conduct a regression analysis to examine whether other factors such as the relatively numerous and varied attacks on the Mt. Gox exchange could explain the switch in the daily Bitcoin price, both at Mt. Gox and other leading exchanges (Gandal et al. 2017).

The analysis confirms that only Willy’s trading presence affected the price. The estimated coefficient (on the dummy variable for whether Willy was active) is virtually the same ($21.65) as in Table 1. We conclude that the suspicious trading activity of a single actor was the primary cause of the massive spike in the Bitcoin–US dollar exchange rate, in which the rate rose from around $150 to over $1,000 in just two months in late 2013. The fall was almost as precipitous: the Mt. Gox exchange folded due to insolvency in early 2014, and it has taken more than three years for Bitcoin to match the rise triggered by fraudulent transactions.

Why should we care about the Bitcoin manipulation that took place in 2013? After all, the Bitcoin ecosystem is not almost as significant as the Fresh York Stock Exchange. Nonetheless, latest trends indicate that Bitcoin is becoming an significant asset in the financial system.

Trading in cryptocurrency assets has exploded recently. In the case of Bitcoin, during the one year period ending in mid-June 2017, the market capitalisation enhanced massively from around $7 billion to $45 billion; that is an increase of over 500% in one year. The market cap of other cryptocurrencies surged by even more. In the one-year period ending in mid-May 2017, the market value of cryptocurrencies excluding Bitcoin surged from $1.7 billion to more than $29 billion; that is an increase of more than 1,900%. The markets for these other cryptocurrencies are very skinny and subject to manipulation. Given that we now know the Bitcoin price has been artificially inflated by unauthorised trades in the past, we must view the present rise with superb caution, and not necessarily consider it a ‘healthy bubble’, as recently claimed in The Economist (2017).

As mainstream finance invests in cryptocurrency assets and as countries take steps toward legalising Bitcoin as a payment system (as Japan did in April 2017), it is significant to understand how susceptible cryptocurrency markets are to manipulation. We encourage the nascent cryptocurrency industry to work with regulators and researchers to share anonymised transaction data so that more confidence can be placed in the veracity of exchange rates.

References

Babaioff, M, S Dobzinski, S Oren and A Zohar (2012), “On bitcoin and crimson balloons” in Proceedings of the 13th ACM Conference on Electronic Commerce, pp. 56-73.

Eyal, I and E Sirer (2014), “Majority is not Enough: Bitcoin Mining is Vulnerable”, paper introduced at the Eighteenth International Conference on Financial Cryptography and Data Security, Barbados, 3-7 March.

Gandal, N, J Hamrick, T Moore and T Oberman (2017), “Price Manipulation in the Bitcoin Ecosystem,” CEPR Discussion Paper No. 12061.

Mooser, M, R Bohme and D Breuker (2013), “An inquiry into money laundering devices in the Bitcoin ecosystem”, in Proceedings of the Seventh APWG eCrime Re-searcher’s Summit, pp. 1-14.

Ron, D and A Shamir (2013), “Quantitative analysis of the total Bitcoin transaction graph”, in Financial Cryptography and Data Security, Vol. Seven thousand eight hundred fifty nine of Lecture Notes in Computer Science, pp. 6-24.

Vasek, M and T Moore (2015), “There’s no free lunch, even using Bitcoin: Tracking the popularity and profits of virtual currency scams”, in R Bohme and T Okamoto (eds), Financial Cryptography and Data Security, volume eight thousand nine hundred seventy five of Lecture Notes in Computer Science, pp. 44-61.

Vasek, M, J Bonneau, R Castellucci, C Keith and T Moore (2016), “The Bitcoin brain drain: a brief paper on the use and manhandle of bitcoin brain wallets”, in Financial Cryptography and Data Security, Lecture Notes in Computer Science.

Yuxing Huang, D, H Dharmdasani, S Meiklejohn, V Dave, C Grier, D McCoy, S Savage, N Weaver, A Snoeren and K Levchenko (2014), “Botcoin: Monetizing stolen cycles”, in Proceedings of the Network and Distributed System Security Symposium.

Endnotes

[1] The Bitcoin ecosystem includes the core network for propagating transactions, the blockchain, and many intermediaries such as currency exchanges, mining pools, and payment processors that facilitate trade.

[Two] Markus was primarily active in period Three, but he was also active a few days during periods 1,Two, and Four. He was not active on the same days as Willy, who was only active in period Four.

Price manipulation in the Bitcoin ecosystem, VOX, CEPR’s Policy Portal

VOX CEPR’s Policy Portal

Research-based policy analysis and commentary from leading economists

Price manipulation in the Bitcoin ecosystem

Neil Gandal, JT Hamrick, Tyler Moore, Tali Oberman twenty two June two thousand seventeen

The cryptocurrency Bitcoin has attracted widespread interest, in large part due to wild swings in its valuation. This column considers an earlier rise in the Bitcoin price to investigate what is driving the currency’s price spikes. The two thousand thirteen rise was caused by fraudulent trades taking place at the largest Bitcoin currency exchange at the time. This finding has implications for policymakers as they weigh what, if anything, to do about regulating cryptocurrencies in light of the record high Bitcoin valuation that many fear is a bubble.

Related

The digital currency Bitcoin was introduced in 2009. Bitcoin and the many other digital currencies are primarily online currencies. The key currencies are those based primarily on cryptography, and Bitcoin is the leading ‘cryptocurrency’.

Bitcoin has experienced a meteoric rise in popularity since its introduction. While digital currencies were proposed as early as the 1980s, Bitcoin was the very first to catch on. The total value of all Bitcoins in circulation reached $45 billion in June 2017. Its success has inspired scores of rivaling cryptocurrencies that go after a similar design. Bitcoin and most other cryptocurrencies do not require a central authority to validate and lodge transactions. Instead, these currencies use cryptography (and an internal incentive system) to control transactions, manage the supply, and prevent fraud. Payments are validated by a decentralised network. Once confirmed, all transactions are stored digitally and recorded in a public ‘blockchain’,’ which can be thought of as a distributed accounting system.

While Bitcoin’s algorithm provides safeguards against ‘counterfeiting’ of the currency, the eco-system is still vulnerable to theft. Users keep keys to their Bitcoins and make transactions with the help of wallets. Exchanges facilitate trade inbetween Bitcoins and fiat currencies, and also permit for storing Bitcoins. Bitcoins can be stolen through wallets or exchanges. Exchanges have been targeted more frequently than wallets because many wallets are located on users’ (local) computers, while exchanges frequently store customer deposits in their own (much larger) wallets.

The supply of most cryptocurrencies increases at a predetermined rate, and cannot be switched by any central authority. There are about fifteen million Bitcoins presently in circulation, with the ultimate number eventually reaching twenty one million. The stationary supply in the long run creates concerns about the deflationary aspect of the currency.

While Bitcoin shows good promise to disrupt existing payment systems through innovations in its technical design, the Bitcoin ecosystem one has been the frequent target of attacks by financially motivated criminals. Due to the unregulated, decentralised environment in which they operate, cryptocurrencies are under constant threat of attack.

Bitcoin only recently became a subject of research in economics. However, the topic has been of interest for longer in computer science (for early work by computer scientists on incentives, see Babaioff et al. 2012, and Eyal and Sirer 2014.) Numerous researchers have conducted studies in order to document and combat threats such as Ponzi schemes, money laundering, mining botnets, and the theft of cryptocurrency wallets (Moeser et al. 2013, Vasek and Moore 2015, Vasek et al. 2016, Yuxing et al. 2014). Ron and Shamir (2013) attempt to identify suspicious trading activity by building a graph of Bitcoin transactions found in the public ledger. None of these papers can associate individual transactions with specific users of the currency exchanges.

In latest work, we showcase that the very first time Bitcoin reached an exchange rate of more than $1,000, the meteoric rise was driven by fraud (Gandal et al. 2017). We leverage a unique and very detailed dataset to examine suspicious trading activity that occurred over a ten-month period in two thousand thirteen on Mt. Gox, the leading Bitcoin currency exchange at the time. We very first quantify the extent of the suspicious/fraudulent trading activity and demonstrate that it constitutes a large fraction of trading on the days the activity occurred. We then showcase how this trading activity affected the exchange rates at Mt. Gox and other leading currency exchanges.

Figure 1 Bitcoin–US dollar exchange rate, with periods of suspicious activity shaded

While it was the superior currency exchange when Bitcoin very first shot to prominence in early 2013, behind the scenes, Tokyo-based Mt. Gox was in trouble. In addition to suffering from repeated denial-of-service attacks and Bitcoin thefts, two unauthorised traders were able to transact on the exchange without spending real money. In the very first case, a trader dubbed ‘Markus’ was credited with Bitcoins by duplicating previously finished transactions. In the 2nd case, a trader dubbed ‘Willy’ bought Bitcoins from traders by ‘crediting’ the sellers’ accounts with fiat currencies that, in many cases, could not be withdrawn. Figure one shows when these fraudulent traders were active, along with the Bitcoin–US dollar exchange rate. Most noteworthy is that Willy’s operation coincided with an unprecedented leap in the price of Bitcoin: from around $150 to over $1000. In early 2014, Mt. Gox collapsed, and the Bitcoin price fell with it. Only recently, in early 2017, has Bitcoin surpassed the levels of the earlier rise.

However, how do we know that the rise was caused by the fraudulent trades? Fortunately for us as researchers, the unauthorised trades did not take place every day. Table one shows the daily switch in the Bitcoin–US dollar exchange rate for various time periods on Mt. Gox. In the two quarters before unauthorised trading commenced, the daily price increase was, on average, positive but relatively petite: a $0.21 increase in the very first period and a $1 increase in the 2nd period. During the third quarter, when unauthorised trading began, the price rose by an average of $Three.15 on the seventeen days in which Markus traded, but fell on average by $0.51 on the seventy five days he did not trade. However, it is during the final quarter, when Willy began trading, that the difference became stark. On the fifty days in which Willy traded, the Bitcoin price rose by an average of $21.85. On the forty one days in which Willy did not make unauthorizsed purchases, the price fell by $0.88 on average. (Table one is very similar for the other leading exchanges as well.)

Table 1 Average daily switch in BTC/USD exchange rate as a function of fraudulent activity Two

In our total paper, we conduct a regression analysis to examine whether other factors such as the relatively numerous and varied attacks on the Mt. Gox exchange could explain the switch in the daily Bitcoin price, both at Mt. Gox and other leading exchanges (Gandal et al. 2017).

The analysis confirms that only Willy’s trading presence affected the price. The estimated coefficient (on the dummy variable for whether Willy was active) is virtually the same ($21.65) as in Table 1. We conclude that the suspicious trading activity of a single actor was the primary cause of the massive spike in the Bitcoin–US dollar exchange rate, in which the rate rose from around $150 to over $1,000 in just two months in late 2013. The fall was almost as precipitous: the Mt. Gox exchange folded due to insolvency in early 2014, and it has taken more than three years for Bitcoin to match the rise triggered by fraudulent transactions.

Why should we care about the Bitcoin manipulation that took place in 2013? After all, the Bitcoin ecosystem is not almost as significant as the Fresh York Stock Exchange. Nonetheless, latest trends indicate that Bitcoin is becoming an significant asset in the financial system.

Trading in cryptocurrency assets has exploded recently. In the case of Bitcoin, during the one year period ending in mid-June 2017, the market capitalisation enlargened massively from around $7 billion to $45 billion; that is an increase of over 500% in one year. The market cap of other cryptocurrencies surged by even more. In the one-year period ending in mid-May 2017, the market value of cryptocurrencies excluding Bitcoin surged from $1.7 billion to more than $29 billion; that is an increase of more than 1,900%. The markets for these other cryptocurrencies are very lean and subject to manipulation. Given that we now know the Bitcoin price has been artificially inflated by unauthorised trades in the past, we must view the present rise with superb caution, and not necessarily consider it a ‘healthy bubble’, as recently claimed in The Economist (2017).

As mainstream finance invests in cryptocurrency assets and as countries take steps toward legalising Bitcoin as a payment system (as Japan did in April 2017), it is significant to understand how susceptible cryptocurrency markets are to manipulation. We encourage the nascent cryptocurrency industry to work with regulators and researchers to share anonymised transaction data so that more confidence can be placed in the veracity of exchange rates.

References

Babaioff, M, S Dobzinski, S Oren and A Zohar (2012), “On bitcoin and crimson balloons” in Proceedings of the 13th ACM Conference on Electronic Commerce, pp. 56-73.

Eyal, I and E Sirer (2014), “Majority is not Enough: Bitcoin Mining is Vulnerable”, paper introduced at the Eighteenth International Conference on Financial Cryptography and Data Security, Barbados, 3-7 March.

Gandal, N, J Hamrick, T Moore and T Oberman (2017), “Price Manipulation in the Bitcoin Ecosystem,” CEPR Discussion Paper No. 12061.

Mooser, M, R Bohme and D Breuker (2013), “An inquiry into money laundering contraptions in the Bitcoin ecosystem”, in Proceedings of the Seventh APWG eCrime Re-searcher’s Summit, pp. 1-14.

Ron, D and A Shamir (2013), “Quantitative analysis of the utter Bitcoin transaction graph”, in Financial Cryptography and Data Security, Vol. Seven thousand eight hundred fifty nine of Lecture Notes in Computer Science, pp. 6-24.

Vasek, M and T Moore (2015), “There’s no free lunch, even using Bitcoin: Tracking the popularity and profits of virtual currency scams”, in R Bohme and T Okamoto (eds), Financial Cryptography and Data Security, volume eight thousand nine hundred seventy five of Lecture Notes in Computer Science, pp. 44-61.

Vasek, M, J Bonneau, R Castellucci, C Keith and T Moore (2016), “The Bitcoin brain drain: a brief paper on the use and manhandle of bitcoin brain wallets”, in Financial Cryptography and Data Security, Lecture Notes in Computer Science.

Yuxing Huang, D, H Dharmdasani, S Meiklejohn, V Dave, C Grier, D McCoy, S Savage, N Weaver, A Snoeren and K Levchenko (2014), “Botcoin: Monetizing stolen cycles”, in Proceedings of the Network and Distributed System Security Symposium.

Endnotes

[1] The Bitcoin ecosystem includes the core network for propagating transactions, the blockchain, and many intermediaries such as currency exchanges, mining pools, and payment processors that facilitate trade.

[Two] Markus was primarily active in period Three, but he was also active a few days during periods 1,Two, and Four. He was not active on the same days as Willy, who was only active in period Four.

Price manipulation in the Bitcoin ecosystem, VOX, CEPR’s Policy Portal

VOX CEPR’s Policy Portal

Research-based policy analysis and commentary from leading economists

Price manipulation in the Bitcoin ecosystem

Neil Gandal, JT Hamrick, Tyler Moore, Tali Oberman twenty two June two thousand seventeen

The cryptocurrency Bitcoin has attracted widespread interest, in large part due to wild swings in its valuation. This column considers an earlier rise in the Bitcoin price to investigate what is driving the currency’s price spikes. The two thousand thirteen rise was caused by fraudulent trades taking place at the largest Bitcoin currency exchange at the time. This finding has implications for policymakers as they weigh what, if anything, to do about regulating cryptocurrencies in light of the record high Bitcoin valuation that many fear is a bubble.

Related

The digital currency Bitcoin was introduced in 2009. Bitcoin and the many other digital currencies are primarily online currencies. The key currencies are those based primarily on cryptography, and Bitcoin is the leading ‘cryptocurrency’.

Bitcoin has experienced a meteoric rise in popularity since its introduction. While digital currencies were proposed as early as the 1980s, Bitcoin was the very first to catch on. The total value of all Bitcoins in circulation reached $45 billion in June 2017. Its success has inspired scores of contesting cryptocurrencies that go after a similar design. Bitcoin and most other cryptocurrencies do not require a central authority to validate and lodge transactions. Instead, these currencies use cryptography (and an internal incentive system) to control transactions, manage the supply, and prevent fraud. Payments are validated by a decentralised network. Once confirmed, all transactions are stored digitally and recorded in a public ‘blockchain’,’ which can be thought of as a distributed accounting system.

While Bitcoin’s algorithm provides safeguards against ‘counterfeiting’ of the currency, the eco-system is still vulnerable to theft. Users keep keys to their Bitcoins and make transactions with the help of wallets. Exchanges facilitate trade inbetween Bitcoins and fiat currencies, and also permit for storing Bitcoins. Bitcoins can be stolen through wallets or exchanges. Exchanges have been targeted more frequently than wallets because many wallets are located on users’ (local) computers, while exchanges frequently store customer deposits in their own (much larger) wallets.

The supply of most cryptocurrencies increases at a predetermined rate, and cannot be switched by any central authority. There are about fifteen million Bitcoins presently in circulation, with the ultimate number eventually reaching twenty one million. The immobile supply in the long run creates concerns about the deflationary aspect of the currency.

While Bitcoin shows excellent promise to disrupt existing payment systems through innovations in its technical design, the Bitcoin ecosystem one has been the frequent target of attacks by financially motivated criminals. Due to the unregulated, decentralised environment in which they operate, cryptocurrencies are under constant threat of attack.

Bitcoin only recently became a subject of research in economics. However, the topic has been of interest for longer in computer science (for early work by computer scientists on incentives, see Babaioff et al. 2012, and Eyal and Sirer 2014.) Numerous researchers have conducted studies in order to document and combat threats such as Ponzi schemes, money laundering, mining botnets, and the theft of cryptocurrency wallets (Moeser et al. 2013, Vasek and Moore 2015, Vasek et al. 2016, Yuxing et al. 2014). Ron and Shamir (2013) attempt to identify suspicious trading activity by building a graph of Bitcoin transactions found in the public ledger. None of these papers can associate individual transactions with specific users of the currency exchanges.

In latest work, we demonstrate that the very first time Bitcoin reached an exchange rate of more than $1,000, the meteoric rise was driven by fraud (Gandal et al. 2017). We leverage a unique and very detailed dataset to examine suspicious trading activity that occurred over a ten-month period in two thousand thirteen on Mt. Gox, the leading Bitcoin currency exchange at the time. We very first quantify the extent of the suspicious/fraudulent trading activity and showcase that it constitutes a large fraction of trading on the days the activity occurred. We then demonstrate how this trading activity affected the exchange rates at Mt. Gox and other leading currency exchanges.

Figure 1 Bitcoin–US dollar exchange rate, with periods of suspicious activity shaded

While it was the superior currency exchange when Bitcoin very first shot to prominence in early 2013, behind the scenes, Tokyo-based Mt. Gox was in trouble. In addition to suffering from repeated denial-of-service attacks and Bitcoin thefts, two unauthorised traders were able to transact on the exchange without spending real money. In the very first case, a trader dubbed ‘Markus’ was credited with Bitcoins by duplicating previously ended transactions. In the 2nd case, a trader dubbed ‘Willy’ bought Bitcoins from traders by ‘crediting’ the sellers’ accounts with fiat currencies that, in many cases, could not be withdrawn. Figure one shows when these fraudulent traders were active, along with the Bitcoin–US dollar exchange rate. Most noteworthy is that Willy’s operation coincided with an unprecedented hop in the price of Bitcoin: from around $150 to over $1000. In early 2014, Mt. Gox collapsed, and the Bitcoin price fell with it. Only recently, in early 2017, has Bitcoin surpassed the levels of the earlier rise.

However, how do we know that the rise was caused by the fraudulent trades? Fortunately for us as researchers, the unauthorised trades did not take place every day. Table one shows the daily switch in the Bitcoin–US dollar exchange rate for various time periods on Mt. Gox. In the two quarters before unauthorised trading commenced, the daily price increase was, on average, positive but relatively puny: a $0.21 increase in the very first period and a $1 increase in the 2nd period. During the third quarter, when unauthorised trading embarked, the price rose by an average of $Three.15 on the seventeen days in which Markus traded, but fell on average by $0.51 on the seventy five days he did not trade. However, it is during the final quarter, when Willy began trading, that the difference became stark. On the fifty days in which Willy traded, the Bitcoin price rose by an average of $21.85. On the forty one days in which Willy did not make unauthorizsed purchases, the price fell by $0.88 on average. (Table one is very similar for the other leading exchanges as well.)

Table 1 Average daily switch in BTC/USD exchange rate as a function of fraudulent activity Two

In our total paper, we conduct a regression analysis to examine whether other factors such as the relatively numerous and varied attacks on the Mt. Gox exchange could explain the switch in the daily Bitcoin price, both at Mt. Gox and other leading exchanges (Gandal et al. 2017).

The analysis confirms that only Willy’s trading presence affected the price. The estimated coefficient (on the dummy variable for whether Willy was active) is virtually the same ($21.65) as in Table 1. We conclude that the suspicious trading activity of a single actor was the primary cause of the massive spike in the Bitcoin–US dollar exchange rate, in which the rate rose from around $150 to over $1,000 in just two months in late 2013. The fall was almost as precipitous: the Mt. Gox exchange folded due to insolvency in early 2014, and it has taken more than three years for Bitcoin to match the rise triggered by fraudulent transactions.

Why should we care about the Bitcoin manipulation that took place in 2013? After all, the Bitcoin ecosystem is not almost as significant as the Fresh York Stock Exchange. Nonetheless, latest trends indicate that Bitcoin is becoming an significant asset in the financial system.

Trading in cryptocurrency assets has exploded recently. In the case of Bitcoin, during the one year period ending in mid-June 2017, the market capitalisation enhanced massively from around $7 billion to $45 billion; that is an increase of over 500% in one year. The market cap of other cryptocurrencies surged by even more. In the one-year period ending in mid-May 2017, the market value of cryptocurrencies excluding Bitcoin surged from $1.7 billion to more than $29 billion; that is an increase of more than 1,900%. The markets for these other cryptocurrencies are very lean and subject to manipulation. Given that we now know the Bitcoin price has been artificially inflated by unauthorised trades in the past, we must view the present rise with superb caution, and not necessarily consider it a ‘healthy bubble’, as recently claimed in The Economist (2017).

As mainstream finance invests in cryptocurrency assets and as countries take steps toward legalising Bitcoin as a payment system (as Japan did in April 2017), it is significant to understand how susceptible cryptocurrency markets are to manipulation. We encourage the nascent cryptocurrency industry to work with regulators and researchers to share anonymised transaction data so that more confidence can be placed in the veracity of exchange rates.

References

Babaioff, M, S Dobzinski, S Oren and A Zohar (2012), “On bitcoin and crimson balloons” in Proceedings of the 13th ACM Conference on Electronic Commerce, pp. 56-73.

Eyal, I and E Sirer (2014), “Majority is not Enough: Bitcoin Mining is Vulnerable”, paper introduced at the Eighteenth International Conference on Financial Cryptography and Data Security, Barbados, 3-7 March.

Gandal, N, J Hamrick, T Moore and T Oberman (2017), “Price Manipulation in the Bitcoin Ecosystem,” CEPR Discussion Paper No. 12061.

Mooser, M, R Bohme and D Breuker (2013), “An inquiry into money laundering devices in the Bitcoin ecosystem”, in Proceedings of the Seventh APWG eCrime Re-searcher’s Summit, pp. 1-14.

Ron, D and A Shamir (2013), “Quantitative analysis of the total Bitcoin transaction graph”, in Financial Cryptography and Data Security, Vol. Seven thousand eight hundred fifty nine of Lecture Notes in Computer Science, pp. 6-24.

Vasek, M and T Moore (2015), “There’s no free lunch, even using Bitcoin: Tracking the popularity and profits of virtual currency scams”, in R Bohme and T Okamoto (eds), Financial Cryptography and Data Security, volume eight thousand nine hundred seventy five of Lecture Notes in Computer Science, pp. 44-61.

Vasek, M, J Bonneau, R Castellucci, C Keith and T Moore (2016), “The Bitcoin brain drain: a brief paper on the use and manhandle of bitcoin brain wallets”, in Financial Cryptography and Data Security, Lecture Notes in Computer Science.

Yuxing Huang, D, H Dharmdasani, S Meiklejohn, V Dave, C Grier, D McCoy, S Savage, N Weaver, A Snoeren and K Levchenko (2014), “Botcoin: Monetizing stolen cycles”, in Proceedings of the Network and Distributed System Security Symposium.

Endnotes

[1] The Bitcoin ecosystem includes the core network for propagating transactions, the blockchain, and many intermediaries such as currency exchanges, mining pools, and payment processors that facilitate trade.

[Two] Markus was primarily active in period Three, but he was also active a few days during periods 1,Two, and Four. He was not active on the same days as Willy, who was only active in period Four.

Price manipulation in the Bitcoin ecosystem, VOX, CEPR’s Policy Portal

VOX CEPR’s Policy Portal

Research-based policy analysis and commentary from leading economists

Price manipulation in the Bitcoin ecosystem

Neil Gandal, JT Hamrick, Tyler Moore, Tali Oberman twenty two June two thousand seventeen

The cryptocurrency Bitcoin has attracted widespread interest, in large part due to wild swings in its valuation. This column considers an earlier rise in the Bitcoin price to investigate what is driving the currency’s price spikes. The two thousand thirteen rise was caused by fraudulent trades taking place at the largest Bitcoin currency exchange at the time. This finding has implications for policymakers as they weigh what, if anything, to do about regulating cryptocurrencies in light of the record high Bitcoin valuation that many fear is a bubble.

Related

The digital currency Bitcoin was introduced in 2009. Bitcoin and the many other digital currencies are primarily online currencies. The key currencies are those based primarily on cryptography, and Bitcoin is the leading ‘cryptocurrency’.

Bitcoin has experienced a meteoric rise in popularity since its introduction. While digital currencies were proposed as early as the 1980s, Bitcoin was the very first to catch on. The total value of all Bitcoins in circulation reached $45 billion in June 2017. Its success has inspired scores of contesting cryptocurrencies that go after a similar design. Bitcoin and most other cryptocurrencies do not require a central authority to validate and lodge transactions. Instead, these currencies use cryptography (and an internal incentive system) to control transactions, manage the supply, and prevent fraud. Payments are validated by a decentralised network. Once confirmed, all transactions are stored digitally and recorded in a public ‘blockchain’,’ which can be thought of as a distributed accounting system.

While Bitcoin’s algorithm provides safeguards against ‘counterfeiting’ of the currency, the eco-system is still vulnerable to theft. Users keep keys to their Bitcoins and make transactions with the help of wallets. Exchanges facilitate trade inbetween Bitcoins and fiat currencies, and also permit for storing Bitcoins. Bitcoins can be stolen through wallets or exchanges. Exchanges have been targeted more frequently than wallets because many wallets are located on users’ (local) computers, while exchanges frequently store customer deposits in their own (much larger) wallets.

The supply of most cryptocurrencies increases at a predetermined rate, and cannot be switched by any central authority. There are about fifteen million Bitcoins presently in circulation, with the ultimate number eventually reaching twenty one million. The motionless supply in the long run creates concerns about the deflationary aspect of the currency.

While Bitcoin shows good promise to disrupt existing payment systems through innovations in its technical design, the Bitcoin ecosystem one has been the frequent target of attacks by financially motivated criminals. Due to the unregulated, decentralised environment in which they operate, cryptocurrencies are under constant threat of attack.

Bitcoin only recently became a subject of research in economics. However, the topic has been of interest for longer in computer science (for early work by computer scientists on incentives, see Babaioff et al. 2012, and Eyal and Sirer 2014.) Numerous researchers have conducted studies in order to document and combat threats such as Ponzi schemes, money laundering, mining botnets, and the theft of cryptocurrency wallets (Moeser et al. 2013, Vasek and Moore 2015, Vasek et al. 2016, Yuxing et al. 2014). Ron and Shamir (2013) attempt to identify suspicious trading activity by building a graph of Bitcoin transactions found in the public ledger. None of these papers can associate individual transactions with specific users of the currency exchanges.

In latest work, we showcase that the very first time Bitcoin reached an exchange rate of more than $1,000, the meteoric rise was driven by fraud (Gandal et al. 2017). We leverage a unique and very detailed dataset to examine suspicious trading activity that occurred over a ten-month period in two thousand thirteen on Mt. Gox, the leading Bitcoin currency exchange at the time. We very first quantify the extent of the suspicious/fraudulent trading activity and showcase that it constitutes a large fraction of trading on the days the activity occurred. We then demonstrate how this trading activity affected the exchange rates at Mt. Gox and other leading currency exchanges.

Figure 1 Bitcoin–US dollar exchange rate, with periods of suspicious activity shaded

While it was the superior currency exchange when Bitcoin very first shot to prominence in early 2013, behind the scenes, Tokyo-based Mt. Gox was in trouble. In addition to suffering from repeated denial-of-service attacks and Bitcoin thefts, two unauthorised traders were able to transact on the exchange without spending real money. In the very first case, a trader dubbed ‘Markus’ was credited with Bitcoins by duplicating previously finished transactions. In the 2nd case, a trader dubbed ‘Willy’ bought Bitcoins from traders by ‘crediting’ the sellers’ accounts with fiat currencies that, in many cases, could not be withdrawn. Figure one shows when these fraudulent traders were active, along with the Bitcoin–US dollar exchange rate. Most noteworthy is that Willy’s operation coincided with an unprecedented hop in the price of Bitcoin: from around $150 to over $1000. In early 2014, Mt. Gox collapsed, and the Bitcoin price fell with it. Only recently, in early 2017, has Bitcoin surpassed the levels of the earlier rise.

However, how do we know that the rise was caused by the fraudulent trades? Fortunately for us as researchers, the unauthorised trades did not take place every day. Table one shows the daily switch in the Bitcoin–US dollar exchange rate for various time periods on Mt. Gox. In the two quarters before unauthorised trading commenced, the daily price increase was, on average, positive but relatively petite: a $0.21 increase in the very first period and a $1 increase in the 2nd period. During the third quarter, when unauthorised trading began, the price rose by an average of $Three.15 on the seventeen days in which Markus traded, but fell on average by $0.51 on the seventy five days he did not trade. However, it is during the final quarter, when Willy began trading, that the difference became stark. On the fifty days in which Willy traded, the Bitcoin price rose by an average of $21.85. On the forty one days in which Willy did not make unauthorizsed purchases, the price fell by $0.88 on average. (Table one is very similar for the other leading exchanges as well.)

Table 1 Average daily switch in BTC/USD exchange rate as a function of fraudulent activity Two

In our utter paper, we conduct a regression analysis to examine whether other factors such as the relatively numerous and varied attacks on the Mt. Gox exchange could explain the switch in the daily Bitcoin price, both at Mt. Gox and other leading exchanges (Gandal et al. 2017).

The analysis confirms that only Willy’s trading presence affected the price. The estimated coefficient (on the dummy variable for whether Willy was active) is virtually the same ($21.65) as in Table 1. We conclude that the suspicious trading activity of a single actor was the primary cause of the massive spike in the Bitcoin–US dollar exchange rate, in which the rate rose from around $150 to over $1,000 in just two months in late 2013. The fall was almost as precipitous: the Mt. Gox exchange folded due to insolvency in early 2014, and it has taken more than three years for Bitcoin to match the rise triggered by fraudulent transactions.

Why should we care about the Bitcoin manipulation that took place in 2013? After all, the Bitcoin ecosystem is not almost as significant as the Fresh York Stock Exchange. Nonetheless, latest trends indicate that Bitcoin is becoming an significant asset in the financial system.

Trading in cryptocurrency assets has exploded recently. In the case of Bitcoin, during the one year period ending in mid-June 2017, the market capitalisation enhanced massively from around $7 billion to $45 billion; that is an increase of over 500% in one year. The market cap of other cryptocurrencies surged by even more. In the one-year period ending in mid-May 2017, the market value of cryptocurrencies excluding Bitcoin surged from $1.7 billion to more than $29 billion; that is an increase of more than 1,900%. The markets for these other cryptocurrencies are very lean and subject to manipulation. Given that we now know the Bitcoin price has been artificially inflated by unauthorised trades in the past, we must view the present rise with excellent caution, and not necessarily consider it a ‘healthy bubble’, as recently claimed in The Economist (2017).

As mainstream finance invests in cryptocurrency assets and as countries take steps toward legalising Bitcoin as a payment system (as Japan did in April 2017), it is significant to understand how susceptible cryptocurrency markets are to manipulation. We encourage the nascent cryptocurrency industry to work with regulators and researchers to share anonymised transaction data so that more confidence can be placed in the veracity of exchange rates.

References

Babaioff, M, S Dobzinski, S Oren and A Zohar (2012), “On bitcoin and crimson balloons” in Proceedings of the 13th ACM Conference on Electronic Commerce, pp. 56-73.

Eyal, I and E Sirer (2014), “Majority is not Enough: Bitcoin Mining is Vulnerable”, paper introduced at the Eighteenth International Conference on Financial Cryptography and Data Security, Barbados, 3-7 March.

Gandal, N, J Hamrick, T Moore and T Oberman (2017), “Price Manipulation in the Bitcoin Ecosystem,” CEPR Discussion Paper No. 12061.

Mooser, M, R Bohme and D Breuker (2013), “An inquiry into money laundering implements in the Bitcoin ecosystem”, in Proceedings of the Seventh APWG eCrime Re-searcher’s Summit, pp. 1-14.

Ron, D and A Shamir (2013), “Quantitative analysis of the utter Bitcoin transaction graph”, in Financial Cryptography and Data Security, Vol. Seven thousand eight hundred fifty nine of Lecture Notes in Computer Science, pp. 6-24.

Vasek, M and T Moore (2015), “There’s no free lunch, even using Bitcoin: Tracking the popularity and profits of virtual currency scams”, in R Bohme and T Okamoto (eds), Financial Cryptography and Data Security, volume eight thousand nine hundred seventy five of Lecture Notes in Computer Science, pp. 44-61.

Vasek, M, J Bonneau, R Castellucci, C Keith and T Moore (2016), “The Bitcoin brain drain: a brief paper on the use and manhandle of bitcoin brain wallets”, in Financial Cryptography and Data Security, Lecture Notes in Computer Science.

Yuxing Huang, D, H Dharmdasani, S Meiklejohn, V Dave, C Grier, D McCoy, S Savage, N Weaver, A Snoeren and K Levchenko (2014), “Botcoin: Monetizing stolen cycles”, in Proceedings of the Network and Distributed System Security Symposium.

Endnotes

[1] The Bitcoin ecosystem includes the core network for propagating transactions, the blockchain, and many intermediaries such as currency exchanges, mining pools, and payment processors that facilitate trade.

[Two] Markus was primarily active in period Trio, but he was also active a few days during periods 1,Two, and Four. He was not active on the same days as Willy, who was only active in period Four.

Price manipulation in the Bitcoin ecosystem, VOX, CEPR’s Policy Portal

VOX CEPR’s Policy Portal

Research-based policy analysis and commentary from leading economists

Price manipulation in the Bitcoin ecosystem

Neil Gandal, JT Hamrick, Tyler Moore, Tali Oberman twenty two June two thousand seventeen

The cryptocurrency Bitcoin has attracted widespread interest, in large part due to wild swings in its valuation. This column considers an earlier rise in the Bitcoin price to investigate what is driving the currency’s price spikes. The two thousand thirteen rise was caused by fraudulent trades taking place at the largest Bitcoin currency exchange at the time. This finding has implications for policymakers as they weigh what, if anything, to do about regulating cryptocurrencies in light of the record high Bitcoin valuation that many fear is a bubble.

Related

The digital currency Bitcoin was introduced in 2009. Bitcoin and the many other digital currencies are primarily online currencies. The key currencies are those based primarily on cryptography, and Bitcoin is the leading ‘cryptocurrency’.

Bitcoin has experienced a meteoric rise in popularity since its introduction. While digital currencies were proposed as early as the 1980s, Bitcoin was the very first to catch on. The total value of all Bitcoins in circulation reached $45 billion in June 2017. Its success has inspired scores of rivaling cryptocurrencies that go after a similar design. Bitcoin and most other cryptocurrencies do not require a central authority to validate and lodge transactions. Instead, these currencies use cryptography (and an internal incentive system) to control transactions, manage the supply, and prevent fraud. Payments are validated by a decentralised network. Once confirmed, all transactions are stored digitally and recorded in a public ‘blockchain’,’ which can be thought of as a distributed accounting system.

While Bitcoin’s algorithm provides safeguards against ‘counterfeiting’ of the currency, the eco-system is still vulnerable to theft. Users keep keys to their Bitcoins and make transactions with the help of wallets. Exchanges facilitate trade inbetween Bitcoins and fiat currencies, and also permit for storing Bitcoins. Bitcoins can be stolen through wallets or exchanges. Exchanges have been targeted more frequently than wallets because many wallets are located on users’ (local) computers, while exchanges frequently store customer deposits in their own (much larger) wallets.

The supply of most cryptocurrencies increases at a predetermined rate, and cannot be switched by any central authority. There are about fifteen million Bitcoins presently in circulation, with the ultimate number eventually reaching twenty one million. The immobilized supply in the long run creates concerns about the deflationary aspect of the currency.

While Bitcoin shows fine promise to disrupt existing payment systems through innovations in its technical design, the Bitcoin ecosystem one has been the frequent target of attacks by financially motivated criminals. Due to the unregulated, decentralised environment in which they operate, cryptocurrencies are under constant threat of attack.

Bitcoin only recently became a subject of research in economics. However, the topic has been of interest for longer in computer science (for early work by computer scientists on incentives, see Babaioff et al. 2012, and Eyal and Sirer 2014.) Numerous researchers have conducted studies in order to document and combat threats such as Ponzi schemes, money laundering, mining botnets, and the theft of cryptocurrency wallets (Moeser et al. 2013, Vasek and Moore 2015, Vasek et al. 2016, Yuxing et al. 2014). Ron and Shamir (2013) attempt to identify suspicious trading activity by building a graph of Bitcoin transactions found in the public ledger. None of these papers can associate individual transactions with specific users of the currency exchanges.

In latest work, we showcase that the very first time Bitcoin reached an exchange rate of more than $1,000, the meteoric rise was driven by fraud (Gandal et al. 2017). We leverage a unique and very detailed dataset to examine suspicious trading activity that occurred over a ten-month period in two thousand thirteen on Mt. Gox, the leading Bitcoin currency exchange at the time. We very first quantify the extent of the suspicious/fraudulent trading activity and showcase that it constitutes a large fraction of trading on the days the activity occurred. We then display how this trading activity affected the exchange rates at Mt. Gox and other leading currency exchanges.

Figure 1 Bitcoin–US dollar exchange rate, with periods of suspicious activity shaded

While it was the superior currency exchange when Bitcoin very first shot to prominence in early 2013, behind the scenes, Tokyo-based Mt. Gox was in trouble. In addition to suffering from repeated denial-of-service attacks and Bitcoin thefts, two unauthorised traders were able to transact on the exchange without spending real money. In the very first case, a trader dubbed ‘Markus’ was credited with Bitcoins by duplicating previously ended transactions. In the 2nd case, a trader dubbed ‘Willy’ bought Bitcoins from traders by ‘crediting’ the sellers’ accounts with fiat currencies that, in many cases, could not be withdrawn. Figure one shows when these fraudulent traders were active, along with the Bitcoin–US dollar exchange rate. Most noteworthy is that Willy’s operation coincided with an unprecedented leap in the price of Bitcoin: from around $150 to over $1000. In early 2014, Mt. Gox collapsed, and the Bitcoin price fell with it. Only recently, in early 2017, has Bitcoin surpassed the levels of the earlier rise.

However, how do we know that the rise was caused by the fraudulent trades? Fortunately for us as researchers, the unauthorised trades did not take place every day. Table one shows the daily switch in the Bitcoin–US dollar exchange rate for various time periods on Mt. Gox. In the two quarters before unauthorised trading commenced, the daily price increase was, on average, positive but relatively puny: a $0.21 increase in the very first period and a $1 increase in the 2nd period. During the third quarter, when unauthorised trading embarked, the price rose by an average of $Trio.15 on the seventeen days in which Markus traded, but fell on average by $0.51 on the seventy five days he did not trade. However, it is during the final quarter, when Willy began trading, that the difference became stark. On the fifty days in which Willy traded, the Bitcoin price rose by an average of $21.85. On the forty one days in which Willy did not make unauthorizsed purchases, the price fell by $0.88 on average. (Table one is very similar for the other leading exchanges as well.)

Table 1 Average daily switch in BTC/USD exchange rate as a function of fraudulent activity Two

In our total paper, we conduct a regression analysis to examine whether other factors such as the relatively numerous and varied attacks on the Mt. Gox exchange could explain the switch in the daily Bitcoin price, both at Mt. Gox and other leading exchanges (Gandal et al. 2017).

The analysis confirms that only Willy’s trading presence affected the price. The estimated coefficient (on the dummy variable for whether Willy was active) is virtually the same ($21.65) as in Table 1. We conclude that the suspicious trading activity of a single actor was the primary cause of the massive spike in the Bitcoin–US dollar exchange rate, in which the rate rose from around $150 to over $1,000 in just two months in late 2013. The fall was almost as precipitous: the Mt. Gox exchange folded due to insolvency in early 2014, and it has taken more than three years for Bitcoin to match the rise triggered by fraudulent transactions.

Why should we care about the Bitcoin manipulation that took place in 2013? After all, the Bitcoin ecosystem is not almost as significant as the Fresh York Stock Exchange. Nonetheless, latest trends indicate that Bitcoin is becoming an significant asset in the financial system.

Trading in cryptocurrency assets has exploded recently. In the case of Bitcoin, during the one year period ending in mid-June 2017, the market capitalisation enlargened massively from around $7 billion to $45 billion; that is an increase of over 500% in one year. The market cap of other cryptocurrencies surged by even more. In the one-year period ending in mid-May 2017, the market value of cryptocurrencies excluding Bitcoin surged from $1.7 billion to more than $29 billion; that is an increase of more than 1,900%. The markets for these other cryptocurrencies are very lean and subject to manipulation. Given that we now know the Bitcoin price has been artificially inflated by unauthorised trades in the past, we must view the present rise with good caution, and not necessarily consider it a ‘healthy bubble’, as recently claimed in The Economist (2017).

As mainstream finance invests in cryptocurrency assets and as countries take steps toward legalising Bitcoin as a payment system (as Japan did in April 2017), it is significant to understand how susceptible cryptocurrency markets are to manipulation. We encourage the nascent cryptocurrency industry to work with regulators and researchers to share anonymised transaction data so that more confidence can be placed in the veracity of exchange rates.

References

Babaioff, M, S Dobzinski, S Oren and A Zohar (2012), “On bitcoin and crimson balloons” in Proceedings of the 13th ACM Conference on Electronic Commerce, pp. 56-73.

Eyal, I and E Sirer (2014), “Majority is not Enough: Bitcoin Mining is Vulnerable”, paper introduced at the Eighteenth International Conference on Financial Cryptography and Data Security, Barbados, 3-7 March.

Gandal, N, J Hamrick, T Moore and T Oberman (2017), “Price Manipulation in the Bitcoin Ecosystem,” CEPR Discussion Paper No. 12061.

Mooser, M, R Bohme and D Breuker (2013), “An inquiry into money laundering devices in the Bitcoin ecosystem”, in Proceedings of the Seventh APWG eCrime Re-searcher’s Summit, pp. 1-14.

Ron, D and A Shamir (2013), “Quantitative analysis of the total Bitcoin transaction graph”, in Financial Cryptography and Data Security, Vol. Seven thousand eight hundred fifty nine of Lecture Notes in Computer Science, pp. 6-24.

Vasek, M and T Moore (2015), “There’s no free lunch, even using Bitcoin: Tracking the popularity and profits of virtual currency scams”, in R Bohme and T Okamoto (eds), Financial Cryptography and Data Security, volume eight thousand nine hundred seventy five of Lecture Notes in Computer Science, pp. 44-61.

Vasek, M, J Bonneau, R Castellucci, C Keith and T Moore (2016), “The Bitcoin brain drain: a brief paper on the use and manhandle of bitcoin brain wallets”, in Financial Cryptography and Data Security, Lecture Notes in Computer Science.

Yuxing Huang, D, H Dharmdasani, S Meiklejohn, V Dave, C Grier, D McCoy, S Savage, N Weaver, A Snoeren and K Levchenko (2014), “Botcoin: Monetizing stolen cycles”, in Proceedings of the Network and Distributed System Security Symposium.

Endnotes

[1] The Bitcoin ecosystem includes the core network for propagating transactions, the blockchain, and many intermediaries such as currency exchanges, mining pools, and payment processors that facilitate trade.

[Two] Markus was primarily active in period Three, but he was also active a few days during periods 1,Two, and Four. He was not active on the same days as Willy, who was only active in period Four.

Price manipulation in the Bitcoin ecosystem, VOX, CEPR’s Policy Portal

VOX CEPR’s Policy Portal

Research-based policy analysis and commentary from leading economists

Price manipulation in the Bitcoin ecosystem

Neil Gandal, JT Hamrick, Tyler Moore, Tali Oberman twenty two June two thousand seventeen

The cryptocurrency Bitcoin has attracted widespread interest, in large part due to wild swings in its valuation. This column considers an earlier rise in the Bitcoin price to investigate what is driving the currency’s price spikes. The two thousand thirteen rise was caused by fraudulent trades taking place at the largest Bitcoin currency exchange at the time. This finding has implications for policymakers as they weigh what, if anything, to do about regulating cryptocurrencies in light of the record high Bitcoin valuation that many fear is a bubble.

Related

The digital currency Bitcoin was introduced in 2009. Bitcoin and the many other digital currencies are primarily online currencies. The key currencies are those based primarily on cryptography, and Bitcoin is the leading ‘cryptocurrency’.

Bitcoin has experienced a meteoric rise in popularity since its introduction. While digital currencies were proposed as early as the 1980s, Bitcoin was the very first to catch on. The total value of all Bitcoins in circulation reached $45 billion in June 2017. Its success has inspired scores of challenging cryptocurrencies that go after a similar design. Bitcoin and most other cryptocurrencies do not require a central authority to validate and lodge transactions. Instead, these currencies use cryptography (and an internal incentive system) to control transactions, manage the supply, and prevent fraud. Payments are validated by a decentralised network. Once confirmed, all transactions are stored digitally and recorded in a public ‘blockchain’,’ which can be thought of as a distributed accounting system.

While Bitcoin’s algorithm provides safeguards against ‘counterfeiting’ of the currency, the eco-system is still vulnerable to theft. Users keep keys to their Bitcoins and make transactions with the help of wallets. Exchanges facilitate trade inbetween Bitcoins and fiat currencies, and also permit for storing Bitcoins. Bitcoins can be stolen through wallets or exchanges. Exchanges have been targeted more frequently than wallets because many wallets are located on users’ (local) computers, while exchanges frequently store customer deposits in their own (much larger) wallets.

The supply of most cryptocurrencies increases at a predetermined rate, and cannot be switched by any central authority. There are about fifteen million Bitcoins presently in circulation, with the ultimate number eventually reaching twenty one million. The immobile supply in the long run creates concerns about the deflationary aspect of the currency.

While Bitcoin shows good promise to disrupt existing payment systems through innovations in its technical design, the Bitcoin ecosystem one has been the frequent target of attacks by financially motivated criminals. Due to the unregulated, decentralised environment in which they operate, cryptocurrencies are under constant threat of attack.

Bitcoin only recently became a subject of research in economics. However, the topic has been of interest for longer in computer science (for early work by computer scientists on incentives, see Babaioff et al. 2012, and Eyal and Sirer 2014.) Numerous researchers have conducted studies in order to document and combat threats such as Ponzi schemes, money laundering, mining botnets, and the theft of cryptocurrency wallets (Moeser et al. 2013, Vasek and Moore 2015, Vasek et al. 2016, Yuxing et al. 2014). Ron and Shamir (2013) attempt to identify suspicious trading activity by building a graph of Bitcoin transactions found in the public ledger. None of these papers can associate individual transactions with specific users of the currency exchanges.

In latest work, we demonstrate that the very first time Bitcoin reached an exchange rate of more than $1,000, the meteoric rise was driven by fraud (Gandal et al. 2017). We leverage a unique and very detailed dataset to examine suspicious trading activity that occurred over a ten-month period in two thousand thirteen on Mt. Gox, the leading Bitcoin currency exchange at the time. We very first quantify the extent of the suspicious/fraudulent trading activity and display that it constitutes a large fraction of trading on the days the activity occurred. We then demonstrate how this trading activity affected the exchange rates at Mt. Gox and other leading currency exchanges.

Figure 1 Bitcoin–US dollar exchange rate, with periods of suspicious activity shaded

While it was the superior currency exchange when Bitcoin very first shot to prominence in early 2013, behind the scenes, Tokyo-based Mt. Gox was in trouble. In addition to suffering from repeated denial-of-service attacks and Bitcoin thefts, two unauthorised traders were able to transact on the exchange without spending real money. In the very first case, a trader dubbed ‘Markus’ was credited with Bitcoins by duplicating previously finished transactions. In the 2nd case, a trader dubbed ‘Willy’ bought Bitcoins from traders by ‘crediting’ the sellers’ accounts with fiat currencies that, in many cases, could not be withdrawn. Figure one shows when these fraudulent traders were active, along with the Bitcoin–US dollar exchange rate. Most noteworthy is that Willy’s operation coincided with an unprecedented hop in the price of Bitcoin: from around $150 to over $1000. In early 2014, Mt. Gox collapsed, and the Bitcoin price fell with it. Only recently, in early 2017, has Bitcoin surpassed the levels of the earlier rise.

However, how do we know that the rise was caused by the fraudulent trades? Fortunately for us as researchers, the unauthorised trades did not take place every day. Table one shows the daily switch in the Bitcoin–US dollar exchange rate for various time periods on Mt. Gox. In the two quarters before unauthorised trading commenced, the daily price increase was, on average, positive but relatively puny: a $0.21 increase in the very first period and a $1 increase in the 2nd period. During the third quarter, when unauthorised trading embarked, the price rose by an average of $Trio.15 on the seventeen days in which Markus traded, but fell on average by $0.51 on the seventy five days he did not trade. However, it is during the final quarter, when Willy began trading, that the difference became stark. On the fifty days in which Willy traded, the Bitcoin price rose by an average of $21.85. On the forty one days in which Willy did not make unauthorizsed purchases, the price fell by $0.88 on average. (Table one is very similar for the other leading exchanges as well.)

Table 1 Average daily switch in BTC/USD exchange rate as a function of fraudulent activity Two

In our utter paper, we conduct a regression analysis to examine whether other factors such as the relatively numerous and varied attacks on the Mt. Gox exchange could explain the switch in the daily Bitcoin price, both at Mt. Gox and other leading exchanges (Gandal et al. 2017).

The analysis confirms that only Willy’s trading presence affected the price. The estimated coefficient (on the dummy variable for whether Willy was active) is virtually the same ($21.65) as in Table 1. We conclude that the suspicious trading activity of a single actor was the primary cause of the massive spike in the Bitcoin–US dollar exchange rate, in which the rate rose from around $150 to over $1,000 in just two months in late 2013. The fall was almost as precipitous: the Mt. Gox exchange folded due to insolvency in early 2014, and it has taken more than three years for Bitcoin to match the rise triggered by fraudulent transactions.

Why should we care about the Bitcoin manipulation that took place in 2013? After all, the Bitcoin ecosystem is not almost as significant as the Fresh York Stock Exchange. Nonetheless, latest trends indicate that Bitcoin is becoming an significant asset in the financial system.

Trading in cryptocurrency assets has exploded recently. In the case of Bitcoin, during the one year period ending in mid-June 2017, the market capitalisation enhanced massively from around $7 billion to $45 billion; that is an increase of over 500% in one year. The market cap of other cryptocurrencies surged by even more. In the one-year period ending in mid-May 2017, the market value of cryptocurrencies excluding Bitcoin surged from $1.7 billion to more than $29 billion; that is an increase of more than 1,900%. The markets for these other cryptocurrencies are very lean and subject to manipulation. Given that we now know the Bitcoin price has been artificially inflated by unauthorised trades in the past, we must view the present rise with good caution, and not necessarily consider it a ‘healthy bubble’, as recently claimed in The Economist (2017).

As mainstream finance invests in cryptocurrency assets and as countries take steps toward legalising Bitcoin as a payment system (as Japan did in April 2017), it is significant to understand how susceptible cryptocurrency markets are to manipulation. We encourage the nascent cryptocurrency industry to work with regulators and researchers to share anonymised transaction data so that more confidence can be placed in the veracity of exchange rates.

References

Babaioff, M, S Dobzinski, S Oren and A Zohar (2012), “On bitcoin and crimson balloons” in Proceedings of the 13th ACM Conference on Electronic Commerce, pp. 56-73.

Eyal, I and E Sirer (2014), “Majority is not Enough: Bitcoin Mining is Vulnerable”, paper introduced at the Eighteenth International Conference on Financial Cryptography and Data Security, Barbados, 3-7 March.

Gandal, N, J Hamrick, T Moore and T Oberman (2017), “Price Manipulation in the Bitcoin Ecosystem,” CEPR Discussion Paper No. 12061.

Mooser, M, R Bohme and D Breuker (2013), “An inquiry into money laundering instruments in the Bitcoin ecosystem”, in Proceedings of the Seventh APWG eCrime Re-searcher’s Summit, pp. 1-14.

Ron, D and A Shamir (2013), “Quantitative analysis of the total Bitcoin transaction graph”, in Financial Cryptography and Data Security, Vol. Seven thousand eight hundred fifty nine of Lecture Notes in Computer Science, pp. 6-24.

Vasek, M and T Moore (2015), “There’s no free lunch, even using Bitcoin: Tracking the popularity and profits of virtual currency scams”, in R Bohme and T Okamoto (eds), Financial Cryptography and Data Security, volume eight thousand nine hundred seventy five of Lecture Notes in Computer Science, pp. 44-61.

Vasek, M, J Bonneau, R Castellucci, C Keith and T Moore (2016), “The Bitcoin brain drain: a brief paper on the use and manhandle of bitcoin brain wallets”, in Financial Cryptography and Data Security, Lecture Notes in Computer Science.

Yuxing Huang, D, H Dharmdasani, S Meiklejohn, V Dave, C Grier, D McCoy, S Savage, N Weaver, A Snoeren and K Levchenko (2014), “Botcoin: Monetizing stolen cycles”, in Proceedings of the Network and Distributed System Security Symposium.

Endnotes

[1] The Bitcoin ecosystem includes the core network for propagating transactions, the blockchain, and many intermediaries such as currency exchanges, mining pools, and payment processors that facilitate trade.

[Two] Markus was primarily active in period Trio, but he was also active a few days during periods 1,Two, and Four. He was not active on the same days as Willy, who was only active in period Four.

Price manipulation in the Bitcoin ecosystem, VOX, CEPR’s Policy Portal

VOX CEPR’s Policy Portal

Research-based policy analysis and commentary from leading economists

Price manipulation in the Bitcoin ecosystem

Neil Gandal, JT Hamrick, Tyler Moore, Tali Oberman twenty two June two thousand seventeen

The cryptocurrency Bitcoin has attracted widespread interest, in large part due to wild swings in its valuation. This column considers an earlier rise in the Bitcoin price to investigate what is driving the currency’s price spikes. The two thousand thirteen rise was caused by fraudulent trades taking place at the largest Bitcoin currency exchange at the time. This finding has implications for policymakers as they weigh what, if anything, to do about regulating cryptocurrencies in light of the record high Bitcoin valuation that many fear is a bubble.

Related

The digital currency Bitcoin was introduced in 2009. Bitcoin and the many other digital currencies are primarily online currencies. The key currencies are those based primarily on cryptography, and Bitcoin is the leading ‘cryptocurrency’.

Bitcoin has experienced a meteoric rise in popularity since its introduction. While digital currencies were proposed as early as the 1980s, Bitcoin was the very first to catch on. The total value of all Bitcoins in circulation reached $45 billion in June 2017. Its success has inspired scores of challenging cryptocurrencies that go after a similar design. Bitcoin and most other cryptocurrencies do not require a central authority to validate and lodge transactions. Instead, these currencies use cryptography (and an internal incentive system) to control transactions, manage the supply, and prevent fraud. Payments are validated by a decentralised network. Once confirmed, all transactions are stored digitally and recorded in a public ‘blockchain’,’ which can be thought of as a distributed accounting system.

While Bitcoin’s algorithm provides safeguards against ‘counterfeiting’ of the currency, the eco-system is still vulnerable to theft. Users keep keys to their Bitcoins and make transactions with the help of wallets. Exchanges facilitate trade inbetween Bitcoins and fiat currencies, and also permit for storing Bitcoins. Bitcoins can be stolen through wallets or exchanges. Exchanges have been targeted more frequently than wallets because many wallets are located on users’ (local) computers, while exchanges frequently store customer deposits in their own (much larger) wallets.

The supply of most cryptocurrencies increases at a predetermined rate, and cannot be switched by any central authority. There are about fifteen million Bitcoins presently in circulation, with the ultimate number eventually reaching twenty one million. The immobile supply in the long run creates concerns about the deflationary aspect of the currency.

While Bitcoin shows superb promise to disrupt existing payment systems through innovations in its technical design, the Bitcoin ecosystem one has been the frequent target of attacks by financially motivated criminals. Due to the unregulated, decentralised environment in which they operate, cryptocurrencies are under constant threat of attack.

Bitcoin only recently became a subject of research in economics. However, the topic has been of interest for longer in computer science (for early work by computer scientists on incentives, see Babaioff et al. 2012, and Eyal and Sirer 2014.) Numerous researchers have conducted studies in order to document and combat threats such as Ponzi schemes, money laundering, mining botnets, and the theft of cryptocurrency wallets (Moeser et al. 2013, Vasek and Moore 2015, Vasek et al. 2016, Yuxing et al. 2014). Ron and Shamir (2013) attempt to identify suspicious trading activity by building a graph of Bitcoin transactions found in the public ledger. None of these papers can associate individual transactions with specific users of the currency exchanges.

In latest work, we demonstrate that the very first time Bitcoin reached an exchange rate of more than $1,000, the meteoric rise was driven by fraud (Gandal et al. 2017). We leverage a unique and very detailed dataset to examine suspicious trading activity that occurred over a ten-month period in two thousand thirteen on Mt. Gox, the leading Bitcoin currency exchange at the time. We very first quantify the extent of the suspicious/fraudulent trading activity and showcase that it constitutes a large fraction of trading on the days the activity occurred. We then demonstrate how this trading activity affected the exchange rates at Mt. Gox and other leading currency exchanges.

Figure 1 Bitcoin–US dollar exchange rate, with periods of suspicious activity shaded

While it was the superior currency exchange when Bitcoin very first shot to prominence in early 2013, behind the scenes, Tokyo-based Mt. Gox was in trouble. In addition to suffering from repeated denial-of-service attacks and Bitcoin thefts, two unauthorised traders were able to transact on the exchange without spending real money. In the very first case, a trader dubbed ‘Markus’ was credited with Bitcoins by duplicating previously finished transactions. In the 2nd case, a trader dubbed ‘Willy’ bought Bitcoins from traders by ‘crediting’ the sellers’ accounts with fiat currencies that, in many cases, could not be withdrawn. Figure one shows when these fraudulent traders were active, along with the Bitcoin–US dollar exchange rate. Most noteworthy is that Willy’s operation coincided with an unprecedented hop in the price of Bitcoin: from around $150 to over $1000. In early 2014, Mt. Gox collapsed, and the Bitcoin price fell with it. Only recently, in early 2017, has Bitcoin surpassed the levels of the earlier rise.

However, how do we know that the rise was caused by the fraudulent trades? Fortunately for us as researchers, the unauthorised trades did not take place every day. Table one shows the daily switch in the Bitcoin–US dollar exchange rate for various time periods on Mt. Gox. In the two quarters before unauthorised trading commenced, the daily price increase was, on average, positive but relatively puny: a $0.21 increase in the very first period and a $1 increase in the 2nd period. During the third quarter, when unauthorised trading began, the price rose by an average of $Three.15 on the seventeen days in which Markus traded, but fell on average by $0.51 on the seventy five days he did not trade. However, it is during the final quarter, when Willy began trading, that the difference became stark. On the fifty days in which Willy traded, the Bitcoin price rose by an average of $21.85. On the forty one days in which Willy did not make unauthorizsed purchases, the price fell by $0.88 on average. (Table one is very similar for the other leading exchanges as well.)

Table 1 Average daily switch in BTC/USD exchange rate as a function of fraudulent activity Two

In our utter paper, we conduct a regression analysis to examine whether other factors such as the relatively numerous and varied attacks on the Mt. Gox exchange could explain the switch in the daily Bitcoin price, both at Mt. Gox and other leading exchanges (Gandal et al. 2017).

The analysis confirms that only Willy’s trading presence affected the price. The estimated coefficient (on the dummy variable for whether Willy was active) is virtually the same ($21.65) as in Table 1. We conclude that the suspicious trading activity of a single actor was the primary cause of the massive spike in the Bitcoin–US dollar exchange rate, in which the rate rose from around $150 to over $1,000 in just two months in late 2013. The fall was almost as precipitous: the Mt. Gox exchange folded due to insolvency in early 2014, and it has taken more than three years for Bitcoin to match the rise triggered by fraudulent transactions.

Why should we care about the Bitcoin manipulation that took place in 2013? After all, the Bitcoin ecosystem is not almost as significant as the Fresh York Stock Exchange. Nonetheless, latest trends indicate that Bitcoin is becoming an significant asset in the financial system.

Trading in cryptocurrency assets has exploded recently. In the case of Bitcoin, during the one year period ending in mid-June 2017, the market capitalisation enlargened massively from around $7 billion to $45 billion; that is an increase of over 500% in one year. The market cap of other cryptocurrencies surged by even more. In the one-year period ending in mid-May 2017, the market value of cryptocurrencies excluding Bitcoin surged from $1.7 billion to more than $29 billion; that is an increase of more than 1,900%. The markets for these other cryptocurrencies are very lean and subject to manipulation. Given that we now know the Bitcoin price has been artificially inflated by unauthorised trades in the past, we must view the present rise with good caution, and not necessarily consider it a ‘healthy bubble’, as recently claimed in The Economist (2017).

As mainstream finance invests in cryptocurrency assets and as countries take steps toward legalising Bitcoin as a payment system (as Japan did in April 2017), it is significant to understand how susceptible cryptocurrency markets are to manipulation. We encourage the nascent cryptocurrency industry to work with regulators and researchers to share anonymised transaction data so that more confidence can be placed in the veracity of exchange rates.

References

Babaioff, M, S Dobzinski, S Oren and A Zohar (2012), “On bitcoin and crimson balloons” in Proceedings of the 13th ACM Conference on Electronic Commerce, pp. 56-73.

Eyal, I and E Sirer (2014), “Majority is not Enough: Bitcoin Mining is Vulnerable”, paper introduced at the Eighteenth International Conference on Financial Cryptography and Data Security, Barbados, 3-7 March.

Gandal, N, J Hamrick, T Moore and T Oberman (2017), “Price Manipulation in the Bitcoin Ecosystem,” CEPR Discussion Paper No. 12061.

Mooser, M, R Bohme and D Breuker (2013), “An inquiry into money laundering instruments in the Bitcoin ecosystem”, in Proceedings of the Seventh APWG eCrime Re-searcher’s Summit, pp. 1-14.

Ron, D and A Shamir (2013), “Quantitative analysis of the total Bitcoin transaction graph”, in Financial Cryptography and Data Security, Vol. Seven thousand eight hundred fifty nine of Lecture Notes in Computer Science, pp. 6-24.

Vasek, M and T Moore (2015), “There’s no free lunch, even using Bitcoin: Tracking the popularity and profits of virtual currency scams”, in R Bohme and T Okamoto (eds), Financial Cryptography and Data Security, volume eight thousand nine hundred seventy five of Lecture Notes in Computer Science, pp. 44-61.

Vasek, M, J Bonneau, R Castellucci, C Keith and T Moore (2016), “The Bitcoin brain drain: a brief paper on the use and manhandle of bitcoin brain wallets”, in Financial Cryptography and Data Security, Lecture Notes in Computer Science.

Yuxing Huang, D, H Dharmdasani, S Meiklejohn, V Dave, C Grier, D McCoy, S Savage, N Weaver, A Snoeren and K Levchenko (2014), “Botcoin: Monetizing stolen cycles”, in Proceedings of the Network and Distributed System Security Symposium.

Endnotes

[1] The Bitcoin ecosystem includes the core network for propagating transactions, the blockchain, and many intermediaries such as currency exchanges, mining pools, and payment processors that facilitate trade.

[Two] Markus was primarily active in period Trio, but he was also active a few days during periods 1,Two, and Four. He was not active on the same days as Willy, who was only active in period Four.

Price manipulation in the Bitcoin ecosystem, VOX, CEPR’s Policy Portal

VOX CEPR’s Policy Portal

Research-based policy analysis and commentary from leading economists

Price manipulation in the Bitcoin ecosystem

Neil Gandal, JT Hamrick, Tyler Moore, Tali Oberman twenty two June two thousand seventeen

The cryptocurrency Bitcoin has attracted widespread interest, in large part due to wild swings in its valuation. This column considers an earlier rise in the Bitcoin price to investigate what is driving the currency’s price spikes. The two thousand thirteen rise was caused by fraudulent trades taking place at the largest Bitcoin currency exchange at the time. This finding has implications for policymakers as they weigh what, if anything, to do about regulating cryptocurrencies in light of the record high Bitcoin valuation that many fear is a bubble.

Related

The digital currency Bitcoin was introduced in 2009. Bitcoin and the many other digital currencies are primarily online currencies. The key currencies are those based primarily on cryptography, and Bitcoin is the leading ‘cryptocurrency’.

Bitcoin has experienced a meteoric rise in popularity since its introduction. While digital currencies were proposed as early as the 1980s, Bitcoin was the very first to catch on. The total value of all Bitcoins in circulation reached $45 billion in June 2017. Its success has inspired scores of challenging cryptocurrencies that go after a similar design. Bitcoin and most other cryptocurrencies do not require a central authority to validate and lodge transactions. Instead, these currencies use cryptography (and an internal incentive system) to control transactions, manage the supply, and prevent fraud. Payments are validated by a decentralised network. Once confirmed, all transactions are stored digitally and recorded in a public ‘blockchain’,’ which can be thought of as a distributed accounting system.

While Bitcoin’s algorithm provides safeguards against ‘counterfeiting’ of the currency, the eco-system is still vulnerable to theft. Users keep keys to their Bitcoins and make transactions with the help of wallets. Exchanges facilitate trade inbetween Bitcoins and fiat currencies, and also permit for storing Bitcoins. Bitcoins can be stolen through wallets or exchanges. Exchanges have been targeted more frequently than wallets because many wallets are located on users’ (local) computers, while exchanges frequently store customer deposits in their own (much larger) wallets.

The supply of most cryptocurrencies increases at a predetermined rate, and cannot be switched by any central authority. There are about fifteen million Bitcoins presently in circulation, with the ultimate number eventually reaching twenty one million. The immobile supply in the long run creates concerns about the deflationary aspect of the currency.

While Bitcoin shows superb promise to disrupt existing payment systems through innovations in its technical design, the Bitcoin ecosystem one has been the frequent target of attacks by financially motivated criminals. Due to the unregulated, decentralised environment in which they operate, cryptocurrencies are under constant threat of attack.

Bitcoin only recently became a subject of research in economics. However, the topic has been of interest for longer in computer science (for early work by computer scientists on incentives, see Babaioff et al. 2012, and Eyal and Sirer 2014.) Numerous researchers have conducted studies in order to document and combat threats such as Ponzi schemes, money laundering, mining botnets, and the theft of cryptocurrency wallets (Moeser et al. 2013, Vasek and Moore 2015, Vasek et al. 2016, Yuxing et al. 2014). Ron and Shamir (2013) attempt to identify suspicious trading activity by building a graph of Bitcoin transactions found in the public ledger. None of these papers can associate individual transactions with specific users of the currency exchanges.

In latest work, we demonstrate that the very first time Bitcoin reached an exchange rate of more than $1,000, the meteoric rise was driven by fraud (Gandal et al. 2017). We leverage a unique and very detailed dataset to examine suspicious trading activity that occurred over a ten-month period in two thousand thirteen on Mt. Gox, the leading Bitcoin currency exchange at the time. We very first quantify the extent of the suspicious/fraudulent trading activity and display that it constitutes a large fraction of trading on the days the activity occurred. We then demonstrate how this trading activity affected the exchange rates at Mt. Gox and other leading currency exchanges.

Figure 1 Bitcoin–US dollar exchange rate, with periods of suspicious activity shaded

While it was the superior currency exchange when Bitcoin very first shot to prominence in early 2013, behind the scenes, Tokyo-based Mt. Gox was in trouble. In addition to suffering from repeated denial-of-service attacks and Bitcoin thefts, two unauthorised traders were able to transact on the exchange without spending real money. In the very first case, a trader dubbed ‘Markus’ was credited with Bitcoins by duplicating previously ended transactions. In the 2nd case, a trader dubbed ‘Willy’ bought Bitcoins from traders by ‘crediting’ the sellers’ accounts with fiat currencies that, in many cases, could not be withdrawn. Figure one shows when these fraudulent traders were active, along with the Bitcoin–US dollar exchange rate. Most noteworthy is that Willy’s operation coincided with an unprecedented hop in the price of Bitcoin: from around $150 to over $1000. In early 2014, Mt. Gox collapsed, and the Bitcoin price fell with it. Only recently, in early 2017, has Bitcoin surpassed the levels of the earlier rise.

However, how do we know that the rise was caused by the fraudulent trades? Fortunately for us as researchers, the unauthorised trades did not take place every day. Table one shows the daily switch in the Bitcoin–US dollar exchange rate for various time periods on Mt. Gox. In the two quarters before unauthorised trading commenced, the daily price increase was, on average, positive but relatively puny: a $0.21 increase in the very first period and a $1 increase in the 2nd period. During the third quarter, when unauthorised trading began, the price rose by an average of $Three.15 on the seventeen days in which Markus traded, but fell on average by $0.51 on the seventy five days he did not trade. However, it is during the final quarter, when Willy began trading, that the difference became stark. On the fifty days in which Willy traded, the Bitcoin price rose by an average of $21.85. On the forty one days in which Willy did not make unauthorizsed purchases, the price fell by $0.88 on average. (Table one is very similar for the other leading exchanges as well.)

Table 1 Average daily switch in BTC/USD exchange rate as a function of fraudulent activity Two

In our total paper, we conduct a regression analysis to examine whether other factors such as the relatively numerous and varied attacks on the Mt. Gox exchange could explain the switch in the daily Bitcoin price, both at Mt. Gox and other leading exchanges (Gandal et al. 2017).

The analysis confirms that only Willy’s trading presence affected the price. The estimated coefficient (on the dummy variable for whether Willy was active) is virtually the same ($21.65) as in Table 1. We conclude that the suspicious trading activity of a single actor was the primary cause of the massive spike in the Bitcoin–US dollar exchange rate, in which the rate rose from around $150 to over $1,000 in just two months in late 2013. The fall was almost as precipitous: the Mt. Gox exchange folded due to insolvency in early 2014, and it has taken more than three years for Bitcoin to match the rise triggered by fraudulent transactions.

Why should we care about the Bitcoin manipulation that took place in 2013? After all, the Bitcoin ecosystem is not almost as significant as the Fresh York Stock Exchange. Nonetheless, latest trends indicate that Bitcoin is becoming an significant asset in the financial system.

Trading in cryptocurrency assets has exploded recently. In the case of Bitcoin, during the one year period ending in mid-June 2017, the market capitalisation enlargened massively from around $7 billion to $45 billion; that is an increase of over 500% in one year. The market cap of other cryptocurrencies surged by even more. In the one-year period ending in mid-May 2017, the market value of cryptocurrencies excluding Bitcoin surged from $1.7 billion to more than $29 billion; that is an increase of more than 1,900%. The markets for these other cryptocurrencies are very lean and subject to manipulation. Given that we now know the Bitcoin price has been artificially inflated by unauthorised trades in the past, we must view the present rise with good caution, and not necessarily consider it a ‘healthy bubble’, as recently claimed in The Economist (2017).

As mainstream finance invests in cryptocurrency assets and as countries take steps toward legalising Bitcoin as a payment system (as Japan did in April 2017), it is significant to understand how susceptible cryptocurrency markets are to manipulation. We encourage the nascent cryptocurrency industry to work with regulators and researchers to share anonymised transaction data so that more confidence can be placed in the veracity of exchange rates.

References

Babaioff, M, S Dobzinski, S Oren and A Zohar (2012), “On bitcoin and crimson balloons” in Proceedings of the 13th ACM Conference on Electronic Commerce, pp. 56-73.

Eyal, I and E Sirer (2014), “Majority is not Enough: Bitcoin Mining is Vulnerable”, paper introduced at the Eighteenth International Conference on Financial Cryptography and Data Security, Barbados, 3-7 March.

Gandal, N, J Hamrick, T Moore and T Oberman (2017), “Price Manipulation in the Bitcoin Ecosystem,” CEPR Discussion Paper No. 12061.

Mooser, M, R Bohme and D Breuker (2013), “An inquiry into money laundering instruments in the Bitcoin ecosystem”, in Proceedings of the Seventh APWG eCrime Re-searcher’s Summit, pp. 1-14.

Ron, D and A Shamir (2013), “Quantitative analysis of the utter Bitcoin transaction graph”, in Financial Cryptography and Data Security, Vol. Seven thousand eight hundred fifty nine of Lecture Notes in Computer Science, pp. 6-24.

Vasek, M and T Moore (2015), “There’s no free lunch, even using Bitcoin: Tracking the popularity and profits of virtual currency scams”, in R Bohme and T Okamoto (eds), Financial Cryptography and Data Security, volume eight thousand nine hundred seventy five of Lecture Notes in Computer Science, pp. 44-61.

Vasek, M, J Bonneau, R Castellucci, C Keith and T Moore (2016), “The Bitcoin brain drain: a brief paper on the use and manhandle of bitcoin brain wallets”, in Financial Cryptography and Data Security, Lecture Notes in Computer Science.

Yuxing Huang, D, H Dharmdasani, S Meiklejohn, V Dave, C Grier, D McCoy, S Savage, N Weaver, A Snoeren and K Levchenko (2014), “Botcoin: Monetizing stolen cycles”, in Proceedings of the Network and Distributed System Security Symposium.

Endnotes

[1] The Bitcoin ecosystem includes the core network for propagating transactions, the blockchain, and many intermediaries such as currency exchanges, mining pools, and payment processors that facilitate trade.

[Two] Markus was primarily active in period Trio, but he was also active a few days during periods 1,Two, and Four. He was not active on the same days as Willy, who was only active in period Four.

Price manipulation in the Bitcoin ecosystem, VOX, CEPR’s Policy Portal

VOX CEPR’s Policy Portal

Research-based policy analysis and commentary from leading economists

Price manipulation in the Bitcoin ecosystem

Neil Gandal, JT Hamrick, Tyler Moore, Tali Oberman twenty two June two thousand seventeen

The cryptocurrency Bitcoin has attracted widespread interest, in large part due to wild swings in its valuation. This column considers an earlier rise in the Bitcoin price to investigate what is driving the currency’s price spikes. The two thousand thirteen rise was caused by fraudulent trades taking place at the largest Bitcoin currency exchange at the time. This finding has implications for policymakers as they weigh what, if anything, to do about regulating cryptocurrencies in light of the record high Bitcoin valuation that many fear is a bubble.

Related

The digital currency Bitcoin was introduced in 2009. Bitcoin and the many other digital currencies are primarily online currencies. The key currencies are those based primarily on cryptography, and Bitcoin is the leading ‘cryptocurrency’.

Bitcoin has experienced a meteoric rise in popularity since its introduction. While digital currencies were proposed as early as the 1980s, Bitcoin was the very first to catch on. The total value of all Bitcoins in circulation reached $45 billion in June 2017. Its success has inspired scores of challenging cryptocurrencies that go after a similar design. Bitcoin and most other cryptocurrencies do not require a central authority to validate and lodge transactions. Instead, these currencies use cryptography (and an internal incentive system) to control transactions, manage the supply, and prevent fraud. Payments are validated by a decentralised network. Once confirmed, all transactions are stored digitally and recorded in a public ‘blockchain’,’ which can be thought of as a distributed accounting system.

While Bitcoin’s algorithm provides safeguards against ‘counterfeiting’ of the currency, the eco-system is still vulnerable to theft. Users keep keys to their Bitcoins and make transactions with the help of wallets. Exchanges facilitate trade inbetween Bitcoins and fiat currencies, and also permit for storing Bitcoins. Bitcoins can be stolen through wallets or exchanges. Exchanges have been targeted more frequently than wallets because many wallets are located on users’ (local) computers, while exchanges frequently store customer deposits in their own (much larger) wallets.

The supply of most cryptocurrencies increases at a predetermined rate, and cannot be switched by any central authority. There are about fifteen million Bitcoins presently in circulation, with the ultimate number eventually reaching twenty one million. The motionless supply in the long run creates concerns about the deflationary aspect of the currency.

While Bitcoin shows fine promise to disrupt existing payment systems through innovations in its technical design, the Bitcoin ecosystem one has been the frequent target of attacks by financially motivated criminals. Due to the unregulated, decentralised environment in which they operate, cryptocurrencies are under constant threat of attack.

Bitcoin only recently became a subject of research in economics. However, the topic has been of interest for longer in computer science (for early work by computer scientists on incentives, see Babaioff et al. 2012, and Eyal and Sirer 2014.) Numerous researchers have conducted studies in order to document and combat threats such as Ponzi schemes, money laundering, mining botnets, and the theft of cryptocurrency wallets (Moeser et al. 2013, Vasek and Moore 2015, Vasek et al. 2016, Yuxing et al. 2014). Ron and Shamir (2013) attempt to identify suspicious trading activity by building a graph of Bitcoin transactions found in the public ledger. None of these papers can associate individual transactions with specific users of the currency exchanges.

In latest work, we showcase that the very first time Bitcoin reached an exchange rate of more than $1,000, the meteoric rise was driven by fraud (Gandal et al. 2017). We leverage a unique and very detailed dataset to examine suspicious trading activity that occurred over a ten-month period in two thousand thirteen on Mt. Gox, the leading Bitcoin currency exchange at the time. We very first quantify the extent of the suspicious/fraudulent trading activity and showcase that it constitutes a large fraction of trading on the days the activity occurred. We then display how this trading activity affected the exchange rates at Mt. Gox and other leading currency exchanges.

Figure 1 Bitcoin–US dollar exchange rate, with periods of suspicious activity shaded

While it was the superior currency exchange when Bitcoin very first shot to prominence in early 2013, behind the scenes, Tokyo-based Mt. Gox was in trouble. In addition to suffering from repeated denial-of-service attacks and Bitcoin thefts, two unauthorised traders were able to transact on the exchange without spending real money. In the very first case, a trader dubbed ‘Markus’ was credited with Bitcoins by duplicating previously ended transactions. In the 2nd case, a trader dubbed ‘Willy’ bought Bitcoins from traders by ‘crediting’ the sellers’ accounts with fiat currencies that, in many cases, could not be withdrawn. Figure one shows when these fraudulent traders were active, along with the Bitcoin–US dollar exchange rate. Most noteworthy is that Willy’s operation coincided with an unprecedented hop in the price of Bitcoin: from around $150 to over $1000. In early 2014, Mt. Gox collapsed, and the Bitcoin price fell with it. Only recently, in early 2017, has Bitcoin surpassed the levels of the earlier rise.

However, how do we know that the rise was caused by the fraudulent trades? Fortunately for us as researchers, the unauthorised trades did not take place every day. Table one shows the daily switch in the Bitcoin–US dollar exchange rate for various time periods on Mt. Gox. In the two quarters before unauthorised trading commenced, the daily price increase was, on average, positive but relatively puny: a $0.21 increase in the very first period and a $1 increase in the 2nd period. During the third quarter, when unauthorised trading commenced, the price rose by an average of $Three.15 on the seventeen days in which Markus traded, but fell on average by $0.51 on the seventy five days he did not trade. However, it is during the final quarter, when Willy began trading, that the difference became stark. On the fifty days in which Willy traded, the Bitcoin price rose by an average of $21.85. On the forty one days in which Willy did not make unauthorizsed purchases, the price fell by $0.88 on average. (Table one is very similar for the other leading exchanges as well.)

Table 1 Average daily switch in BTC/USD exchange rate as a function of fraudulent activity Two

In our total paper, we conduct a regression analysis to examine whether other factors such as the relatively numerous and varied attacks on the Mt. Gox exchange could explain the switch in the daily Bitcoin price, both at Mt. Gox and other leading exchanges (Gandal et al. 2017).

The analysis confirms that only Willy’s trading presence affected the price. The estimated coefficient (on the dummy variable for whether Willy was active) is virtually the same ($21.65) as in Table 1. We conclude that the suspicious trading activity of a single actor was the primary cause of the massive spike in the Bitcoin–US dollar exchange rate, in which the rate rose from around $150 to over $1,000 in just two months in late 2013. The fall was almost as precipitous: the Mt. Gox exchange folded due to insolvency in early 2014, and it has taken more than three years for Bitcoin to match the rise triggered by fraudulent transactions.

Why should we care about the Bitcoin manipulation that took place in 2013? After all, the Bitcoin ecosystem is not almost as significant as the Fresh York Stock Exchange. Nonetheless, latest trends indicate that Bitcoin is becoming an significant asset in the financial system.

Trading in cryptocurrency assets has exploded recently. In the case of Bitcoin, during the one year period ending in mid-June 2017, the market capitalisation enlargened massively from around $7 billion to $45 billion; that is an increase of over 500% in one year. The market cap of other cryptocurrencies surged by even more. In the one-year period ending in mid-May 2017, the market value of cryptocurrencies excluding Bitcoin surged from $1.7 billion to more than $29 billion; that is an increase of more than 1,900%. The markets for these other cryptocurrencies are very skinny and subject to manipulation. Given that we now know the Bitcoin price has been artificially inflated by unauthorised trades in the past, we must view the present rise with superb caution, and not necessarily consider it a ‘healthy bubble’, as recently claimed in The Economist (2017).

As mainstream finance invests in cryptocurrency assets and as countries take steps toward legalising Bitcoin as a payment system (as Japan did in April 2017), it is significant to understand how susceptible cryptocurrency markets are to manipulation. We encourage the nascent cryptocurrency industry to work with regulators and researchers to share anonymised transaction data so that more confidence can be placed in the veracity of exchange rates.

References

Babaioff, M, S Dobzinski, S Oren and A Zohar (2012), “On bitcoin and crimson balloons” in Proceedings of the 13th ACM Conference on Electronic Commerce, pp. 56-73.

Eyal, I and E Sirer (2014), “Majority is not Enough: Bitcoin Mining is Vulnerable”, paper introduced at the Eighteenth International Conference on Financial Cryptography and Data Security, Barbados, 3-7 March.

Gandal, N, J Hamrick, T Moore and T Oberman (2017), “Price Manipulation in the Bitcoin Ecosystem,” CEPR Discussion Paper No. 12061.

Mooser, M, R Bohme and D Breuker (2013), “An inquiry into money laundering implements in the Bitcoin ecosystem”, in Proceedings of the Seventh APWG eCrime Re-searcher’s Summit, pp. 1-14.

Ron, D and A Shamir (2013), “Quantitative analysis of the total Bitcoin transaction graph”, in Financial Cryptography and Data Security, Vol. Seven thousand eight hundred fifty nine of Lecture Notes in Computer Science, pp. 6-24.

Vasek, M and T Moore (2015), “There’s no free lunch, even using Bitcoin: Tracking the popularity and profits of virtual currency scams”, in R Bohme and T Okamoto (eds), Financial Cryptography and Data Security, volume eight thousand nine hundred seventy five of Lecture Notes in Computer Science, pp. 44-61.

Vasek, M, J Bonneau, R Castellucci, C Keith and T Moore (2016), “The Bitcoin brain drain: a brief paper on the use and manhandle of bitcoin brain wallets”, in Financial Cryptography and Data Security, Lecture Notes in Computer Science.

Yuxing Huang, D, H Dharmdasani, S Meiklejohn, V Dave, C Grier, D McCoy, S Savage, N Weaver, A Snoeren and K Levchenko (2014), “Botcoin: Monetizing stolen cycles”, in Proceedings of the Network and Distributed System Security Symposium.

Endnotes

[1] The Bitcoin ecosystem includes the core network for propagating transactions, the blockchain, and many intermediaries such as currency exchanges, mining pools, and payment processors that facilitate trade.

[Two] Markus was primarily active in period Trio, but he was also active a few days during periods 1,Two, and Four. He was not active on the same days as Willy, who was only active in period Four.

Price manipulation in the Bitcoin ecosystem, VOX, CEPR’s Policy Portal

VOX CEPR’s Policy Portal

Research-based policy analysis and commentary from leading economists

Price manipulation in the Bitcoin ecosystem

Neil Gandal, JT Hamrick, Tyler Moore, Tali Oberman twenty two June two thousand seventeen

The cryptocurrency Bitcoin has attracted widespread interest, in large part due to wild swings in its valuation. This column considers an earlier rise in the Bitcoin price to investigate what is driving the currency’s price spikes. The two thousand thirteen rise was caused by fraudulent trades taking place at the largest Bitcoin currency exchange at the time. This finding has implications for policymakers as they weigh what, if anything, to do about regulating cryptocurrencies in light of the record high Bitcoin valuation that many fear is a bubble.

Related

The digital currency Bitcoin was introduced in 2009. Bitcoin and the many other digital currencies are primarily online currencies. The key currencies are those based primarily on cryptography, and Bitcoin is the leading ‘cryptocurrency’.

Bitcoin has experienced a meteoric rise in popularity since its introduction. While digital currencies were proposed as early as the 1980s, Bitcoin was the very first to catch on. The total value of all Bitcoins in circulation reached $45 billion in June 2017. Its success has inspired scores of rivaling cryptocurrencies that go after a similar design. Bitcoin and most other cryptocurrencies do not require a central authority to validate and lodge transactions. Instead, these currencies use cryptography (and an internal incentive system) to control transactions, manage the supply, and prevent fraud. Payments are validated by a decentralised network. Once confirmed, all transactions are stored digitally and recorded in a public ‘blockchain’,’ which can be thought of as a distributed accounting system.

While Bitcoin’s algorithm provides safeguards against ‘counterfeiting’ of the currency, the eco-system is still vulnerable to theft. Users keep keys to their Bitcoins and make transactions with the help of wallets. Exchanges facilitate trade inbetween Bitcoins and fiat currencies, and also permit for storing Bitcoins. Bitcoins can be stolen through wallets or exchanges. Exchanges have been targeted more frequently than wallets because many wallets are located on users’ (local) computers, while exchanges frequently store customer deposits in their own (much larger) wallets.

The supply of most cryptocurrencies increases at a predetermined rate, and cannot be switched by any central authority. There are about fifteen million Bitcoins presently in circulation, with the ultimate number eventually reaching twenty one million. The immobile supply in the long run creates concerns about the deflationary aspect of the currency.

While Bitcoin shows excellent promise to disrupt existing payment systems through innovations in its technical design, the Bitcoin ecosystem one has been the frequent target of attacks by financially motivated criminals. Due to the unregulated, decentralised environment in which they operate, cryptocurrencies are under constant threat of attack.

Bitcoin only recently became a subject of research in economics. However, the topic has been of interest for longer in computer science (for early work by computer scientists on incentives, see Babaioff et al. 2012, and Eyal and Sirer 2014.) Numerous researchers have conducted studies in order to document and combat threats such as Ponzi schemes, money laundering, mining botnets, and the theft of cryptocurrency wallets (Moeser et al. 2013, Vasek and Moore 2015, Vasek et al. 2016, Yuxing et al. 2014). Ron and Shamir (2013) attempt to identify suspicious trading activity by building a graph of Bitcoin transactions found in the public ledger. None of these papers can associate individual transactions with specific users of the currency exchanges.

In latest work, we showcase that the very first time Bitcoin reached an exchange rate of more than $1,000, the meteoric rise was driven by fraud (Gandal et al. 2017). We leverage a unique and very detailed dataset to examine suspicious trading activity that occurred over a ten-month period in two thousand thirteen on Mt. Gox, the leading Bitcoin currency exchange at the time. We very first quantify the extent of the suspicious/fraudulent trading activity and demonstrate that it constitutes a large fraction of trading on the days the activity occurred. We then showcase how this trading activity affected the exchange rates at Mt. Gox and other leading currency exchanges.

Figure 1 Bitcoin–US dollar exchange rate, with periods of suspicious activity shaded

While it was the superior currency exchange when Bitcoin very first shot to prominence in early 2013, behind the scenes, Tokyo-based Mt. Gox was in trouble. In addition to suffering from repeated denial-of-service attacks and Bitcoin thefts, two unauthorised traders were able to transact on the exchange without spending real money. In the very first case, a trader dubbed ‘Markus’ was credited with Bitcoins by duplicating previously finished transactions. In the 2nd case, a trader dubbed ‘Willy’ bought Bitcoins from traders by ‘crediting’ the sellers’ accounts with fiat currencies that, in many cases, could not be withdrawn. Figure one shows when these fraudulent traders were active, along with the Bitcoin–US dollar exchange rate. Most noteworthy is that Willy’s operation coincided with an unprecedented hop in the price of Bitcoin: from around $150 to over $1000. In early 2014, Mt. Gox collapsed, and the Bitcoin price fell with it. Only recently, in early 2017, has Bitcoin surpassed the levels of the earlier rise.

However, how do we know that the rise was caused by the fraudulent trades? Fortunately for us as researchers, the unauthorised trades did not take place every day. Table one shows the daily switch in the Bitcoin–US dollar exchange rate for various time periods on Mt. Gox. In the two quarters before unauthorised trading commenced, the daily price increase was, on average, positive but relatively petite: a $0.21 increase in the very first period and a $1 increase in the 2nd period. During the third quarter, when unauthorised trading began, the price rose by an average of $Three.15 on the seventeen days in which Markus traded, but fell on average by $0.51 on the seventy five days he did not trade. However, it is during the final quarter, when Willy began trading, that the difference became stark. On the fifty days in which Willy traded, the Bitcoin price rose by an average of $21.85. On the forty one days in which Willy did not make unauthorizsed purchases, the price fell by $0.88 on average. (Table one is very similar for the other leading exchanges as well.)

Table 1 Average daily switch in BTC/USD exchange rate as a function of fraudulent activity Two

In our total paper, we conduct a regression analysis to examine whether other factors such as the relatively numerous and varied attacks on the Mt. Gox exchange could explain the switch in the daily Bitcoin price, both at Mt. Gox and other leading exchanges (Gandal et al. 2017).

The analysis confirms that only Willy’s trading presence affected the price. The estimated coefficient (on the dummy variable for whether Willy was active) is virtually the same ($21.65) as in Table 1. We conclude that the suspicious trading activity of a single actor was the primary cause of the massive spike in the Bitcoin–US dollar exchange rate, in which the rate rose from around $150 to over $1,000 in just two months in late 2013. The fall was almost as precipitous: the Mt. Gox exchange folded due to insolvency in early 2014, and it has taken more than three years for Bitcoin to match the rise triggered by fraudulent transactions.

Why should we care about the Bitcoin manipulation that took place in 2013? After all, the Bitcoin ecosystem is not almost as significant as the Fresh York Stock Exchange. Nonetheless, latest trends indicate that Bitcoin is becoming an significant asset in the financial system.

Trading in cryptocurrency assets has exploded recently. In the case of Bitcoin, during the one year period ending in mid-June 2017, the market capitalisation enhanced massively from around $7 billion to $45 billion; that is an increase of over 500% in one year. The market cap of other cryptocurrencies surged by even more. In the one-year period ending in mid-May 2017, the market value of cryptocurrencies excluding Bitcoin surged from $1.7 billion to more than $29 billion; that is an increase of more than 1,900%. The markets for these other cryptocurrencies are very skinny and subject to manipulation. Given that we now know the Bitcoin price has been artificially inflated by unauthorised trades in the past, we must view the present rise with superb caution, and not necessarily consider it a ‘healthy bubble’, as recently claimed in The Economist (2017).

As mainstream finance invests in cryptocurrency assets and as countries take steps toward legalising Bitcoin as a payment system (as Japan did in April 2017), it is significant to understand how susceptible cryptocurrency markets are to manipulation. We encourage the nascent cryptocurrency industry to work with regulators and researchers to share anonymised transaction data so that more confidence can be placed in the veracity of exchange rates.

References

Babaioff, M, S Dobzinski, S Oren and A Zohar (2012), “On bitcoin and crimson balloons” in Proceedings of the 13th ACM Conference on Electronic Commerce, pp. 56-73.

Eyal, I and E Sirer (2014), “Majority is not Enough: Bitcoin Mining is Vulnerable”, paper introduced at the Eighteenth International Conference on Financial Cryptography and Data Security, Barbados, 3-7 March.

Gandal, N, J Hamrick, T Moore and T Oberman (2017), “Price Manipulation in the Bitcoin Ecosystem,” CEPR Discussion Paper No. 12061.

Mooser, M, R Bohme and D Breuker (2013), “An inquiry into money laundering implements in the Bitcoin ecosystem”, in Proceedings of the Seventh APWG eCrime Re-searcher’s Summit, pp. 1-14.

Ron, D and A Shamir (2013), “Quantitative analysis of the utter Bitcoin transaction graph”, in Financial Cryptography and Data Security, Vol. Seven thousand eight hundred fifty nine of Lecture Notes in Computer Science, pp. 6-24.

Vasek, M and T Moore (2015), “There’s no free lunch, even using Bitcoin: Tracking the popularity and profits of virtual currency scams”, in R Bohme and T Okamoto (eds), Financial Cryptography and Data Security, volume eight thousand nine hundred seventy five of Lecture Notes in Computer Science, pp. 44-61.

Vasek, M, J Bonneau, R Castellucci, C Keith and T Moore (2016), “The Bitcoin brain drain: a brief paper on the use and manhandle of bitcoin brain wallets”, in Financial Cryptography and Data Security, Lecture Notes in Computer Science.

Yuxing Huang, D, H Dharmdasani, S Meiklejohn, V Dave, C Grier, D McCoy, S Savage, N Weaver, A Snoeren and K Levchenko (2014), “Botcoin: Monetizing stolen cycles”, in Proceedings of the Network and Distributed System Security Symposium.

Endnotes

[1] The Bitcoin ecosystem includes the core network for propagating transactions, the blockchain, and many intermediaries such as currency exchanges, mining pools, and payment processors that facilitate trade.

[Two] Markus was primarily active in period Trio, but he was also active a few days during periods 1,Two, and Four. He was not active on the same days as Willy, who was only active in period Four.

Price manipulation in the Bitcoin ecosystem, VOX, CEPR’s Policy Portal

VOX CEPR’s Policy Portal

Research-based policy analysis and commentary from leading economists

Price manipulation in the Bitcoin ecosystem

Neil Gandal, JT Hamrick, Tyler Moore, Tali Oberman twenty two June two thousand seventeen

The cryptocurrency Bitcoin has attracted widespread interest, in large part due to wild swings in its valuation. This column considers an earlier rise in the Bitcoin price to investigate what is driving the currency’s price spikes. The two thousand thirteen rise was caused by fraudulent trades taking place at the largest Bitcoin currency exchange at the time. This finding has implications for policymakers as they weigh what, if anything, to do about regulating cryptocurrencies in light of the record high Bitcoin valuation that many fear is a bubble.

Related

The digital currency Bitcoin was introduced in 2009. Bitcoin and the many other digital currencies are primarily online currencies. The key currencies are those based primarily on cryptography, and Bitcoin is the leading ‘cryptocurrency’.

Bitcoin has experienced a meteoric rise in popularity since its introduction. While digital currencies were proposed as early as the 1980s, Bitcoin was the very first to catch on. The total value of all Bitcoins in circulation reached $45 billion in June 2017. Its success has inspired scores of rivaling cryptocurrencies that go after a similar design. Bitcoin and most other cryptocurrencies do not require a central authority to validate and lodge transactions. Instead, these currencies use cryptography (and an internal incentive system) to control transactions, manage the supply, and prevent fraud. Payments are validated by a decentralised network. Once confirmed, all transactions are stored digitally and recorded in a public ‘blockchain’,’ which can be thought of as a distributed accounting system.

While Bitcoin’s algorithm provides safeguards against ‘counterfeiting’ of the currency, the eco-system is still vulnerable to theft. Users keep keys to their Bitcoins and make transactions with the help of wallets. Exchanges facilitate trade inbetween Bitcoins and fiat currencies, and also permit for storing Bitcoins. Bitcoins can be stolen through wallets or exchanges. Exchanges have been targeted more frequently than wallets because many wallets are located on users’ (local) computers, while exchanges frequently store customer deposits in their own (much larger) wallets.

The supply of most cryptocurrencies increases at a predetermined rate, and cannot be switched by any central authority. There are about fifteen million Bitcoins presently in circulation, with the ultimate number eventually reaching twenty one million. The immovable supply in the long run creates concerns about the deflationary aspect of the currency.

While Bitcoin shows fine promise to disrupt existing payment systems through innovations in its technical design, the Bitcoin ecosystem one has been the frequent target of attacks by financially motivated criminals. Due to the unregulated, decentralised environment in which they operate, cryptocurrencies are under constant threat of attack.

Bitcoin only recently became a subject of research in economics. However, the topic has been of interest for longer in computer science (for early work by computer scientists on incentives, see Babaioff et al. 2012, and Eyal and Sirer 2014.) Numerous researchers have conducted studies in order to document and combat threats such as Ponzi schemes, money laundering, mining botnets, and the theft of cryptocurrency wallets (Moeser et al. 2013, Vasek and Moore 2015, Vasek et al. 2016, Yuxing et al. 2014). Ron and Shamir (2013) attempt to identify suspicious trading activity by building a graph of Bitcoin transactions found in the public ledger. None of these papers can associate individual transactions with specific users of the currency exchanges.

In latest work, we display that the very first time Bitcoin reached an exchange rate of more than $1,000, the meteoric rise was driven by fraud (Gandal et al. 2017). We leverage a unique and very detailed dataset to examine suspicious trading activity that occurred over a ten-month period in two thousand thirteen on Mt. Gox, the leading Bitcoin currency exchange at the time. We very first quantify the extent of the suspicious/fraudulent trading activity and showcase that it constitutes a large fraction of trading on the days the activity occurred. We then demonstrate how this trading activity affected the exchange rates at Mt. Gox and other leading currency exchanges.

Figure 1 Bitcoin–US dollar exchange rate, with periods of suspicious activity shaded

While it was the superior currency exchange when Bitcoin very first shot to prominence in early 2013, behind the scenes, Tokyo-based Mt. Gox was in trouble. In addition to suffering from repeated denial-of-service attacks and Bitcoin thefts, two unauthorised traders were able to transact on the exchange without spending real money. In the very first case, a trader dubbed ‘Markus’ was credited with Bitcoins by duplicating previously ended transactions. In the 2nd case, a trader dubbed ‘Willy’ bought Bitcoins from traders by ‘crediting’ the sellers’ accounts with fiat currencies that, in many cases, could not be withdrawn. Figure one shows when these fraudulent traders were active, along with the Bitcoin–US dollar exchange rate. Most noteworthy is that Willy’s operation coincided with an unprecedented leap in the price of Bitcoin: from around $150 to over $1000. In early 2014, Mt. Gox collapsed, and the Bitcoin price fell with it. Only recently, in early 2017, has Bitcoin surpassed the levels of the earlier rise.

However, how do we know that the rise was caused by the fraudulent trades? Fortunately for us as researchers, the unauthorised trades did not take place every day. Table one shows the daily switch in the Bitcoin–US dollar exchange rate for various time periods on Mt. Gox. In the two quarters before unauthorised trading commenced, the daily price increase was, on average, positive but relatively puny: a $0.21 increase in the very first period and a $1 increase in the 2nd period. During the third quarter, when unauthorised trading commenced, the price rose by an average of $Trio.15 on the seventeen days in which Markus traded, but fell on average by $0.51 on the seventy five days he did not trade. However, it is during the final quarter, when Willy began trading, that the difference became stark. On the fifty days in which Willy traded, the Bitcoin price rose by an average of $21.85. On the forty one days in which Willy did not make unauthorizsed purchases, the price fell by $0.88 on average. (Table one is very similar for the other leading exchanges as well.)

Table 1 Average daily switch in BTC/USD exchange rate as a function of fraudulent activity Two

In our utter paper, we conduct a regression analysis to examine whether other factors such as the relatively numerous and varied attacks on the Mt. Gox exchange could explain the switch in the daily Bitcoin price, both at Mt. Gox and other leading exchanges (Gandal et al. 2017).

The analysis confirms that only Willy’s trading presence affected the price. The estimated coefficient (on the dummy variable for whether Willy was active) is virtually the same ($21.65) as in Table 1. We conclude that the suspicious trading activity of a single actor was the primary cause of the massive spike in the Bitcoin–US dollar exchange rate, in which the rate rose from around $150 to over $1,000 in just two months in late 2013. The fall was almost as precipitous: the Mt. Gox exchange folded due to insolvency in early 2014, and it has taken more than three years for Bitcoin to match the rise triggered by fraudulent transactions.

Why should we care about the Bitcoin manipulation that took place in 2013? After all, the Bitcoin ecosystem is not almost as significant as the Fresh York Stock Exchange. Nonetheless, latest trends indicate that Bitcoin is becoming an significant asset in the financial system.

Trading in cryptocurrency assets has exploded recently. In the case of Bitcoin, during the one year period ending in mid-June 2017, the market capitalisation enlargened massively from around $7 billion to $45 billion; that is an increase of over 500% in one year. The market cap of other cryptocurrencies surged by even more. In the one-year period ending in mid-May 2017, the market value of cryptocurrencies excluding Bitcoin surged from $1.7 billion to more than $29 billion; that is an increase of more than 1,900%. The markets for these other cryptocurrencies are very skinny and subject to manipulation. Given that we now know the Bitcoin price has been artificially inflated by unauthorised trades in the past, we must view the present rise with superb caution, and not necessarily consider it a ‘healthy bubble’, as recently claimed in The Economist (2017).

As mainstream finance invests in cryptocurrency assets and as countries take steps toward legalising Bitcoin as a payment system (as Japan did in April 2017), it is significant to understand how susceptible cryptocurrency markets are to manipulation. We encourage the nascent cryptocurrency industry to work with regulators and researchers to share anonymised transaction data so that more confidence can be placed in the veracity of exchange rates.

References

Babaioff, M, S Dobzinski, S Oren and A Zohar (2012), “On bitcoin and crimson balloons” in Proceedings of the 13th ACM Conference on Electronic Commerce, pp. 56-73.

Eyal, I and E Sirer (2014), “Majority is not Enough: Bitcoin Mining is Vulnerable”, paper introduced at the Eighteenth International Conference on Financial Cryptography and Data Security, Barbados, 3-7 March.

Gandal, N, J Hamrick, T Moore and T Oberman (2017), “Price Manipulation in the Bitcoin Ecosystem,” CEPR Discussion Paper No. 12061.

Mooser, M, R Bohme and D Breuker (2013), “An inquiry into money laundering devices in the Bitcoin ecosystem”, in Proceedings of the Seventh APWG eCrime Re-searcher’s Summit, pp. 1-14.

Ron, D and A Shamir (2013), “Quantitative analysis of the utter Bitcoin transaction graph”, in Financial Cryptography and Data Security, Vol. Seven thousand eight hundred fifty nine of Lecture Notes in Computer Science, pp. 6-24.

Vasek, M and T Moore (2015), “There’s no free lunch, even using Bitcoin: Tracking the popularity and profits of virtual currency scams”, in R Bohme and T Okamoto (eds), Financial Cryptography and Data Security, volume eight thousand nine hundred seventy five of Lecture Notes in Computer Science, pp. 44-61.

Vasek, M, J Bonneau, R Castellucci, C Keith and T Moore (2016), “The Bitcoin brain drain: a brief paper on the use and manhandle of bitcoin brain wallets”, in Financial Cryptography and Data Security, Lecture Notes in Computer Science.

Yuxing Huang, D, H Dharmdasani, S Meiklejohn, V Dave, C Grier, D McCoy, S Savage, N Weaver, A Snoeren and K Levchenko (2014), “Botcoin: Monetizing stolen cycles”, in Proceedings of the Network and Distributed System Security Symposium.

Endnotes

[1] The Bitcoin ecosystem includes the core network for propagating transactions, the blockchain, and many intermediaries such as currency exchanges, mining pools, and payment processors that facilitate trade.

[Two] Markus was primarily active in period Three, but he was also active a few days during periods 1,Two, and Four. He was not active on the same days as Willy, who was only active in period Four.

Price manipulation in the Bitcoin ecosystem, VOX, CEPR’s Policy Portal

VOX CEPR’s Policy Portal

Research-based policy analysis and commentary from leading economists

Price manipulation in the Bitcoin ecosystem

Neil Gandal, JT Hamrick, Tyler Moore, Tali Oberman twenty two June two thousand seventeen

The cryptocurrency Bitcoin has attracted widespread interest, in large part due to wild swings in its valuation. This column considers an earlier rise in the Bitcoin price to investigate what is driving the currency’s price spikes. The two thousand thirteen rise was caused by fraudulent trades taking place at the largest Bitcoin currency exchange at the time. This finding has implications for policymakers as they weigh what, if anything, to do about regulating cryptocurrencies in light of the record high Bitcoin valuation that many fear is a bubble.

Related

The digital currency Bitcoin was introduced in 2009. Bitcoin and the many other digital currencies are primarily online currencies. The key currencies are those based primarily on cryptography, and Bitcoin is the leading ‘cryptocurrency’.

Bitcoin has experienced a meteoric rise in popularity since its introduction. While digital currencies were proposed as early as the 1980s, Bitcoin was the very first to catch on. The total value of all Bitcoins in circulation reached $45 billion in June 2017. Its success has inspired scores of contesting cryptocurrencies that go after a similar design. Bitcoin and most other cryptocurrencies do not require a central authority to validate and lodge transactions. Instead, these currencies use cryptography (and an internal incentive system) to control transactions, manage the supply, and prevent fraud. Payments are validated by a decentralised network. Once confirmed, all transactions are stored digitally and recorded in a public ‘blockchain’,’ which can be thought of as a distributed accounting system.

While Bitcoin’s algorithm provides safeguards against ‘counterfeiting’ of the currency, the eco-system is still vulnerable to theft. Users keep keys to their Bitcoins and make transactions with the help of wallets. Exchanges facilitate trade inbetween Bitcoins and fiat currencies, and also permit for storing Bitcoins. Bitcoins can be stolen through wallets or exchanges. Exchanges have been targeted more frequently than wallets because many wallets are located on users’ (local) computers, while exchanges frequently store customer deposits in their own (much larger) wallets.

The supply of most cryptocurrencies increases at a predetermined rate, and cannot be switched by any central authority. There are about fifteen million Bitcoins presently in circulation, with the ultimate number eventually reaching twenty one million. The stationary supply in the long run creates concerns about the deflationary aspect of the currency.

While Bitcoin shows superb promise to disrupt existing payment systems through innovations in its technical design, the Bitcoin ecosystem one has been the frequent target of attacks by financially motivated criminals. Due to the unregulated, decentralised environment in which they operate, cryptocurrencies are under constant threat of attack.

Bitcoin only recently became a subject of research in economics. However, the topic has been of interest for longer in computer science (for early work by computer scientists on incentives, see Babaioff et al. 2012, and Eyal and Sirer 2014.) Numerous researchers have conducted studies in order to document and combat threats such as Ponzi schemes, money laundering, mining botnets, and the theft of cryptocurrency wallets (Moeser et al. 2013, Vasek and Moore 2015, Vasek et al. 2016, Yuxing et al. 2014). Ron and Shamir (2013) attempt to identify suspicious trading activity by building a graph of Bitcoin transactions found in the public ledger. None of these papers can associate individual transactions with specific users of the currency exchanges.

In latest work, we display that the very first time Bitcoin reached an exchange rate of more than $1,000, the meteoric rise was driven by fraud (Gandal et al. 2017). We leverage a unique and very detailed dataset to examine suspicious trading activity that occurred over a ten-month period in two thousand thirteen on Mt. Gox, the leading Bitcoin currency exchange at the time. We very first quantify the extent of the suspicious/fraudulent trading activity and showcase that it constitutes a large fraction of trading on the days the activity occurred. We then display how this trading activity affected the exchange rates at Mt. Gox and other leading currency exchanges.

Figure 1 Bitcoin–US dollar exchange rate, with periods of suspicious activity shaded

While it was the superior currency exchange when Bitcoin very first shot to prominence in early 2013, behind the scenes, Tokyo-based Mt. Gox was in trouble. In addition to suffering from repeated denial-of-service attacks and Bitcoin thefts, two unauthorised traders were able to transact on the exchange without spending real money. In the very first case, a trader dubbed ‘Markus’ was credited with Bitcoins by duplicating previously finished transactions. In the 2nd case, a trader dubbed ‘Willy’ bought Bitcoins from traders by ‘crediting’ the sellers’ accounts with fiat currencies that, in many cases, could not be withdrawn. Figure one shows when these fraudulent traders were active, along with the Bitcoin–US dollar exchange rate. Most noteworthy is that Willy’s operation coincided with an unprecedented leap in the price of Bitcoin: from around $150 to over $1000. In early 2014, Mt. Gox collapsed, and the Bitcoin price fell with it. Only recently, in early 2017, has Bitcoin surpassed the levels of the earlier rise.

However, how do we know that the rise was caused by the fraudulent trades? Fortunately for us as researchers, the unauthorised trades did not take place every day. Table one shows the daily switch in the Bitcoin–US dollar exchange rate for various time periods on Mt. Gox. In the two quarters before unauthorised trading commenced, the daily price increase was, on average, positive but relatively petite: a $0.21 increase in the very first period and a $1 increase in the 2nd period. During the third quarter, when unauthorised trading began, the price rose by an average of $Three.15 on the seventeen days in which Markus traded, but fell on average by $0.51 on the seventy five days he did not trade. However, it is during the final quarter, when Willy began trading, that the difference became stark. On the fifty days in which Willy traded, the Bitcoin price rose by an average of $21.85. On the forty one days in which Willy did not make unauthorizsed purchases, the price fell by $0.88 on average. (Table one is very similar for the other leading exchanges as well.)

Table 1 Average daily switch in BTC/USD exchange rate as a function of fraudulent activity Two

In our utter paper, we conduct a regression analysis to examine whether other factors such as the relatively numerous and varied attacks on the Mt. Gox exchange could explain the switch in the daily Bitcoin price, both at Mt. Gox and other leading exchanges (Gandal et al. 2017).

The analysis confirms that only Willy’s trading presence affected the price. The estimated coefficient (on the dummy variable for whether Willy was active) is virtually the same ($21.65) as in Table 1. We conclude that the suspicious trading activity of a single actor was the primary cause of the massive spike in the Bitcoin–US dollar exchange rate, in which the rate rose from around $150 to over $1,000 in just two months in late 2013. The fall was almost as precipitous: the Mt. Gox exchange folded due to insolvency in early 2014, and it has taken more than three years for Bitcoin to match the rise triggered by fraudulent transactions.

Why should we care about the Bitcoin manipulation that took place in 2013? After all, the Bitcoin ecosystem is not almost as significant as the Fresh York Stock Exchange. Nonetheless, latest trends indicate that Bitcoin is becoming an significant asset in the financial system.

Trading in cryptocurrency assets has exploded recently. In the case of Bitcoin, during the one year period ending in mid-June 2017, the market capitalisation enhanced massively from around $7 billion to $45 billion; that is an increase of over 500% in one year. The market cap of other cryptocurrencies surged by even more. In the one-year period ending in mid-May 2017, the market value of cryptocurrencies excluding Bitcoin surged from $1.7 billion to more than $29 billion; that is an increase of more than 1,900%. The markets for these other cryptocurrencies are very skinny and subject to manipulation. Given that we now know the Bitcoin price has been artificially inflated by unauthorised trades in the past, we must view the present rise with good caution, and not necessarily consider it a ‘healthy bubble’, as recently claimed in The Economist (2017).

As mainstream finance invests in cryptocurrency assets and as countries take steps toward legalising Bitcoin as a payment system (as Japan did in April 2017), it is significant to understand how susceptible cryptocurrency markets are to manipulation. We encourage the nascent cryptocurrency industry to work with regulators and researchers to share anonymised transaction data so that more confidence can be placed in the veracity of exchange rates.

References

Babaioff, M, S Dobzinski, S Oren and A Zohar (2012), “On bitcoin and crimson balloons” in Proceedings of the 13th ACM Conference on Electronic Commerce, pp. 56-73.

Eyal, I and E Sirer (2014), “Majority is not Enough: Bitcoin Mining is Vulnerable”, paper introduced at the Eighteenth International Conference on Financial Cryptography and Data Security, Barbados, 3-7 March.

Gandal, N, J Hamrick, T Moore and T Oberman (2017), “Price Manipulation in the Bitcoin Ecosystem,” CEPR Discussion Paper No. 12061.

Mooser, M, R Bohme and D Breuker (2013), “An inquiry into money laundering implements in the Bitcoin ecosystem”, in Proceedings of the Seventh APWG eCrime Re-searcher’s Summit, pp. 1-14.

Ron, D and A Shamir (2013), “Quantitative analysis of the utter Bitcoin transaction graph”, in Financial Cryptography and Data Security, Vol. Seven thousand eight hundred fifty nine of Lecture Notes in Computer Science, pp. 6-24.

Vasek, M and T Moore (2015), “There’s no free lunch, even using Bitcoin: Tracking the popularity and profits of virtual currency scams”, in R Bohme and T Okamoto (eds), Financial Cryptography and Data Security, volume eight thousand nine hundred seventy five of Lecture Notes in Computer Science, pp. 44-61.

Vasek, M, J Bonneau, R Castellucci, C Keith and T Moore (2016), “The Bitcoin brain drain: a brief paper on the use and manhandle of bitcoin brain wallets”, in Financial Cryptography and Data Security, Lecture Notes in Computer Science.

Yuxing Huang, D, H Dharmdasani, S Meiklejohn, V Dave, C Grier, D McCoy, S Savage, N Weaver, A Snoeren and K Levchenko (2014), “Botcoin: Monetizing stolen cycles”, in Proceedings of the Network and Distributed System Security Symposium.

Endnotes

[1] The Bitcoin ecosystem includes the core network for propagating transactions, the blockchain, and many intermediaries such as currency exchanges, mining pools, and payment processors that facilitate trade.

[Two] Markus was primarily active in period Three, but he was also active a few days during periods 1,Two, and Four. He was not active on the same days as Willy, who was only active in period Four.

Price manipulation in the Bitcoin ecosystem, VOX, CEPR’s Policy Portal

VOX CEPR’s Policy Portal

Research-based policy analysis and commentary from leading economists

Price manipulation in the Bitcoin ecosystem

Neil Gandal, JT Hamrick, Tyler Moore, Tali Oberman twenty two June two thousand seventeen

The cryptocurrency Bitcoin has attracted widespread interest, in large part due to wild swings in its valuation. This column considers an earlier rise in the Bitcoin price to investigate what is driving the currency’s price spikes. The two thousand thirteen rise was caused by fraudulent trades taking place at the largest Bitcoin currency exchange at the time. This finding has implications for policymakers as they weigh what, if anything, to do about regulating cryptocurrencies in light of the record high Bitcoin valuation that many fear is a bubble.

Related

The digital currency Bitcoin was introduced in 2009. Bitcoin and the many other digital currencies are primarily online currencies. The key currencies are those based primarily on cryptography, and Bitcoin is the leading ‘cryptocurrency’.

Bitcoin has experienced a meteoric rise in popularity since its introduction. While digital currencies were proposed as early as the 1980s, Bitcoin was the very first to catch on. The total value of all Bitcoins in circulation reached $45 billion in June 2017. Its success has inspired scores of challenging cryptocurrencies that go after a similar design. Bitcoin and most other cryptocurrencies do not require a central authority to validate and lodge transactions. Instead, these currencies use cryptography (and an internal incentive system) to control transactions, manage the supply, and prevent fraud. Payments are validated by a decentralised network. Once confirmed, all transactions are stored digitally and recorded in a public ‘blockchain’,’ which can be thought of as a distributed accounting system.

While Bitcoin’s algorithm provides safeguards against ‘counterfeiting’ of the currency, the eco-system is still vulnerable to theft. Users keep keys to their Bitcoins and make transactions with the help of wallets. Exchanges facilitate trade inbetween Bitcoins and fiat currencies, and also permit for storing Bitcoins. Bitcoins can be stolen through wallets or exchanges. Exchanges have been targeted more frequently than wallets because many wallets are located on users’ (local) computers, while exchanges frequently store customer deposits in their own (much larger) wallets.

The supply of most cryptocurrencies increases at a predetermined rate, and cannot be switched by any central authority. There are about fifteen million Bitcoins presently in circulation, with the ultimate number eventually reaching twenty one million. The motionless supply in the long run creates concerns about the deflationary aspect of the currency.

While Bitcoin shows good promise to disrupt existing payment systems through innovations in its technical design, the Bitcoin ecosystem one has been the frequent target of attacks by financially motivated criminals. Due to the unregulated, decentralised environment in which they operate, cryptocurrencies are under constant threat of attack.

Bitcoin only recently became a subject of research in economics. However, the topic has been of interest for longer in computer science (for early work by computer scientists on incentives, see Babaioff et al. 2012, and Eyal and Sirer 2014.) Numerous researchers have conducted studies in order to document and combat threats such as Ponzi schemes, money laundering, mining botnets, and the theft of cryptocurrency wallets (Moeser et al. 2013, Vasek and Moore 2015, Vasek et al. 2016, Yuxing et al. 2014). Ron and Shamir (2013) attempt to identify suspicious trading activity by building a graph of Bitcoin transactions found in the public ledger. None of these papers can associate individual transactions with specific users of the currency exchanges.

In latest work, we display that the very first time Bitcoin reached an exchange rate of more than $1,000, the meteoric rise was driven by fraud (Gandal et al. 2017). We leverage a unique and very detailed dataset to examine suspicious trading activity that occurred over a ten-month period in two thousand thirteen on Mt. Gox, the leading Bitcoin currency exchange at the time. We very first quantify the extent of the suspicious/fraudulent trading activity and demonstrate that it constitutes a large fraction of trading on the days the activity occurred. We then showcase how this trading activity affected the exchange rates at Mt. Gox and other leading currency exchanges.

Figure 1 Bitcoin–US dollar exchange rate, with periods of suspicious activity shaded

While it was the superior currency exchange when Bitcoin very first shot to prominence in early 2013, behind the scenes, Tokyo-based Mt. Gox was in trouble. In addition to suffering from repeated denial-of-service attacks and Bitcoin thefts, two unauthorised traders were able to transact on the exchange without spending real money. In the very first case, a trader dubbed ‘Markus’ was credited with Bitcoins by duplicating previously ended transactions. In the 2nd case, a trader dubbed ‘Willy’ bought Bitcoins from traders by ‘crediting’ the sellers’ accounts with fiat currencies that, in many cases, could not be withdrawn. Figure one shows when these fraudulent traders were active, along with the Bitcoin–US dollar exchange rate. Most noteworthy is that Willy’s operation coincided with an unprecedented leap in the price of Bitcoin: from around $150 to over $1000. In early 2014, Mt. Gox collapsed, and the Bitcoin price fell with it. Only recently, in early 2017, has Bitcoin surpassed the levels of the earlier rise.

However, how do we know that the rise was caused by the fraudulent trades? Fortunately for us as researchers, the unauthorised trades did not take place every day. Table one shows the daily switch in the Bitcoin–US dollar exchange rate for various time periods on Mt. Gox. In the two quarters before unauthorised trading commenced, the daily price increase was, on average, positive but relatively petite: a $0.21 increase in the very first period and a $1 increase in the 2nd period. During the third quarter, when unauthorised trading embarked, the price rose by an average of $Trio.15 on the seventeen days in which Markus traded, but fell on average by $0.51 on the seventy five days he did not trade. However, it is during the final quarter, when Willy began trading, that the difference became stark. On the fifty days in which Willy traded, the Bitcoin price rose by an average of $21.85. On the forty one days in which Willy did not make unauthorizsed purchases, the price fell by $0.88 on average. (Table one is very similar for the other leading exchanges as well.)

Table 1 Average daily switch in BTC/USD exchange rate as a function of fraudulent activity Two

In our utter paper, we conduct a regression analysis to examine whether other factors such as the relatively numerous and varied attacks on the Mt. Gox exchange could explain the switch in the daily Bitcoin price, both at Mt. Gox and other leading exchanges (Gandal et al. 2017).

The analysis confirms that only Willy’s trading presence affected the price. The estimated coefficient (on the dummy variable for whether Willy was active) is virtually the same ($21.65) as in Table 1. We conclude that the suspicious trading activity of a single actor was the primary cause of the massive spike in the Bitcoin–US dollar exchange rate, in which the rate rose from around $150 to over $1,000 in just two months in late 2013. The fall was almost as precipitous: the Mt. Gox exchange folded due to insolvency in early 2014, and it has taken more than three years for Bitcoin to match the rise triggered by fraudulent transactions.

Why should we care about the Bitcoin manipulation that took place in 2013? After all, the Bitcoin ecosystem is not almost as significant as the Fresh York Stock Exchange. Nonetheless, latest trends indicate that Bitcoin is becoming an significant asset in the financial system.

Trading in cryptocurrency assets has exploded recently. In the case of Bitcoin, during the one year period ending in mid-June 2017, the market capitalisation enhanced massively from around $7 billion to $45 billion; that is an increase of over 500% in one year. The market cap of other cryptocurrencies surged by even more. In the one-year period ending in mid-May 2017, the market value of cryptocurrencies excluding Bitcoin surged from $1.7 billion to more than $29 billion; that is an increase of more than 1,900%. The markets for these other cryptocurrencies are very skinny and subject to manipulation. Given that we now know the Bitcoin price has been artificially inflated by unauthorised trades in the past, we must view the present rise with good caution, and not necessarily consider it a ‘healthy bubble’, as recently claimed in The Economist (2017).

As mainstream finance invests in cryptocurrency assets and as countries take steps toward legalising Bitcoin as a payment system (as Japan did in April 2017), it is significant to understand how susceptible cryptocurrency markets are to manipulation. We encourage the nascent cryptocurrency industry to work with regulators and researchers to share anonymised transaction data so that more confidence can be placed in the veracity of exchange rates.

References

Babaioff, M, S Dobzinski, S Oren and A Zohar (2012), “On bitcoin and crimson balloons” in Proceedings of the 13th ACM Conference on Electronic Commerce, pp. 56-73.

Eyal, I and E Sirer (2014), “Majority is not Enough: Bitcoin Mining is Vulnerable”, paper introduced at the Eighteenth International Conference on Financial Cryptography and Data Security, Barbados, 3-7 March.

Gandal, N, J Hamrick, T Moore and T Oberman (2017), “Price Manipulation in the Bitcoin Ecosystem,” CEPR Discussion Paper No. 12061.

Mooser, M, R Bohme and D Breuker (2013), “An inquiry into money laundering contraptions in the Bitcoin ecosystem”, in Proceedings of the Seventh APWG eCrime Re-searcher’s Summit, pp. 1-14.

Ron, D and A Shamir (2013), “Quantitative analysis of the utter Bitcoin transaction graph”, in Financial Cryptography and Data Security, Vol. Seven thousand eight hundred fifty nine of Lecture Notes in Computer Science, pp. 6-24.

Vasek, M and T Moore (2015), “There’s no free lunch, even using Bitcoin: Tracking the popularity and profits of virtual currency scams”, in R Bohme and T Okamoto (eds), Financial Cryptography and Data Security, volume eight thousand nine hundred seventy five of Lecture Notes in Computer Science, pp. 44-61.

Vasek, M, J Bonneau, R Castellucci, C Keith and T Moore (2016), “The Bitcoin brain drain: a brief paper on the use and manhandle of bitcoin brain wallets”, in Financial Cryptography and Data Security, Lecture Notes in Computer Science.

Yuxing Huang, D, H Dharmdasani, S Meiklejohn, V Dave, C Grier, D McCoy, S Savage, N Weaver, A Snoeren and K Levchenko (2014), “Botcoin: Monetizing stolen cycles”, in Proceedings of the Network and Distributed System Security Symposium.

Endnotes

[1] The Bitcoin ecosystem includes the core network for propagating transactions, the blockchain, and many intermediaries such as currency exchanges, mining pools, and payment processors that facilitate trade.

[Two] Markus was primarily active in period Three, but he was also active a few days during periods 1,Two, and Four. He was not active on the same days as Willy, who was only active in period Four.

Price manipulation in the Bitcoin ecosystem, VOX, CEPR’s Policy Portal

VOX CEPR’s Policy Portal

Research-based policy analysis and commentary from leading economists

Price manipulation in the Bitcoin ecosystem

Neil Gandal, JT Hamrick, Tyler Moore, Tali Oberman twenty two June two thousand seventeen

The cryptocurrency Bitcoin has attracted widespread interest, in large part due to wild swings in its valuation. This column considers an earlier rise in the Bitcoin price to investigate what is driving the currency’s price spikes. The two thousand thirteen rise was caused by fraudulent trades taking place at the largest Bitcoin currency exchange at the time. This finding has implications for policymakers as they weigh what, if anything, to do about regulating cryptocurrencies in light of the record high Bitcoin valuation that many fear is a bubble.

Related

The digital currency Bitcoin was introduced in 2009. Bitcoin and the many other digital currencies are primarily online currencies. The key currencies are those based primarily on cryptography, and Bitcoin is the leading ‘cryptocurrency’.

Bitcoin has experienced a meteoric rise in popularity since its introduction. While digital currencies were proposed as early as the 1980s, Bitcoin was the very first to catch on. The total value of all Bitcoins in circulation reached $45 billion in June 2017. Its success has inspired scores of contesting cryptocurrencies that go after a similar design. Bitcoin and most other cryptocurrencies do not require a central authority to validate and lodge transactions. Instead, these currencies use cryptography (and an internal incentive system) to control transactions, manage the supply, and prevent fraud. Payments are validated by a decentralised network. Once confirmed, all transactions are stored digitally and recorded in a public ‘blockchain’,’ which can be thought of as a distributed accounting system.

While Bitcoin’s algorithm provides safeguards against ‘counterfeiting’ of the currency, the eco-system is still vulnerable to theft. Users keep keys to their Bitcoins and make transactions with the help of wallets. Exchanges facilitate trade inbetween Bitcoins and fiat currencies, and also permit for storing Bitcoins. Bitcoins can be stolen through wallets or exchanges. Exchanges have been targeted more frequently than wallets because many wallets are located on users’ (local) computers, while exchanges frequently store customer deposits in their own (much larger) wallets.

The supply of most cryptocurrencies increases at a predetermined rate, and cannot be switched by any central authority. There are about fifteen million Bitcoins presently in circulation, with the ultimate number eventually reaching twenty one million. The stationary supply in the long run creates concerns about the deflationary aspect of the currency.

While Bitcoin shows superb promise to disrupt existing payment systems through innovations in its technical design, the Bitcoin ecosystem one has been the frequent target of attacks by financially motivated criminals. Due to the unregulated, decentralised environment in which they operate, cryptocurrencies are under constant threat of attack.

Bitcoin only recently became a subject of research in economics. However, the topic has been of interest for longer in computer science (for early work by computer scientists on incentives, see Babaioff et al. 2012, and Eyal and Sirer 2014.) Numerous researchers have conducted studies in order to document and combat threats such as Ponzi schemes, money laundering, mining botnets, and the theft of cryptocurrency wallets (Moeser et al. 2013, Vasek and Moore 2015, Vasek et al. 2016, Yuxing et al. 2014). Ron and Shamir (2013) attempt to identify suspicious trading activity by building a graph of Bitcoin transactions found in the public ledger. None of these papers can associate individual transactions with specific users of the currency exchanges.

In latest work, we demonstrate that the very first time Bitcoin reached an exchange rate of more than $1,000, the meteoric rise was driven by fraud (Gandal et al. 2017). We leverage a unique and very detailed dataset to examine suspicious trading activity that occurred over a ten-month period in two thousand thirteen on Mt. Gox, the leading Bitcoin currency exchange at the time. We very first quantify the extent of the suspicious/fraudulent trading activity and demonstrate that it constitutes a large fraction of trading on the days the activity occurred. We then demonstrate how this trading activity affected the exchange rates at Mt. Gox and other leading currency exchanges.

Figure 1 Bitcoin–US dollar exchange rate, with periods of suspicious activity shaded

While it was the superior currency exchange when Bitcoin very first shot to prominence in early 2013, behind the scenes, Tokyo-based Mt. Gox was in trouble. In addition to suffering from repeated denial-of-service attacks and Bitcoin thefts, two unauthorised traders were able to transact on the exchange without spending real money. In the very first case, a trader dubbed ‘Markus’ was credited with Bitcoins by duplicating previously ended transactions. In the 2nd case, a trader dubbed ‘Willy’ bought Bitcoins from traders by ‘crediting’ the sellers’ accounts with fiat currencies that, in many cases, could not be withdrawn. Figure one shows when these fraudulent traders were active, along with the Bitcoin–US dollar exchange rate. Most noteworthy is that Willy’s operation coincided with an unprecedented leap in the price of Bitcoin: from around $150 to over $1000. In early 2014, Mt. Gox collapsed, and the Bitcoin price fell with it. Only recently, in early 2017, has Bitcoin surpassed the levels of the earlier rise.

However, how do we know that the rise was caused by the fraudulent trades? Fortunately for us as researchers, the unauthorised trades did not take place every day. Table one shows the daily switch in the Bitcoin–US dollar exchange rate for various time periods on Mt. Gox. In the two quarters before unauthorised trading commenced, the daily price increase was, on average, positive but relatively puny: a $0.21 increase in the very first period and a $1 increase in the 2nd period. During the third quarter, when unauthorised trading embarked, the price rose by an average of $Three.15 on the seventeen days in which Markus traded, but fell on average by $0.51 on the seventy five days he did not trade. However, it is during the final quarter, when Willy began trading, that the difference became stark. On the fifty days in which Willy traded, the Bitcoin price rose by an average of $21.85. On the forty one days in which Willy did not make unauthorizsed purchases, the price fell by $0.88 on average. (Table one is very similar for the other leading exchanges as well.)

Table 1 Average daily switch in BTC/USD exchange rate as a function of fraudulent activity Two

In our utter paper, we conduct a regression analysis to examine whether other factors such as the relatively numerous and varied attacks on the Mt. Gox exchange could explain the switch in the daily Bitcoin price, both at Mt. Gox and other leading exchanges (Gandal et al. 2017).

The analysis confirms that only Willy’s trading presence affected the price. The estimated coefficient (on the dummy variable for whether Willy was active) is virtually the same ($21.65) as in Table 1. We conclude that the suspicious trading activity of a single actor was the primary cause of the massive spike in the Bitcoin–US dollar exchange rate, in which the rate rose from around $150 to over $1,000 in just two months in late 2013. The fall was almost as precipitous: the Mt. Gox exchange folded due to insolvency in early 2014, and it has taken more than three years for Bitcoin to match the rise triggered by fraudulent transactions.

Why should we care about the Bitcoin manipulation that took place in 2013? After all, the Bitcoin ecosystem is not almost as significant as the Fresh York Stock Exchange. Nonetheless, latest trends indicate that Bitcoin is becoming an significant asset in the financial system.

Trading in cryptocurrency assets has exploded recently. In the case of Bitcoin, during the one year period ending in mid-June 2017, the market capitalisation enhanced massively from around $7 billion to $45 billion; that is an increase of over 500% in one year. The market cap of other cryptocurrencies surged by even more. In the one-year period ending in mid-May 2017, the market value of cryptocurrencies excluding Bitcoin surged from $1.7 billion to more than $29 billion; that is an increase of more than 1,900%. The markets for these other cryptocurrencies are very skinny and subject to manipulation. Given that we now know the Bitcoin price has been artificially inflated by unauthorised trades in the past, we must view the present rise with superb caution, and not necessarily consider it a ‘healthy bubble’, as recently claimed in The Economist (2017).

As mainstream finance invests in cryptocurrency assets and as countries take steps toward legalising Bitcoin as a payment system (as Japan did in April 2017), it is significant to understand how susceptible cryptocurrency markets are to manipulation. We encourage the nascent cryptocurrency industry to work with regulators and researchers to share anonymised transaction data so that more confidence can be placed in the veracity of exchange rates.

References

Babaioff, M, S Dobzinski, S Oren and A Zohar (2012), “On bitcoin and crimson balloons” in Proceedings of the 13th ACM Conference on Electronic Commerce, pp. 56-73.

Eyal, I and E Sirer (2014), “Majority is not Enough: Bitcoin Mining is Vulnerable”, paper introduced at the Eighteenth International Conference on Financial Cryptography and Data Security, Barbados, 3-7 March.

Gandal, N, J Hamrick, T Moore and T Oberman (2017), “Price Manipulation in the Bitcoin Ecosystem,” CEPR Discussion Paper No. 12061.

Mooser, M, R Bohme and D Breuker (2013), “An inquiry into money laundering contraptions in the Bitcoin ecosystem”, in Proceedings of the Seventh APWG eCrime Re-searcher’s Summit, pp. 1-14.

Ron, D and A Shamir (2013), “Quantitative analysis of the total Bitcoin transaction graph”, in Financial Cryptography and Data Security, Vol. Seven thousand eight hundred fifty nine of Lecture Notes in Computer Science, pp. 6-24.

Vasek, M and T Moore (2015), “There’s no free lunch, even using Bitcoin: Tracking the popularity and profits of virtual currency scams”, in R Bohme and T Okamoto (eds), Financial Cryptography and Data Security, volume eight thousand nine hundred seventy five of Lecture Notes in Computer Science, pp. 44-61.

Vasek, M, J Bonneau, R Castellucci, C Keith and T Moore (2016), “The Bitcoin brain drain: a brief paper on the use and manhandle of bitcoin brain wallets”, in Financial Cryptography and Data Security, Lecture Notes in Computer Science.

Yuxing Huang, D, H Dharmdasani, S Meiklejohn, V Dave, C Grier, D McCoy, S Savage, N Weaver, A Snoeren and K Levchenko (2014), “Botcoin: Monetizing stolen cycles”, in Proceedings of the Network and Distributed System Security Symposium.

Endnotes

[1] The Bitcoin ecosystem includes the core network for propagating transactions, the blockchain, and many intermediaries such as currency exchanges, mining pools, and payment processors that facilitate trade.

[Two] Markus was primarily active in period Trio, but he was also active a few days during periods 1,Two, and Four. He was not active on the same days as Willy, who was only active in period Four.

Price manipulation in the Bitcoin ecosystem, VOX, CEPR’s Policy Portal

VOX CEPR’s Policy Portal

Research-based policy analysis and commentary from leading economists

Price manipulation in the Bitcoin ecosystem

Neil Gandal, JT Hamrick, Tyler Moore, Tali Oberman twenty two June two thousand seventeen

The cryptocurrency Bitcoin has attracted widespread interest, in large part due to wild swings in its valuation. This column considers an earlier rise in the Bitcoin price to investigate what is driving the currency’s price spikes. The two thousand thirteen rise was caused by fraudulent trades taking place at the largest Bitcoin currency exchange at the time. This finding has implications for policymakers as they weigh what, if anything, to do about regulating cryptocurrencies in light of the record high Bitcoin valuation that many fear is a bubble.

Related

The digital currency Bitcoin was introduced in 2009. Bitcoin and the many other digital currencies are primarily online currencies. The key currencies are those based primarily on cryptography, and Bitcoin is the leading ‘cryptocurrency’.

Bitcoin has experienced a meteoric rise in popularity since its introduction. While digital currencies were proposed as early as the 1980s, Bitcoin was the very first to catch on. The total value of all Bitcoins in circulation reached $45 billion in June 2017. Its success has inspired scores of challenging cryptocurrencies that go after a similar design. Bitcoin and most other cryptocurrencies do not require a central authority to validate and lodge transactions. Instead, these currencies use cryptography (and an internal incentive system) to control transactions, manage the supply, and prevent fraud. Payments are validated by a decentralised network. Once confirmed, all transactions are stored digitally and recorded in a public ‘blockchain’,’ which can be thought of as a distributed accounting system.

While Bitcoin’s algorithm provides safeguards against ‘counterfeiting’ of the currency, the eco-system is still vulnerable to theft. Users keep keys to their Bitcoins and make transactions with the help of wallets. Exchanges facilitate trade inbetween Bitcoins and fiat currencies, and also permit for storing Bitcoins. Bitcoins can be stolen through wallets or exchanges. Exchanges have been targeted more frequently than wallets because many wallets are located on users’ (local) computers, while exchanges frequently store customer deposits in their own (much larger) wallets.

The supply of most cryptocurrencies increases at a predetermined rate, and cannot be switched by any central authority. There are about fifteen million Bitcoins presently in circulation, with the ultimate number eventually reaching twenty one million. The stationary supply in the long run creates concerns about the deflationary aspect of the currency.

While Bitcoin shows superb promise to disrupt existing payment systems through innovations in its technical design, the Bitcoin ecosystem one has been the frequent target of attacks by financially motivated criminals. Due to the unregulated, decentralised environment in which they operate, cryptocurrencies are under constant threat of attack.

Bitcoin only recently became a subject of research in economics. However, the topic has been of interest for longer in computer science (for early work by computer scientists on incentives, see Babaioff et al. 2012, and Eyal and Sirer 2014.) Numerous researchers have conducted studies in order to document and combat threats such as Ponzi schemes, money laundering, mining botnets, and the theft of cryptocurrency wallets (Moeser et al. 2013, Vasek and Moore 2015, Vasek et al. 2016, Yuxing et al. 2014). Ron and Shamir (2013) attempt to identify suspicious trading activity by building a graph of Bitcoin transactions found in the public ledger. None of these papers can associate individual transactions with specific users of the currency exchanges.

In latest work, we display that the very first time Bitcoin reached an exchange rate of more than $1,000, the meteoric rise was driven by fraud (Gandal et al. 2017). We leverage a unique and very detailed dataset to examine suspicious trading activity that occurred over a ten-month period in two thousand thirteen on Mt. Gox, the leading Bitcoin currency exchange at the time. We very first quantify the extent of the suspicious/fraudulent trading activity and showcase that it constitutes a large fraction of trading on the days the activity occurred. We then display how this trading activity affected the exchange rates at Mt. Gox and other leading currency exchanges.

Figure 1 Bitcoin–US dollar exchange rate, with periods of suspicious activity shaded

While it was the superior currency exchange when Bitcoin very first shot to prominence in early 2013, behind the scenes, Tokyo-based Mt. Gox was in trouble. In addition to suffering from repeated denial-of-service attacks and Bitcoin thefts, two unauthorised traders were able to transact on the exchange without spending real money. In the very first case, a trader dubbed ‘Markus’ was credited with Bitcoins by duplicating previously ended transactions. In the 2nd case, a trader dubbed ‘Willy’ bought Bitcoins from traders by ‘crediting’ the sellers’ accounts with fiat currencies that, in many cases, could not be withdrawn. Figure one shows when these fraudulent traders were active, along with the Bitcoin–US dollar exchange rate. Most noteworthy is that Willy’s operation coincided with an unprecedented leap in the price of Bitcoin: from around $150 to over $1000. In early 2014, Mt. Gox collapsed, and the Bitcoin price fell with it. Only recently, in early 2017, has Bitcoin surpassed the levels of the earlier rise.

However, how do we know that the rise was caused by the fraudulent trades? Fortunately for us as researchers, the unauthorised trades did not take place every day. Table one shows the daily switch in the Bitcoin–US dollar exchange rate for various time periods on Mt. Gox. In the two quarters before unauthorised trading commenced, the daily price increase was, on average, positive but relatively petite: a $0.21 increase in the very first period and a $1 increase in the 2nd period. During the third quarter, when unauthorised trading commenced, the price rose by an average of $Three.15 on the seventeen days in which Markus traded, but fell on average by $0.51 on the seventy five days he did not trade. However, it is during the final quarter, when Willy began trading, that the difference became stark. On the fifty days in which Willy traded, the Bitcoin price rose by an average of $21.85. On the forty one days in which Willy did not make unauthorizsed purchases, the price fell by $0.88 on average. (Table one is very similar for the other leading exchanges as well.)

Table 1 Average daily switch in BTC/USD exchange rate as a function of fraudulent activity Two

In our total paper, we conduct a regression analysis to examine whether other factors such as the relatively numerous and varied attacks on the Mt. Gox exchange could explain the switch in the daily Bitcoin price, both at Mt. Gox and other leading exchanges (Gandal et al. 2017).

The analysis confirms that only Willy’s trading presence affected the price. The estimated coefficient (on the dummy variable for whether Willy was active) is virtually the same ($21.65) as in Table 1. We conclude that the suspicious trading activity of a single actor was the primary cause of the massive spike in the Bitcoin–US dollar exchange rate, in which the rate rose from around $150 to over $1,000 in just two months in late 2013. The fall was almost as precipitous: the Mt. Gox exchange folded due to insolvency in early 2014, and it has taken more than three years for Bitcoin to match the rise triggered by fraudulent transactions.

Why should we care about the Bitcoin manipulation that took place in 2013? After all, the Bitcoin ecosystem is not almost as significant as the Fresh York Stock Exchange. Nonetheless, latest trends indicate that Bitcoin is becoming an significant asset in the financial system.

Trading in cryptocurrency assets has exploded recently. In the case of Bitcoin, during the one year period ending in mid-June 2017, the market capitalisation enhanced massively from around $7 billion to $45 billion; that is an increase of over 500% in one year. The market cap of other cryptocurrencies surged by even more. In the one-year period ending in mid-May 2017, the market value of cryptocurrencies excluding Bitcoin surged from $1.7 billion to more than $29 billion; that is an increase of more than 1,900%. The markets for these other cryptocurrencies are very skinny and subject to manipulation. Given that we now know the Bitcoin price has been artificially inflated by unauthorised trades in the past, we must view the present rise with excellent caution, and not necessarily consider it a ‘healthy bubble’, as recently claimed in The Economist (2017).

As mainstream finance invests in cryptocurrency assets and as countries take steps toward legalising Bitcoin as a payment system (as Japan did in April 2017), it is significant to understand how susceptible cryptocurrency markets are to manipulation. We encourage the nascent cryptocurrency industry to work with regulators and researchers to share anonymised transaction data so that more confidence can be placed in the veracity of exchange rates.

References

Babaioff, M, S Dobzinski, S Oren and A Zohar (2012), “On bitcoin and crimson balloons” in Proceedings of the 13th ACM Conference on Electronic Commerce, pp. 56-73.

Eyal, I and E Sirer (2014), “Majority is not Enough: Bitcoin Mining is Vulnerable”, paper introduced at the Eighteenth International Conference on Financial Cryptography and Data Security, Barbados, 3-7 March.

Gandal, N, J Hamrick, T Moore and T Oberman (2017), “Price Manipulation in the Bitcoin Ecosystem,” CEPR Discussion Paper No. 12061.

Mooser, M, R Bohme and D Breuker (2013), “An inquiry into money laundering implements in the Bitcoin ecosystem”, in Proceedings of the Seventh APWG eCrime Re-searcher’s Summit, pp. 1-14.

Ron, D and A Shamir (2013), “Quantitative analysis of the total Bitcoin transaction graph”, in Financial Cryptography and Data Security, Vol. Seven thousand eight hundred fifty nine of Lecture Notes in Computer Science, pp. 6-24.

Vasek, M and T Moore (2015), “There’s no free lunch, even using Bitcoin: Tracking the popularity and profits of virtual currency scams”, in R Bohme and T Okamoto (eds), Financial Cryptography and Data Security, volume eight thousand nine hundred seventy five of Lecture Notes in Computer Science, pp. 44-61.

Vasek, M, J Bonneau, R Castellucci, C Keith and T Moore (2016), “The Bitcoin brain drain: a brief paper on the use and manhandle of bitcoin brain wallets”, in Financial Cryptography and Data Security, Lecture Notes in Computer Science.

Yuxing Huang, D, H Dharmdasani, S Meiklejohn, V Dave, C Grier, D McCoy, S Savage, N Weaver, A Snoeren and K Levchenko (2014), “Botcoin: Monetizing stolen cycles”, in Proceedings of the Network and Distributed System Security Symposium.

Endnotes

[1] The Bitcoin ecosystem includes the core network for propagating transactions, the blockchain, and many intermediaries such as currency exchanges, mining pools, and payment processors that facilitate trade.

[Two] Markus was primarily active in period Trio, but he was also active a few days during periods 1,Two, and Four. He was not active on the same days as Willy, who was only active in period Four.

Price manipulation in the Bitcoin ecosystem, VOX, CEPR’s Policy Portal

VOX CEPR’s Policy Portal

Research-based policy analysis and commentary from leading economists

Price manipulation in the Bitcoin ecosystem

Neil Gandal, JT Hamrick, Tyler Moore, Tali Oberman twenty two June two thousand seventeen

The cryptocurrency Bitcoin has attracted widespread interest, in large part due to wild swings in its valuation. This column considers an earlier rise in the Bitcoin price to investigate what is driving the currency’s price spikes. The two thousand thirteen rise was caused by fraudulent trades taking place at the largest Bitcoin currency exchange at the time. This finding has implications for policymakers as they weigh what, if anything, to do about regulating cryptocurrencies in light of the record high Bitcoin valuation that many fear is a bubble.

Related

The digital currency Bitcoin was introduced in 2009. Bitcoin and the many other digital currencies are primarily online currencies. The key currencies are those based primarily on cryptography, and Bitcoin is the leading ‘cryptocurrency’.

Bitcoin has experienced a meteoric rise in popularity since its introduction. While digital currencies were proposed as early as the 1980s, Bitcoin was the very first to catch on. The total value of all Bitcoins in circulation reached $45 billion in June 2017. Its success has inspired scores of challenging cryptocurrencies that go after a similar design. Bitcoin and most other cryptocurrencies do not require a central authority to validate and lodge transactions. Instead, these currencies use cryptography (and an internal incentive system) to control transactions, manage the supply, and prevent fraud. Payments are validated by a decentralised network. Once confirmed, all transactions are stored digitally and recorded in a public ‘blockchain’,’ which can be thought of as a distributed accounting system.

While Bitcoin’s algorithm provides safeguards against ‘counterfeiting’ of the currency, the eco-system is still vulnerable to theft. Users keep keys to their Bitcoins and make transactions with the help of wallets. Exchanges facilitate trade inbetween Bitcoins and fiat currencies, and also permit for storing Bitcoins. Bitcoins can be stolen through wallets or exchanges. Exchanges have been targeted more frequently than wallets because many wallets are located on users’ (local) computers, while exchanges frequently store customer deposits in their own (much larger) wallets.

The supply of most cryptocurrencies increases at a predetermined rate, and cannot be switched by any central authority. There are about fifteen million Bitcoins presently in circulation, with the ultimate number eventually reaching twenty one million. The stationary supply in the long run creates concerns about the deflationary aspect of the currency.

While Bitcoin shows superb promise to disrupt existing payment systems through innovations in its technical design, the Bitcoin ecosystem one has been the frequent target of attacks by financially motivated criminals. Due to the unregulated, decentralised environment in which they operate, cryptocurrencies are under constant threat of attack.

Bitcoin only recently became a subject of research in economics. However, the topic has been of interest for longer in computer science (for early work by computer scientists on incentives, see Babaioff et al. 2012, and Eyal and Sirer 2014.) Numerous researchers have conducted studies in order to document and combat threats such as Ponzi schemes, money laundering, mining botnets, and the theft of cryptocurrency wallets (Moeser et al. 2013, Vasek and Moore 2015, Vasek et al. 2016, Yuxing et al. 2014). Ron and Shamir (2013) attempt to identify suspicious trading activity by building a graph of Bitcoin transactions found in the public ledger. None of these papers can associate individual transactions with specific users of the currency exchanges.

In latest work, we demonstrate that the very first time Bitcoin reached an exchange rate of more than $1,000, the meteoric rise was driven by fraud (Gandal et al. 2017). We leverage a unique and very detailed dataset to examine suspicious trading activity that occurred over a ten-month period in two thousand thirteen on Mt. Gox, the leading Bitcoin currency exchange at the time. We very first quantify the extent of the suspicious/fraudulent trading activity and display that it constitutes a large fraction of trading on the days the activity occurred. We then showcase how this trading activity affected the exchange rates at Mt. Gox and other leading currency exchanges.

Figure 1 Bitcoin–US dollar exchange rate, with periods of suspicious activity shaded

While it was the superior currency exchange when Bitcoin very first shot to prominence in early 2013, behind the scenes, Tokyo-based Mt. Gox was in trouble. In addition to suffering from repeated denial-of-service attacks and Bitcoin thefts, two unauthorised traders were able to transact on the exchange without spending real money. In the very first case, a trader dubbed ‘Markus’ was credited with Bitcoins by duplicating previously ended transactions. In the 2nd case, a trader dubbed ‘Willy’ bought Bitcoins from traders by ‘crediting’ the sellers’ accounts with fiat currencies that, in many cases, could not be withdrawn. Figure one shows when these fraudulent traders were active, along with the Bitcoin–US dollar exchange rate. Most noteworthy is that Willy’s operation coincided with an unprecedented hop in the price of Bitcoin: from around $150 to over $1000. In early 2014, Mt. Gox collapsed, and the Bitcoin price fell with it. Only recently, in early 2017, has Bitcoin surpassed the levels of the earlier rise.

However, how do we know that the rise was caused by the fraudulent trades? Fortunately for us as researchers, the unauthorised trades did not take place every day. Table one shows the daily switch in the Bitcoin–US dollar exchange rate for various time periods on Mt. Gox. In the two quarters before unauthorised trading commenced, the daily price increase was, on average, positive but relatively petite: a $0.21 increase in the very first period and a $1 increase in the 2nd period. During the third quarter, when unauthorised trading commenced, the price rose by an average of $Trio.15 on the seventeen days in which Markus traded, but fell on average by $0.51 on the seventy five days he did not trade. However, it is during the final quarter, when Willy began trading, that the difference became stark. On the fifty days in which Willy traded, the Bitcoin price rose by an average of $21.85. On the forty one days in which Willy did not make unauthorizsed purchases, the price fell by $0.88 on average. (Table one is very similar for the other leading exchanges as well.)

Table 1 Average daily switch in BTC/USD exchange rate as a function of fraudulent activity Two

In our total paper, we conduct a regression analysis to examine whether other factors such as the relatively numerous and varied attacks on the Mt. Gox exchange could explain the switch in the daily Bitcoin price, both at Mt. Gox and other leading exchanges (Gandal et al. 2017).

The analysis confirms that only Willy’s trading presence affected the price. The estimated coefficient (on the dummy variable for whether Willy was active) is virtually the same ($21.65) as in Table 1. We conclude that the suspicious trading activity of a single actor was the primary cause of the massive spike in the Bitcoin–US dollar exchange rate, in which the rate rose from around $150 to over $1,000 in just two months in late 2013. The fall was almost as precipitous: the Mt. Gox exchange folded due to insolvency in early 2014, and it has taken more than three years for Bitcoin to match the rise triggered by fraudulent transactions.

Why should we care about the Bitcoin manipulation that took place in 2013? After all, the Bitcoin ecosystem is not almost as significant as the Fresh York Stock Exchange. Nonetheless, latest trends indicate that Bitcoin is becoming an significant asset in the financial system.

Trading in cryptocurrency assets has exploded recently. In the case of Bitcoin, during the one year period ending in mid-June 2017, the market capitalisation enlargened massively from around $7 billion to $45 billion; that is an increase of over 500% in one year. The market cap of other cryptocurrencies surged by even more. In the one-year period ending in mid-May 2017, the market value of cryptocurrencies excluding Bitcoin surged from $1.7 billion to more than $29 billion; that is an increase of more than 1,900%. The markets for these other cryptocurrencies are very lean and subject to manipulation. Given that we now know the Bitcoin price has been artificially inflated by unauthorised trades in the past, we must view the present rise with superb caution, and not necessarily consider it a ‘healthy bubble’, as recently claimed in The Economist (2017).

As mainstream finance invests in cryptocurrency assets and as countries take steps toward legalising Bitcoin as a payment system (as Japan did in April 2017), it is significant to understand how susceptible cryptocurrency markets are to manipulation. We encourage the nascent cryptocurrency industry to work with regulators and researchers to share anonymised transaction data so that more confidence can be placed in the veracity of exchange rates.

References

Babaioff, M, S Dobzinski, S Oren and A Zohar (2012), “On bitcoin and crimson balloons” in Proceedings of the 13th ACM Conference on Electronic Commerce, pp. 56-73.

Eyal, I and E Sirer (2014), “Majority is not Enough: Bitcoin Mining is Vulnerable”, paper introduced at the Eighteenth International Conference on Financial Cryptography and Data Security, Barbados, 3-7 March.

Gandal, N, J Hamrick, T Moore and T Oberman (2017), “Price Manipulation in the Bitcoin Ecosystem,” CEPR Discussion Paper No. 12061.

Mooser, M, R Bohme and D Breuker (2013), “An inquiry into money laundering implements in the Bitcoin ecosystem”, in Proceedings of the Seventh APWG eCrime Re-searcher’s Summit, pp. 1-14.

Ron, D and A Shamir (2013), “Quantitative analysis of the total Bitcoin transaction graph”, in Financial Cryptography and Data Security, Vol. Seven thousand eight hundred fifty nine of Lecture Notes in Computer Science, pp. 6-24.

Vasek, M and T Moore (2015), “There’s no free lunch, even using Bitcoin: Tracking the popularity and profits of virtual currency scams”, in R Bohme and T Okamoto (eds), Financial Cryptography and Data Security, volume eight thousand nine hundred seventy five of Lecture Notes in Computer Science, pp. 44-61.

Vasek, M, J Bonneau, R Castellucci, C Keith and T Moore (2016), “The Bitcoin brain drain: a brief paper on the use and manhandle of bitcoin brain wallets”, in Financial Cryptography and Data Security, Lecture Notes in Computer Science.

Yuxing Huang, D, H Dharmdasani, S Meiklejohn, V Dave, C Grier, D McCoy, S Savage, N Weaver, A Snoeren and K Levchenko (2014), “Botcoin: Monetizing stolen cycles”, in Proceedings of the Network and Distributed System Security Symposium.

Endnotes

[1] The Bitcoin ecosystem includes the core network for propagating transactions, the blockchain, and many intermediaries such as currency exchanges, mining pools, and payment processors that facilitate trade.

[Two] Markus was primarily active in period Three, but he was also active a few days during periods 1,Two, and Four. He was not active on the same days as Willy, who was only active in period Four.

Price manipulation in the Bitcoin ecosystem, VOX, CEPR’s Policy Portal

VOX CEPR’s Policy Portal

Research-based policy analysis and commentary from leading economists

Price manipulation in the Bitcoin ecosystem

Neil Gandal, JT Hamrick, Tyler Moore, Tali Oberman twenty two June two thousand seventeen

The cryptocurrency Bitcoin has attracted widespread interest, in large part due to wild swings in its valuation. This column considers an earlier rise in the Bitcoin price to investigate what is driving the currency’s price spikes. The two thousand thirteen rise was caused by fraudulent trades taking place at the largest Bitcoin currency exchange at the time. This finding has implications for policymakers as they weigh what, if anything, to do about regulating cryptocurrencies in light of the record high Bitcoin valuation that many fear is a bubble.

Related

The digital currency Bitcoin was introduced in 2009. Bitcoin and the many other digital currencies are primarily online currencies. The key currencies are those based primarily on cryptography, and Bitcoin is the leading ‘cryptocurrency’.

Bitcoin has experienced a meteoric rise in popularity since its introduction. While digital currencies were proposed as early as the 1980s, Bitcoin was the very first to catch on. The total value of all Bitcoins in circulation reached $45 billion in June 2017. Its success has inspired scores of rivaling cryptocurrencies that go after a similar design. Bitcoin and most other cryptocurrencies do not require a central authority to validate and lodge transactions. Instead, these currencies use cryptography (and an internal incentive system) to control transactions, manage the supply, and prevent fraud. Payments are validated by a decentralised network. Once confirmed, all transactions are stored digitally and recorded in a public ‘blockchain’,’ which can be thought of as a distributed accounting system.

While Bitcoin’s algorithm provides safeguards against ‘counterfeiting’ of the currency, the eco-system is still vulnerable to theft. Users keep keys to their Bitcoins and make transactions with the help of wallets. Exchanges facilitate trade inbetween Bitcoins and fiat currencies, and also permit for storing Bitcoins. Bitcoins can be stolen through wallets or exchanges. Exchanges have been targeted more frequently than wallets because many wallets are located on users’ (local) computers, while exchanges frequently store customer deposits in their own (much larger) wallets.

The supply of most cryptocurrencies increases at a predetermined rate, and cannot be switched by any central authority. There are about fifteen million Bitcoins presently in circulation, with the ultimate number eventually reaching twenty one million. The motionless supply in the long run creates concerns about the deflationary aspect of the currency.

While Bitcoin shows superb promise to disrupt existing payment systems through innovations in its technical design, the Bitcoin ecosystem one has been the frequent target of attacks by financially motivated criminals. Due to the unregulated, decentralised environment in which they operate, cryptocurrencies are under constant threat of attack.

Bitcoin only recently became a subject of research in economics. However, the topic has been of interest for longer in computer science (for early work by computer scientists on incentives, see Babaioff et al. 2012, and Eyal and Sirer 2014.) Numerous researchers have conducted studies in order to document and combat threats such as Ponzi schemes, money laundering, mining botnets, and the theft of cryptocurrency wallets (Moeser et al. 2013, Vasek and Moore 2015, Vasek et al. 2016, Yuxing et al. 2014). Ron and Shamir (2013) attempt to identify suspicious trading activity by building a graph of Bitcoin transactions found in the public ledger. None of these papers can associate individual transactions with specific users of the currency exchanges.

In latest work, we display that the very first time Bitcoin reached an exchange rate of more than $1,000, the meteoric rise was driven by fraud (Gandal et al. 2017). We leverage a unique and very detailed dataset to examine suspicious trading activity that occurred over a ten-month period in two thousand thirteen on Mt. Gox, the leading Bitcoin currency exchange at the time. We very first quantify the extent of the suspicious/fraudulent trading activity and showcase that it constitutes a large fraction of trading on the days the activity occurred. We then showcase how this trading activity affected the exchange rates at Mt. Gox and other leading currency exchanges.

Figure 1 Bitcoin–US dollar exchange rate, with periods of suspicious activity shaded

While it was the superior currency exchange when Bitcoin very first shot to prominence in early 2013, behind the scenes, Tokyo-based Mt. Gox was in trouble. In addition to suffering from repeated denial-of-service attacks and Bitcoin thefts, two unauthorised traders were able to transact on the exchange without spending real money. In the very first case, a trader dubbed ‘Markus’ was credited with Bitcoins by duplicating previously finished transactions. In the 2nd case, a trader dubbed ‘Willy’ bought Bitcoins from traders by ‘crediting’ the sellers’ accounts with fiat currencies that, in many cases, could not be withdrawn. Figure one shows when these fraudulent traders were active, along with the Bitcoin–US dollar exchange rate. Most noteworthy is that Willy’s operation coincided with an unprecedented leap in the price of Bitcoin: from around $150 to over $1000. In early 2014, Mt. Gox collapsed, and the Bitcoin price fell with it. Only recently, in early 2017, has Bitcoin surpassed the levels of the earlier rise.

However, how do we know that the rise was caused by the fraudulent trades? Fortunately for us as researchers, the unauthorised trades did not take place every day. Table one shows the daily switch in the Bitcoin–US dollar exchange rate for various time periods on Mt. Gox. In the two quarters before unauthorised trading commenced, the daily price increase was, on average, positive but relatively puny: a $0.21 increase in the very first period and a $1 increase in the 2nd period. During the third quarter, when unauthorised trading embarked, the price rose by an average of $Three.15 on the seventeen days in which Markus traded, but fell on average by $0.51 on the seventy five days he did not trade. However, it is during the final quarter, when Willy began trading, that the difference became stark. On the fifty days in which Willy traded, the Bitcoin price rose by an average of $21.85. On the forty one days in which Willy did not make unauthorizsed purchases, the price fell by $0.88 on average. (Table one is very similar for the other leading exchanges as well.)

Table 1 Average daily switch in BTC/USD exchange rate as a function of fraudulent activity Two

In our total paper, we conduct a regression analysis to examine whether other factors such as the relatively numerous and varied attacks on the Mt. Gox exchange could explain the switch in the daily Bitcoin price, both at Mt. Gox and other leading exchanges (Gandal et al. 2017).

The analysis confirms that only Willy’s trading presence affected the price. The estimated coefficient (on the dummy variable for whether Willy was active) is virtually the same ($21.65) as in Table 1. We conclude that the suspicious trading activity of a single actor was the primary cause of the massive spike in the Bitcoin–US dollar exchange rate, in which the rate rose from around $150 to over $1,000 in just two months in late 2013. The fall was almost as precipitous: the Mt. Gox exchange folded due to insolvency in early 2014, and it has taken more than three years for Bitcoin to match the rise triggered by fraudulent transactions.

Why should we care about the Bitcoin manipulation that took place in 2013? After all, the Bitcoin ecosystem is not almost as significant as the Fresh York Stock Exchange. Nonetheless, latest trends indicate that Bitcoin is becoming an significant asset in the financial system.

Trading in cryptocurrency assets has exploded recently. In the case of Bitcoin, during the one year period ending in mid-June 2017, the market capitalisation enhanced massively from around $7 billion to $45 billion; that is an increase of over 500% in one year. The market cap of other cryptocurrencies surged by even more. In the one-year period ending in mid-May 2017, the market value of cryptocurrencies excluding Bitcoin surged from $1.7 billion to more than $29 billion; that is an increase of more than 1,900%. The markets for these other cryptocurrencies are very skinny and subject to manipulation. Given that we now know the Bitcoin price has been artificially inflated by unauthorised trades in the past, we must view the present rise with good caution, and not necessarily consider it a ‘healthy bubble’, as recently claimed in The Economist (2017).

As mainstream finance invests in cryptocurrency assets and as countries take steps toward legalising Bitcoin as a payment system (as Japan did in April 2017), it is significant to understand how susceptible cryptocurrency markets are to manipulation. We encourage the nascent cryptocurrency industry to work with regulators and researchers to share anonymised transaction data so that more confidence can be placed in the veracity of exchange rates.

References

Babaioff, M, S Dobzinski, S Oren and A Zohar (2012), “On bitcoin and crimson balloons” in Proceedings of the 13th ACM Conference on Electronic Commerce, pp. 56-73.

Eyal, I and E Sirer (2014), “Majority is not Enough: Bitcoin Mining is Vulnerable”, paper introduced at the Eighteenth International Conference on Financial Cryptography and Data Security, Barbados, 3-7 March.

Gandal, N, J Hamrick, T Moore and T Oberman (2017), “Price Manipulation in the Bitcoin Ecosystem,” CEPR Discussion Paper No. 12061.

Mooser, M, R Bohme and D Breuker (2013), “An inquiry into money laundering implements in the Bitcoin ecosystem”, in Proceedings of the Seventh APWG eCrime Re-searcher’s Summit, pp. 1-14.

Ron, D and A Shamir (2013), “Quantitative analysis of the utter Bitcoin transaction graph”, in Financial Cryptography and Data Security, Vol. Seven thousand eight hundred fifty nine of Lecture Notes in Computer Science, pp. 6-24.

Vasek, M and T Moore (2015), “There’s no free lunch, even using Bitcoin: Tracking the popularity and profits of virtual currency scams”, in R Bohme and T Okamoto (eds), Financial Cryptography and Data Security, volume eight thousand nine hundred seventy five of Lecture Notes in Computer Science, pp. 44-61.

Vasek, M, J Bonneau, R Castellucci, C Keith and T Moore (2016), “The Bitcoin brain drain: a brief paper on the use and manhandle of bitcoin brain wallets”, in Financial Cryptography and Data Security, Lecture Notes in Computer Science.

Yuxing Huang, D, H Dharmdasani, S Meiklejohn, V Dave, C Grier, D McCoy, S Savage, N Weaver, A Snoeren and K Levchenko (2014), “Botcoin: Monetizing stolen cycles”, in Proceedings of the Network and Distributed System Security Symposium.

Endnotes

[1] The Bitcoin ecosystem includes the core network for propagating transactions, the blockchain, and many intermediaries such as currency exchanges, mining pools, and payment processors that facilitate trade.

[Two] Markus was primarily active in period Trio, but he was also active a few days during periods 1,Two, and Four. He was not active on the same days as Willy, who was only active in period Four.

Price manipulation in the Bitcoin ecosystem, VOX, CEPR’s Policy Portal

VOX CEPR’s Policy Portal

Research-based policy analysis and commentary from leading economists

Price manipulation in the Bitcoin ecosystem

Neil Gandal, JT Hamrick, Tyler Moore, Tali Oberman twenty two June two thousand seventeen

The cryptocurrency Bitcoin has attracted widespread interest, in large part due to wild swings in its valuation. This column considers an earlier rise in the Bitcoin price to investigate what is driving the currency’s price spikes. The two thousand thirteen rise was caused by fraudulent trades taking place at the largest Bitcoin currency exchange at the time. This finding has implications for policymakers as they weigh what, if anything, to do about regulating cryptocurrencies in light of the record high Bitcoin valuation that many fear is a bubble.

Related

The digital currency Bitcoin was introduced in 2009. Bitcoin and the many other digital currencies are primarily online currencies. The key currencies are those based primarily on cryptography, and Bitcoin is the leading ‘cryptocurrency’.

Bitcoin has experienced a meteoric rise in popularity since its introduction. While digital currencies were proposed as early as the 1980s, Bitcoin was the very first to catch on. The total value of all Bitcoins in circulation reached $45 billion in June 2017. Its success has inspired scores of challenging cryptocurrencies that go after a similar design. Bitcoin and most other cryptocurrencies do not require a central authority to validate and lodge transactions. Instead, these currencies use cryptography (and an internal incentive system) to control transactions, manage the supply, and prevent fraud. Payments are validated by a decentralised network. Once confirmed, all transactions are stored digitally and recorded in a public ‘blockchain’,’ which can be thought of as a distributed accounting system.

While Bitcoin’s algorithm provides safeguards against ‘counterfeiting’ of the currency, the eco-system is still vulnerable to theft. Users keep keys to their Bitcoins and make transactions with the help of wallets. Exchanges facilitate trade inbetween Bitcoins and fiat currencies, and also permit for storing Bitcoins. Bitcoins can be stolen through wallets or exchanges. Exchanges have been targeted more frequently than wallets because many wallets are located on users’ (local) computers, while exchanges frequently store customer deposits in their own (much larger) wallets.

The supply of most cryptocurrencies increases at a predetermined rate, and cannot be switched by any central authority. There are about fifteen million Bitcoins presently in circulation, with the ultimate number eventually reaching twenty one million. The immovable supply in the long run creates concerns about the deflationary aspect of the currency.

While Bitcoin shows excellent promise to disrupt existing payment systems through innovations in its technical design, the Bitcoin ecosystem one has been the frequent target of attacks by financially motivated criminals. Due to the unregulated, decentralised environment in which they operate, cryptocurrencies are under constant threat of attack.

Bitcoin only recently became a subject of research in economics. However, the topic has been of interest for longer in computer science (for early work by computer scientists on incentives, see Babaioff et al. 2012, and Eyal and Sirer 2014.) Numerous researchers have conducted studies in order to document and combat threats such as Ponzi schemes, money laundering, mining botnets, and the theft of cryptocurrency wallets (Moeser et al. 2013, Vasek and Moore 2015, Vasek et al. 2016, Yuxing et al. 2014). Ron and Shamir (2013) attempt to identify suspicious trading activity by building a graph of Bitcoin transactions found in the public ledger. None of these papers can associate individual transactions with specific users of the currency exchanges.

In latest work, we showcase that the very first time Bitcoin reached an exchange rate of more than $1,000, the meteoric rise was driven by fraud (Gandal et al. 2017). We leverage a unique and very detailed dataset to examine suspicious trading activity that occurred over a ten-month period in two thousand thirteen on Mt. Gox, the leading Bitcoin currency exchange at the time. We very first quantify the extent of the suspicious/fraudulent trading activity and showcase that it constitutes a large fraction of trading on the days the activity occurred. We then showcase how this trading activity affected the exchange rates at Mt. Gox and other leading currency exchanges.

Figure 1 Bitcoin–US dollar exchange rate, with periods of suspicious activity shaded

While it was the superior currency exchange when Bitcoin very first shot to prominence in early 2013, behind the scenes, Tokyo-based Mt. Gox was in trouble. In addition to suffering from repeated denial-of-service attacks and Bitcoin thefts, two unauthorised traders were able to transact on the exchange without spending real money. In the very first case, a trader dubbed ‘Markus’ was credited with Bitcoins by duplicating previously ended transactions. In the 2nd case, a trader dubbed ‘Willy’ bought Bitcoins from traders by ‘crediting’ the sellers’ accounts with fiat currencies that, in many cases, could not be withdrawn. Figure one shows when these fraudulent traders were active, along with the Bitcoin–US dollar exchange rate. Most noteworthy is that Willy’s operation coincided with an unprecedented hop in the price of Bitcoin: from around $150 to over $1000. In early 2014, Mt. Gox collapsed, and the Bitcoin price fell with it. Only recently, in early 2017, has Bitcoin surpassed the levels of the earlier rise.

However, how do we know that the rise was caused by the fraudulent trades? Fortunately for us as researchers, the unauthorised trades did not take place every day. Table one shows the daily switch in the Bitcoin–US dollar exchange rate for various time periods on Mt. Gox. In the two quarters before unauthorised trading commenced, the daily price increase was, on average, positive but relatively puny: a $0.21 increase in the very first period and a $1 increase in the 2nd period. During the third quarter, when unauthorised trading began, the price rose by an average of $Three.15 on the seventeen days in which Markus traded, but fell on average by $0.51 on the seventy five days he did not trade. However, it is during the final quarter, when Willy began trading, that the difference became stark. On the fifty days in which Willy traded, the Bitcoin price rose by an average of $21.85. On the forty one days in which Willy did not make unauthorizsed purchases, the price fell by $0.88 on average. (Table one is very similar for the other leading exchanges as well.)

Table 1 Average daily switch in BTC/USD exchange rate as a function of fraudulent activity Two

In our utter paper, we conduct a regression analysis to examine whether other factors such as the relatively numerous and varied attacks on the Mt. Gox exchange could explain the switch in the daily Bitcoin price, both at Mt. Gox and other leading exchanges (Gandal et al. 2017).

The analysis confirms that only Willy’s trading presence affected the price. The estimated coefficient (on the dummy variable for whether Willy was active) is virtually the same ($21.65) as in Table 1. We conclude that the suspicious trading activity of a single actor was the primary cause of the massive spike in the Bitcoin–US dollar exchange rate, in which the rate rose from around $150 to over $1,000 in just two months in late 2013. The fall was almost as precipitous: the Mt. Gox exchange folded due to insolvency in early 2014, and it has taken more than three years for Bitcoin to match the rise triggered by fraudulent transactions.

Why should we care about the Bitcoin manipulation that took place in 2013? After all, the Bitcoin ecosystem is not almost as significant as the Fresh York Stock Exchange. Nonetheless, latest trends indicate that Bitcoin is becoming an significant asset in the financial system.

Trading in cryptocurrency assets has exploded recently. In the case of Bitcoin, during the one year period ending in mid-June 2017, the market capitalisation enhanced massively from around $7 billion to $45 billion; that is an increase of over 500% in one year. The market cap of other cryptocurrencies surged by even more. In the one-year period ending in mid-May 2017, the market value of cryptocurrencies excluding Bitcoin surged from $1.7 billion to more than $29 billion; that is an increase of more than 1,900%. The markets for these other cryptocurrencies are very skinny and subject to manipulation. Given that we now know the Bitcoin price has been artificially inflated by unauthorised trades in the past, we must view the present rise with good caution, and not necessarily consider it a ‘healthy bubble’, as recently claimed in The Economist (2017).

As mainstream finance invests in cryptocurrency assets and as countries take steps toward legalising Bitcoin as a payment system (as Japan did in April 2017), it is significant to understand how susceptible cryptocurrency markets are to manipulation. We encourage the nascent cryptocurrency industry to work with regulators and researchers to share anonymised transaction data so that more confidence can be placed in the veracity of exchange rates.

References

Babaioff, M, S Dobzinski, S Oren and A Zohar (2012), “On bitcoin and crimson balloons” in Proceedings of the 13th ACM Conference on Electronic Commerce, pp. 56-73.

Eyal, I and E Sirer (2014), “Majority is not Enough: Bitcoin Mining is Vulnerable”, paper introduced at the Eighteenth International Conference on Financial Cryptography and Data Security, Barbados, 3-7 March.

Gandal, N, J Hamrick, T Moore and T Oberman (2017), “Price Manipulation in the Bitcoin Ecosystem,” CEPR Discussion Paper No. 12061.

Mooser, M, R Bohme and D Breuker (2013), “An inquiry into money laundering implements in the Bitcoin ecosystem”, in Proceedings of the Seventh APWG eCrime Re-searcher’s Summit, pp. 1-14.

Ron, D and A Shamir (2013), “Quantitative analysis of the total Bitcoin transaction graph”, in Financial Cryptography and Data Security, Vol. Seven thousand eight hundred fifty nine of Lecture Notes in Computer Science, pp. 6-24.

Vasek, M and T Moore (2015), “There’s no free lunch, even using Bitcoin: Tracking the popularity and profits of virtual currency scams”, in R Bohme and T Okamoto (eds), Financial Cryptography and Data Security, volume eight thousand nine hundred seventy five of Lecture Notes in Computer Science, pp. 44-61.

Vasek, M, J Bonneau, R Castellucci, C Keith and T Moore (2016), “The Bitcoin brain drain: a brief paper on the use and manhandle of bitcoin brain wallets”, in Financial Cryptography and Data Security, Lecture Notes in Computer Science.

Yuxing Huang, D, H Dharmdasani, S Meiklejohn, V Dave, C Grier, D McCoy, S Savage, N Weaver, A Snoeren and K Levchenko (2014), “Botcoin: Monetizing stolen cycles”, in Proceedings of the Network and Distributed System Security Symposium.

Endnotes

[1] The Bitcoin ecosystem includes the core network for propagating transactions, the blockchain, and many intermediaries such as currency exchanges, mining pools, and payment processors that facilitate trade.

[Two] Markus was primarily active in period Trio, but he was also active a few days during periods 1,Two, and Four. He was not active on the same days as Willy, who was only active in period Four.

Price manipulation in the Bitcoin ecosystem, VOX, CEPR’s Policy Portal

VOX CEPR’s Policy Portal

Research-based policy analysis and commentary from leading economists

Price manipulation in the Bitcoin ecosystem

Neil Gandal, JT Hamrick, Tyler Moore, Tali Oberman twenty two June two thousand seventeen

The cryptocurrency Bitcoin has attracted widespread interest, in large part due to wild swings in its valuation. This column considers an earlier rise in the Bitcoin price to investigate what is driving the currency’s price spikes. The two thousand thirteen rise was caused by fraudulent trades taking place at the largest Bitcoin currency exchange at the time. This finding has implications for policymakers as they weigh what, if anything, to do about regulating cryptocurrencies in light of the record high Bitcoin valuation that many fear is a bubble.

Related

The digital currency Bitcoin was introduced in 2009. Bitcoin and the many other digital currencies are primarily online currencies. The key currencies are those based primarily on cryptography, and Bitcoin is the leading ‘cryptocurrency’.

Bitcoin has experienced a meteoric rise in popularity since its introduction. While digital currencies were proposed as early as the 1980s, Bitcoin was the very first to catch on. The total value of all Bitcoins in circulation reached $45 billion in June 2017. Its success has inspired scores of rivaling cryptocurrencies that go after a similar design. Bitcoin and most other cryptocurrencies do not require a central authority to validate and lodge transactions. Instead, these currencies use cryptography (and an internal incentive system) to control transactions, manage the supply, and prevent fraud. Payments are validated by a decentralised network. Once confirmed, all transactions are stored digitally and recorded in a public ‘blockchain’,’ which can be thought of as a distributed accounting system.

While Bitcoin’s algorithm provides safeguards against ‘counterfeiting’ of the currency, the eco-system is still vulnerable to theft. Users keep keys to their Bitcoins and make transactions with the help of wallets. Exchanges facilitate trade inbetween Bitcoins and fiat currencies, and also permit for storing Bitcoins. Bitcoins can be stolen through wallets or exchanges. Exchanges have been targeted more frequently than wallets because many wallets are located on users’ (local) computers, while exchanges frequently store customer deposits in their own (much larger) wallets.

The supply of most cryptocurrencies increases at a predetermined rate, and cannot be switched by any central authority. There are about fifteen million Bitcoins presently in circulation, with the ultimate number eventually reaching twenty one million. The motionless supply in the long run creates concerns about the deflationary aspect of the currency.

While Bitcoin shows excellent promise to disrupt existing payment systems through innovations in its technical design, the Bitcoin ecosystem one has been the frequent target of attacks by financially motivated criminals. Due to the unregulated, decentralised environment in which they operate, cryptocurrencies are under constant threat of attack.

Bitcoin only recently became a subject of research in economics. However, the topic has been of interest for longer in computer science (for early work by computer scientists on incentives, see Babaioff et al. 2012, and Eyal and Sirer 2014.) Numerous researchers have conducted studies in order to document and combat threats such as Ponzi schemes, money laundering, mining botnets, and the theft of cryptocurrency wallets (Moeser et al. 2013, Vasek and Moore 2015, Vasek et al. 2016, Yuxing et al. 2014). Ron and Shamir (2013) attempt to identify suspicious trading activity by building a graph of Bitcoin transactions found in the public ledger. None of these papers can associate individual transactions with specific users of the currency exchanges.

In latest work, we display that the very first time Bitcoin reached an exchange rate of more than $1,000, the meteoric rise was driven by fraud (Gandal et al. 2017). We leverage a unique and very detailed dataset to examine suspicious trading activity that occurred over a ten-month period in two thousand thirteen on Mt. Gox, the leading Bitcoin currency exchange at the time. We very first quantify the extent of the suspicious/fraudulent trading activity and showcase that it constitutes a large fraction of trading on the days the activity occurred. We then display how this trading activity affected the exchange rates at Mt. Gox and other leading currency exchanges.

Figure 1 Bitcoin–US dollar exchange rate, with periods of suspicious activity shaded

While it was the superior currency exchange when Bitcoin very first shot to prominence in early 2013, behind the scenes, Tokyo-based Mt. Gox was in trouble. In addition to suffering from repeated denial-of-service attacks and Bitcoin thefts, two unauthorised traders were able to transact on the exchange without spending real money. In the very first case, a trader dubbed ‘Markus’ was credited with Bitcoins by duplicating previously ended transactions. In the 2nd case, a trader dubbed ‘Willy’ bought Bitcoins from traders by ‘crediting’ the sellers’ accounts with fiat currencies that, in many cases, could not be withdrawn. Figure one shows when these fraudulent traders were active, along with the Bitcoin–US dollar exchange rate. Most noteworthy is that Willy’s operation coincided with an unprecedented hop in the price of Bitcoin: from around $150 to over $1000. In early 2014, Mt. Gox collapsed, and the Bitcoin price fell with it. Only recently, in early 2017, has Bitcoin surpassed the levels of the earlier rise.

However, how do we know that the rise was caused by the fraudulent trades? Fortunately for us as researchers, the unauthorised trades did not take place every day. Table one shows the daily switch in the Bitcoin–US dollar exchange rate for various time periods on Mt. Gox. In the two quarters before unauthorised trading commenced, the daily price increase was, on average, positive but relatively puny: a $0.21 increase in the very first period and a $1 increase in the 2nd period. During the third quarter, when unauthorised trading commenced, the price rose by an average of $Trio.15 on the seventeen days in which Markus traded, but fell on average by $0.51 on the seventy five days he did not trade. However, it is during the final quarter, when Willy began trading, that the difference became stark. On the fifty days in which Willy traded, the Bitcoin price rose by an average of $21.85. On the forty one days in which Willy did not make unauthorizsed purchases, the price fell by $0.88 on average. (Table one is very similar for the other leading exchanges as well.)

Table 1 Average daily switch in BTC/USD exchange rate as a function of fraudulent activity Two

In our utter paper, we conduct a regression analysis to examine whether other factors such as the relatively numerous and varied attacks on the Mt. Gox exchange could explain the switch in the daily Bitcoin price, both at Mt. Gox and other leading exchanges (Gandal et al. 2017).

The analysis confirms that only Willy’s trading presence affected the price. The estimated coefficient (on the dummy variable for whether Willy was active) is virtually the same ($21.65) as in Table 1. We conclude that the suspicious trading activity of a single actor was the primary cause of the massive spike in the Bitcoin–US dollar exchange rate, in which the rate rose from around $150 to over $1,000 in just two months in late 2013. The fall was almost as precipitous: the Mt. Gox exchange folded due to insolvency in early 2014, and it has taken more than three years for Bitcoin to match the rise triggered by fraudulent transactions.

Why should we care about the Bitcoin manipulation that took place in 2013? After all, the Bitcoin ecosystem is not almost as significant as the Fresh York Stock Exchange. Nonetheless, latest trends indicate that Bitcoin is becoming an significant asset in the financial system.

Trading in cryptocurrency assets has exploded recently. In the case of Bitcoin, during the one year period ending in mid-June 2017, the market capitalisation enlargened massively from around $7 billion to $45 billion; that is an increase of over 500% in one year. The market cap of other cryptocurrencies surged by even more. In the one-year period ending in mid-May 2017, the market value of cryptocurrencies excluding Bitcoin surged from $1.7 billion to more than $29 billion; that is an increase of more than 1,900%. The markets for these other cryptocurrencies are very lean and subject to manipulation. Given that we now know the Bitcoin price has been artificially inflated by unauthorised trades in the past, we must view the present rise with fine caution, and not necessarily consider it a ‘healthy bubble’, as recently claimed in The Economist (2017).

As mainstream finance invests in cryptocurrency assets and as countries take steps toward legalising Bitcoin as a payment system (as Japan did in April 2017), it is significant to understand how susceptible cryptocurrency markets are to manipulation. We encourage the nascent cryptocurrency industry to work with regulators and researchers to share anonymised transaction data so that more confidence can be placed in the veracity of exchange rates.

References

Babaioff, M, S Dobzinski, S Oren and A Zohar (2012), “On bitcoin and crimson balloons” in Proceedings of the 13th ACM Conference on Electronic Commerce, pp. 56-73.

Eyal, I and E Sirer (2014), “Majority is not Enough: Bitcoin Mining is Vulnerable”, paper introduced at the Eighteenth International Conference on Financial Cryptography and Data Security, Barbados, 3-7 March.

Gandal, N, J Hamrick, T Moore and T Oberman (2017), “Price Manipulation in the Bitcoin Ecosystem,” CEPR Discussion Paper No. 12061.

Mooser, M, R Bohme and D Breuker (2013), “An inquiry into money laundering instruments in the Bitcoin ecosystem”, in Proceedings of the Seventh APWG eCrime Re-searcher’s Summit, pp. 1-14.

Ron, D and A Shamir (2013), “Quantitative analysis of the utter Bitcoin transaction graph”, in Financial Cryptography and Data Security, Vol. Seven thousand eight hundred fifty nine of Lecture Notes in Computer Science, pp. 6-24.

Vasek, M and T Moore (2015), “There’s no free lunch, even using Bitcoin: Tracking the popularity and profits of virtual currency scams”, in R Bohme and T Okamoto (eds), Financial Cryptography and Data Security, volume eight thousand nine hundred seventy five of Lecture Notes in Computer Science, pp. 44-61.

Vasek, M, J Bonneau, R Castellucci, C Keith and T Moore (2016), “The Bitcoin brain drain: a brief paper on the use and manhandle of bitcoin brain wallets”, in Financial Cryptography and Data Security, Lecture Notes in Computer Science.

Yuxing Huang, D, H Dharmdasani, S Meiklejohn, V Dave, C Grier, D McCoy, S Savage, N Weaver, A Snoeren and K Levchenko (2014), “Botcoin: Monetizing stolen cycles”, in Proceedings of the Network and Distributed System Security Symposium.

Endnotes

[1] The Bitcoin ecosystem includes the core network for propagating transactions, the blockchain, and many intermediaries such as currency exchanges, mining pools, and payment processors that facilitate trade.

[Two] Markus was primarily active in period Trio, but he was also active a few days during periods 1,Two, and Four. He was not active on the same days as Willy, who was only active in period Four.

Price manipulation in the Bitcoin ecosystem, VOX, CEPR’s Policy Portal

VOX CEPR’s Policy Portal

Research-based policy analysis and commentary from leading economists

Price manipulation in the Bitcoin ecosystem

Neil Gandal, JT Hamrick, Tyler Moore, Tali Oberman twenty two June two thousand seventeen

The cryptocurrency Bitcoin has attracted widespread interest, in large part due to wild swings in its valuation. This column considers an earlier rise in the Bitcoin price to investigate what is driving the currency’s price spikes. The two thousand thirteen rise was caused by fraudulent trades taking place at the largest Bitcoin currency exchange at the time. This finding has implications for policymakers as they weigh what, if anything, to do about regulating cryptocurrencies in light of the record high Bitcoin valuation that many fear is a bubble.

Related

The digital currency Bitcoin was introduced in 2009. Bitcoin and the many other digital currencies are primarily online currencies. The key currencies are those based primarily on cryptography, and Bitcoin is the leading ‘cryptocurrency’.

Bitcoin has experienced a meteoric rise in popularity since its introduction. While digital currencies were proposed as early as the 1980s, Bitcoin was the very first to catch on. The total value of all Bitcoins in circulation reached $45 billion in June 2017. Its success has inspired scores of challenging cryptocurrencies that go after a similar design. Bitcoin and most other cryptocurrencies do not require a central authority to validate and lodge transactions. Instead, these currencies use cryptography (and an internal incentive system) to control transactions, manage the supply, and prevent fraud. Payments are validated by a decentralised network. Once confirmed, all transactions are stored digitally and recorded in a public ‘blockchain’,’ which can be thought of as a distributed accounting system.

While Bitcoin’s algorithm provides safeguards against ‘counterfeiting’ of the currency, the eco-system is still vulnerable to theft. Users keep keys to their Bitcoins and make transactions with the help of wallets. Exchanges facilitate trade inbetween Bitcoins and fiat currencies, and also permit for storing Bitcoins. Bitcoins can be stolen through wallets or exchanges. Exchanges have been targeted more frequently than wallets because many wallets are located on users’ (local) computers, while exchanges frequently store customer deposits in their own (much larger) wallets.

The supply of most cryptocurrencies increases at a predetermined rate, and cannot be switched by any central authority. There are about fifteen million Bitcoins presently in circulation, with the ultimate number eventually reaching twenty one million. The immovable supply in the long run creates concerns about the deflationary aspect of the currency.

While Bitcoin shows excellent promise to disrupt existing payment systems through innovations in its technical design, the Bitcoin ecosystem one has been the frequent target of attacks by financially motivated criminals. Due to the unregulated, decentralised environment in which they operate, cryptocurrencies are under constant threat of attack.

Bitcoin only recently became a subject of research in economics. However, the topic has been of interest for longer in computer science (for early work by computer scientists on incentives, see Babaioff et al. 2012, and Eyal and Sirer 2014.) Numerous researchers have conducted studies in order to document and combat threats such as Ponzi schemes, money laundering, mining botnets, and the theft of cryptocurrency wallets (Moeser et al. 2013, Vasek and Moore 2015, Vasek et al. 2016, Yuxing et al. 2014). Ron and Shamir (2013) attempt to identify suspicious trading activity by building a graph of Bitcoin transactions found in the public ledger. None of these papers can associate individual transactions with specific users of the currency exchanges.

In latest work, we demonstrate that the very first time Bitcoin reached an exchange rate of more than $1,000, the meteoric rise was driven by fraud (Gandal et al. 2017). We leverage a unique and very detailed dataset to examine suspicious trading activity that occurred over a ten-month period in two thousand thirteen on Mt. Gox, the leading Bitcoin currency exchange at the time. We very first quantify the extent of the suspicious/fraudulent trading activity and display that it constitutes a large fraction of trading on the days the activity occurred. We then demonstrate how this trading activity affected the exchange rates at Mt. Gox and other leading currency exchanges.

Figure 1 Bitcoin–US dollar exchange rate, with periods of suspicious activity shaded

While it was the superior currency exchange when Bitcoin very first shot to prominence in early 2013, behind the scenes, Tokyo-based Mt. Gox was in trouble. In addition to suffering from repeated denial-of-service attacks and Bitcoin thefts, two unauthorised traders were able to transact on the exchange without spending real money. In the very first case, a trader dubbed ‘Markus’ was credited with Bitcoins by duplicating previously finished transactions. In the 2nd case, a trader dubbed ‘Willy’ bought Bitcoins from traders by ‘crediting’ the sellers’ accounts with fiat currencies that, in many cases, could not be withdrawn. Figure one shows when these fraudulent traders were active, along with the Bitcoin–US dollar exchange rate. Most noteworthy is that Willy’s operation coincided with an unprecedented hop in the price of Bitcoin: from around $150 to over $1000. In early 2014, Mt. Gox collapsed, and the Bitcoin price fell with it. Only recently, in early 2017, has Bitcoin surpassed the levels of the earlier rise.

However, how do we know that the rise was caused by the fraudulent trades? Fortunately for us as researchers, the unauthorised trades did not take place every day. Table one shows the daily switch in the Bitcoin–US dollar exchange rate for various time periods on Mt. Gox. In the two quarters before unauthorised trading commenced, the daily price increase was, on average, positive but relatively puny: a $0.21 increase in the very first period and a $1 increase in the 2nd period. During the third quarter, when unauthorised trading commenced, the price rose by an average of $Three.15 on the seventeen days in which Markus traded, but fell on average by $0.51 on the seventy five days he did not trade. However, it is during the final quarter, when Willy began trading, that the difference became stark. On the fifty days in which Willy traded, the Bitcoin price rose by an average of $21.85. On the forty one days in which Willy did not make unauthorizsed purchases, the price fell by $0.88 on average. (Table one is very similar for the other leading exchanges as well.)

Table 1 Average daily switch in BTC/USD exchange rate as a function of fraudulent activity Two

In our total paper, we conduct a regression analysis to examine whether other factors such as the relatively numerous and varied attacks on the Mt. Gox exchange could explain the switch in the daily Bitcoin price, both at Mt. Gox and other leading exchanges (Gandal et al. 2017).

The analysis confirms that only Willy’s trading presence affected the price. The estimated coefficient (on the dummy variable for whether Willy was active) is virtually the same ($21.65) as in Table 1. We conclude that the suspicious trading activity of a single actor was the primary cause of the massive spike in the Bitcoin–US dollar exchange rate, in which the rate rose from around $150 to over $1,000 in just two months in late 2013. The fall was almost as precipitous: the Mt. Gox exchange folded due to insolvency in early 2014, and it has taken more than three years for Bitcoin to match the rise triggered by fraudulent transactions.

Why should we care about the Bitcoin manipulation that took place in 2013? After all, the Bitcoin ecosystem is not almost as significant as the Fresh York Stock Exchange. Nonetheless, latest trends indicate that Bitcoin is becoming an significant asset in the financial system.

Trading in cryptocurrency assets has exploded recently. In the case of Bitcoin, during the one year period ending in mid-June 2017, the market capitalisation enlargened massively from around $7 billion to $45 billion; that is an increase of over 500% in one year. The market cap of other cryptocurrencies surged by even more. In the one-year period ending in mid-May 2017, the market value of cryptocurrencies excluding Bitcoin surged from $1.7 billion to more than $29 billion; that is an increase of more than 1,900%. The markets for these other cryptocurrencies are very skinny and subject to manipulation. Given that we now know the Bitcoin price has been artificially inflated by unauthorised trades in the past, we must view the present rise with excellent caution, and not necessarily consider it a ‘healthy bubble’, as recently claimed in The Economist (2017).

As mainstream finance invests in cryptocurrency assets and as countries take steps toward legalising Bitcoin as a payment system (as Japan did in April 2017), it is significant to understand how susceptible cryptocurrency markets are to manipulation. We encourage the nascent cryptocurrency industry to work with regulators and researchers to share anonymised transaction data so that more confidence can be placed in the veracity of exchange rates.

References

Babaioff, M, S Dobzinski, S Oren and A Zohar (2012), “On bitcoin and crimson balloons” in Proceedings of the 13th ACM Conference on Electronic Commerce, pp. 56-73.

Eyal, I and E Sirer (2014), “Majority is not Enough: Bitcoin Mining is Vulnerable”, paper introduced at the Eighteenth International Conference on Financial Cryptography and Data Security, Barbados, 3-7 March.

Gandal, N, J Hamrick, T Moore and T Oberman (2017), “Price Manipulation in the Bitcoin Ecosystem,” CEPR Discussion Paper No. 12061.

Mooser, M, R Bohme and D Breuker (2013), “An inquiry into money laundering implements in the Bitcoin ecosystem”, in Proceedings of the Seventh APWG eCrime Re-searcher’s Summit, pp. 1-14.

Ron, D and A Shamir (2013), “Quantitative analysis of the total Bitcoin transaction graph”, in Financial Cryptography and Data Security, Vol. Seven thousand eight hundred fifty nine of Lecture Notes in Computer Science, pp. 6-24.

Vasek, M and T Moore (2015), “There’s no free lunch, even using Bitcoin: Tracking the popularity and profits of virtual currency scams”, in R Bohme and T Okamoto (eds), Financial Cryptography and Data Security, volume eight thousand nine hundred seventy five of Lecture Notes in Computer Science, pp. 44-61.

Vasek, M, J Bonneau, R Castellucci, C Keith and T Moore (2016), “The Bitcoin brain drain: a brief paper on the use and manhandle of bitcoin brain wallets”, in Financial Cryptography and Data Security, Lecture Notes in Computer Science.

Yuxing Huang, D, H Dharmdasani, S Meiklejohn, V Dave, C Grier, D McCoy, S Savage, N Weaver, A Snoeren and K Levchenko (2014), “Botcoin: Monetizing stolen cycles”, in Proceedings of the Network and Distributed System Security Symposium.

Endnotes

[1] The Bitcoin ecosystem includes the core network for propagating transactions, the blockchain, and many intermediaries such as currency exchanges, mining pools, and payment processors that facilitate trade.

[Two] Markus was primarily active in period Three, but he was also active a few days during periods 1,Two, and Four. He was not active on the same days as Willy, who was only active in period Four.

Price manipulation in the Bitcoin ecosystem, VOX, CEPR’s Policy Portal

VOX CEPR’s Policy Portal

Research-based policy analysis and commentary from leading economists

Price manipulation in the Bitcoin ecosystem

Neil Gandal, JT Hamrick, Tyler Moore, Tali Oberman twenty two June two thousand seventeen

The cryptocurrency Bitcoin has attracted widespread interest, in large part due to wild swings in its valuation. This column considers an earlier rise in the Bitcoin price to investigate what is driving the currency’s price spikes. The two thousand thirteen rise was caused by fraudulent trades taking place at the largest Bitcoin currency exchange at the time. This finding has implications for policymakers as they weigh what, if anything, to do about regulating cryptocurrencies in light of the record high Bitcoin valuation that many fear is a bubble.

Related

The digital currency Bitcoin was introduced in 2009. Bitcoin and the many other digital currencies are primarily online currencies. The key currencies are those based primarily on cryptography, and Bitcoin is the leading ‘cryptocurrency’.

Bitcoin has experienced a meteoric rise in popularity since its introduction. While digital currencies were proposed as early as the 1980s, Bitcoin was the very first to catch on. The total value of all Bitcoins in circulation reached $45 billion in June 2017. Its success has inspired scores of rivaling cryptocurrencies that go after a similar design. Bitcoin and most other cryptocurrencies do not require a central authority to validate and lodge transactions. Instead, these currencies use cryptography (and an internal incentive system) to control transactions, manage the supply, and prevent fraud. Payments are validated by a decentralised network. Once confirmed, all transactions are stored digitally and recorded in a public ‘blockchain’,’ which can be thought of as a distributed accounting system.

While Bitcoin’s algorithm provides safeguards against ‘counterfeiting’ of the currency, the eco-system is still vulnerable to theft. Users keep keys to their Bitcoins and make transactions with the help of wallets. Exchanges facilitate trade inbetween Bitcoins and fiat currencies, and also permit for storing Bitcoins. Bitcoins can be stolen through wallets or exchanges. Exchanges have been targeted more frequently than wallets because many wallets are located on users’ (local) computers, while exchanges frequently store customer deposits in their own (much larger) wallets.

The supply of most cryptocurrencies increases at a predetermined rate, and cannot be switched by any central authority. There are about fifteen million Bitcoins presently in circulation, with the ultimate number eventually reaching twenty one million. The stationary supply in the long run creates concerns about the deflationary aspect of the currency.

While Bitcoin shows superb promise to disrupt existing payment systems through innovations in its technical design, the Bitcoin ecosystem one has been the frequent target of attacks by financially motivated criminals. Due to the unregulated, decentralised environment in which they operate, cryptocurrencies are under constant threat of attack.

Bitcoin only recently became a subject of research in economics. However, the topic has been of interest for longer in computer science (for early work by computer scientists on incentives, see Babaioff et al. 2012, and Eyal and Sirer 2014.) Numerous researchers have conducted studies in order to document and combat threats such as Ponzi schemes, money laundering, mining botnets, and the theft of cryptocurrency wallets (Moeser et al. 2013, Vasek and Moore 2015, Vasek et al. 2016, Yuxing et al. 2014). Ron and Shamir (2013) attempt to identify suspicious trading activity by building a graph of Bitcoin transactions found in the public ledger. None of these papers can associate individual transactions with specific users of the currency exchanges.

In latest work, we demonstrate that the very first time Bitcoin reached an exchange rate of more than $1,000, the meteoric rise was driven by fraud (Gandal et al. 2017). We leverage a unique and very detailed dataset to examine suspicious trading activity that occurred over a ten-month period in two thousand thirteen on Mt. Gox, the leading Bitcoin currency exchange at the time. We very first quantify the extent of the suspicious/fraudulent trading activity and display that it constitutes a large fraction of trading on the days the activity occurred. We then demonstrate how this trading activity affected the exchange rates at Mt. Gox and other leading currency exchanges.

Figure 1 Bitcoin–US dollar exchange rate, with periods of suspicious activity shaded

While it was the superior currency exchange when Bitcoin very first shot to prominence in early 2013, behind the scenes, Tokyo-based Mt. Gox was in trouble. In addition to suffering from repeated denial-of-service attacks and Bitcoin thefts, two unauthorised traders were able to transact on the exchange without spending real money. In the very first case, a trader dubbed ‘Markus’ was credited with Bitcoins by duplicating previously ended transactions. In the 2nd case, a trader dubbed ‘Willy’ bought Bitcoins from traders by ‘crediting’ the sellers’ accounts with fiat currencies that, in many cases, could not be withdrawn. Figure one shows when these fraudulent traders were active, along with the Bitcoin–US dollar exchange rate. Most noteworthy is that Willy’s operation coincided with an unprecedented leap in the price of Bitcoin: from around $150 to over $1000. In early 2014, Mt. Gox collapsed, and the Bitcoin price fell with it. Only recently, in early 2017, has Bitcoin surpassed the levels of the earlier rise.

However, how do we know that the rise was caused by the fraudulent trades? Fortunately for us as researchers, the unauthorised trades did not take place every day. Table one shows the daily switch in the Bitcoin–US dollar exchange rate for various time periods on Mt. Gox. In the two quarters before unauthorised trading commenced, the daily price increase was, on average, positive but relatively petite: a $0.21 increase in the very first period and a $1 increase in the 2nd period. During the third quarter, when unauthorised trading began, the price rose by an average of $Three.15 on the seventeen days in which Markus traded, but fell on average by $0.51 on the seventy five days he did not trade. However, it is during the final quarter, when Willy began trading, that the difference became stark. On the fifty days in which Willy traded, the Bitcoin price rose by an average of $21.85. On the forty one days in which Willy did not make unauthorizsed purchases, the price fell by $0.88 on average. (Table one is very similar for the other leading exchanges as well.)

Table 1 Average daily switch in BTC/USD exchange rate as a function of fraudulent activity Two

In our total paper, we conduct a regression analysis to examine whether other factors such as the relatively numerous and varied attacks on the Mt. Gox exchange could explain the switch in the daily Bitcoin price, both at Mt. Gox and other leading exchanges (Gandal et al. 2017).

The analysis confirms that only Willy’s trading presence affected the price. The estimated coefficient (on the dummy variable for whether Willy was active) is virtually the same ($21.65) as in Table 1. We conclude that the suspicious trading activity of a single actor was the primary cause of the massive spike in the Bitcoin–US dollar exchange rate, in which the rate rose from around $150 to over $1,000 in just two months in late 2013. The fall was almost as precipitous: the Mt. Gox exchange folded due to insolvency in early 2014, and it has taken more than three years for Bitcoin to match the rise triggered by fraudulent transactions.

Why should we care about the Bitcoin manipulation that took place in 2013? After all, the Bitcoin ecosystem is not almost as significant as the Fresh York Stock Exchange. Nonetheless, latest trends indicate that Bitcoin is becoming an significant asset in the financial system.

Trading in cryptocurrency assets has exploded recently. In the case of Bitcoin, during the one year period ending in mid-June 2017, the market capitalisation enhanced massively from around $7 billion to $45 billion; that is an increase of over 500% in one year. The market cap of other cryptocurrencies surged by even more. In the one-year period ending in mid-May 2017, the market value of cryptocurrencies excluding Bitcoin surged from $1.7 billion to more than $29 billion; that is an increase of more than 1,900%. The markets for these other cryptocurrencies are very skinny and subject to manipulation. Given that we now know the Bitcoin price has been artificially inflated by unauthorised trades in the past, we must view the present rise with good caution, and not necessarily consider it a ‘healthy bubble’, as recently claimed in The Economist (2017).

As mainstream finance invests in cryptocurrency assets and as countries take steps toward legalising Bitcoin as a payment system (as Japan did in April 2017), it is significant to understand how susceptible cryptocurrency markets are to manipulation. We encourage the nascent cryptocurrency industry to work with regulators and researchers to share anonymised transaction data so that more confidence can be placed in the veracity of exchange rates.

References

Babaioff, M, S Dobzinski, S Oren and A Zohar (2012), “On bitcoin and crimson balloons” in Proceedings of the 13th ACM Conference on Electronic Commerce, pp. 56-73.

Eyal, I and E Sirer (2014), “Majority is not Enough: Bitcoin Mining is Vulnerable”, paper introduced at the Eighteenth International Conference on Financial Cryptography and Data Security, Barbados, 3-7 March.

Gandal, N, J Hamrick, T Moore and T Oberman (2017), “Price Manipulation in the Bitcoin Ecosystem,” CEPR Discussion Paper No. 12061.

Mooser, M, R Bohme and D Breuker (2013), “An inquiry into money laundering instruments in the Bitcoin ecosystem”, in Proceedings of the Seventh APWG eCrime Re-searcher’s Summit, pp. 1-14.

Ron, D and A Shamir (2013), “Quantitative analysis of the total Bitcoin transaction graph”, in Financial Cryptography and Data Security, Vol. Seven thousand eight hundred fifty nine of Lecture Notes in Computer Science, pp. 6-24.

Vasek, M and T Moore (2015), “There’s no free lunch, even using Bitcoin: Tracking the popularity and profits of virtual currency scams”, in R Bohme and T Okamoto (eds), Financial Cryptography and Data Security, volume eight thousand nine hundred seventy five of Lecture Notes in Computer Science, pp. 44-61.

Vasek, M, J Bonneau, R Castellucci, C Keith and T Moore (2016), “The Bitcoin brain drain: a brief paper on the use and manhandle of bitcoin brain wallets”, in Financial Cryptography and Data Security, Lecture Notes in Computer Science.

Yuxing Huang, D, H Dharmdasani, S Meiklejohn, V Dave, C Grier, D McCoy, S Savage, N Weaver, A Snoeren and K Levchenko (2014), “Botcoin: Monetizing stolen cycles”, in Proceedings of the Network and Distributed System Security Symposium.

Endnotes

[1] The Bitcoin ecosystem includes the core network for propagating transactions, the blockchain, and many intermediaries such as currency exchanges, mining pools, and payment processors that facilitate trade.

[Two] Markus was primarily active in period Three, but he was also active a few days during periods 1,Two, and Four. He was not active on the same days as Willy, who was only active in period Four.

Price manipulation in the Bitcoin ecosystem, VOX, CEPR’s Policy Portal

VOX CEPR’s Policy Portal

Research-based policy analysis and commentary from leading economists

Price manipulation in the Bitcoin ecosystem

Neil Gandal, JT Hamrick, Tyler Moore, Tali Oberman twenty two June two thousand seventeen

The cryptocurrency Bitcoin has attracted widespread interest, in large part due to wild swings in its valuation. This column considers an earlier rise in the Bitcoin price to investigate what is driving the currency’s price spikes. The two thousand thirteen rise was caused by fraudulent trades taking place at the largest Bitcoin currency exchange at the time. This finding has implications for policymakers as they weigh what, if anything, to do about regulating cryptocurrencies in light of the record high Bitcoin valuation that many fear is a bubble.

Related

The digital currency Bitcoin was introduced in 2009. Bitcoin and the many other digital currencies are primarily online currencies. The key currencies are those based primarily on cryptography, and Bitcoin is the leading ‘cryptocurrency’.

Bitcoin has experienced a meteoric rise in popularity since its introduction. While digital currencies were proposed as early as the 1980s, Bitcoin was the very first to catch on. The total value of all Bitcoins in circulation reached $45 billion in June 2017. Its success has inspired scores of rivaling cryptocurrencies that go after a similar design. Bitcoin and most other cryptocurrencies do not require a central authority to validate and lodge transactions. Instead, these currencies use cryptography (and an internal incentive system) to control transactions, manage the supply, and prevent fraud. Payments are validated by a decentralised network. Once confirmed, all transactions are stored digitally and recorded in a public ‘blockchain’,’ which can be thought of as a distributed accounting system.

While Bitcoin’s algorithm provides safeguards against ‘counterfeiting’ of the currency, the eco-system is still vulnerable to theft. Users keep keys to their Bitcoins and make transactions with the help of wallets. Exchanges facilitate trade inbetween Bitcoins and fiat currencies, and also permit for storing Bitcoins. Bitcoins can be stolen through wallets or exchanges. Exchanges have been targeted more frequently than wallets because many wallets are located on users’ (local) computers, while exchanges frequently store customer deposits in their own (much larger) wallets.

The supply of most cryptocurrencies increases at a predetermined rate, and cannot be switched by any central authority. There are about fifteen million Bitcoins presently in circulation, with the ultimate number eventually reaching twenty one million. The motionless supply in the long run creates concerns about the deflationary aspect of the currency.

While Bitcoin shows superb promise to disrupt existing payment systems through innovations in its technical design, the Bitcoin ecosystem one has been the frequent target of attacks by financially motivated criminals. Due to the unregulated, decentralised environment in which they operate, cryptocurrencies are under constant threat of attack.

Bitcoin only recently became a subject of research in economics. However, the topic has been of interest for longer in computer science (for early work by computer scientists on incentives, see Babaioff et al. 2012, and Eyal and Sirer 2014.) Numerous researchers have conducted studies in order to document and combat threats such as Ponzi schemes, money laundering, mining botnets, and the theft of cryptocurrency wallets (Moeser et al. 2013, Vasek and Moore 2015, Vasek et al. 2016, Yuxing et al. 2014). Ron and Shamir (2013) attempt to identify suspicious trading activity by building a graph of Bitcoin transactions found in the public ledger. None of these papers can associate individual transactions with specific users of the currency exchanges.

In latest work, we display that the very first time Bitcoin reached an exchange rate of more than $1,000, the meteoric rise was driven by fraud (Gandal et al. 2017). We leverage a unique and very detailed dataset to examine suspicious trading activity that occurred over a ten-month period in two thousand thirteen on Mt. Gox, the leading Bitcoin currency exchange at the time. We very first quantify the extent of the suspicious/fraudulent trading activity and demonstrate that it constitutes a large fraction of trading on the days the activity occurred. We then display how this trading activity affected the exchange rates at Mt. Gox and other leading currency exchanges.

Figure 1 Bitcoin–US dollar exchange rate, with periods of suspicious activity shaded

While it was the superior currency exchange when Bitcoin very first shot to prominence in early 2013, behind the scenes, Tokyo-based Mt. Gox was in trouble. In addition to suffering from repeated denial-of-service attacks and Bitcoin thefts, two unauthorised traders were able to transact on the exchange without spending real money. In the very first case, a trader dubbed ‘Markus’ was credited with Bitcoins by duplicating previously ended transactions. In the 2nd case, a trader dubbed ‘Willy’ bought Bitcoins from traders by ‘crediting’ the sellers’ accounts with fiat currencies that, in many cases, could not be withdrawn. Figure one shows when these fraudulent traders were active, along with the Bitcoin–US dollar exchange rate. Most noteworthy is that Willy’s operation coincided with an unprecedented hop in the price of Bitcoin: from around $150 to over $1000. In early 2014, Mt. Gox collapsed, and the Bitcoin price fell with it. Only recently, in early 2017, has Bitcoin surpassed the levels of the earlier rise.

However, how do we know that the rise was caused by the fraudulent trades? Fortunately for us as researchers, the unauthorised trades did not take place every day. Table one shows the daily switch in the Bitcoin–US dollar exchange rate for various time periods on Mt. Gox. In the two quarters before unauthorised trading commenced, the daily price increase was, on average, positive but relatively petite: a $0.21 increase in the very first period and a $1 increase in the 2nd period. During the third quarter, when unauthorised trading embarked, the price rose by an average of $Trio.15 on the seventeen days in which Markus traded, but fell on average by $0.51 on the seventy five days he did not trade. However, it is during the final quarter, when Willy began trading, that the difference became stark. On the fifty days in which Willy traded, the Bitcoin price rose by an average of $21.85. On the forty one days in which Willy did not make unauthorizsed purchases, the price fell by $0.88 on average. (Table one is very similar for the other leading exchanges as well.)

Table 1 Average daily switch in BTC/USD exchange rate as a function of fraudulent activity Two

In our total paper, we conduct a regression analysis to examine whether other factors such as the relatively numerous and varied attacks on the Mt. Gox exchange could explain the switch in the daily Bitcoin price, both at Mt. Gox and other leading exchanges (Gandal et al. 2017).

The analysis confirms that only Willy’s trading presence affected the price. The estimated coefficient (on the dummy variable for whether Willy was active) is virtually the same ($21.65) as in Table 1. We conclude that the suspicious trading activity of a single actor was the primary cause of the massive spike in the Bitcoin–US dollar exchange rate, in which the rate rose from around $150 to over $1,000 in just two months in late 2013. The fall was almost as precipitous: the Mt. Gox exchange folded due to insolvency in early 2014, and it has taken more than three years for Bitcoin to match the rise triggered by fraudulent transactions.

Why should we care about the Bitcoin manipulation that took place in 2013? After all, the Bitcoin ecosystem is not almost as significant as the Fresh York Stock Exchange. Nonetheless, latest trends indicate that Bitcoin is becoming an significant asset in the financial system.

Trading in cryptocurrency assets has exploded recently. In the case of Bitcoin, during the one year period ending in mid-June 2017, the market capitalisation enlargened massively from around $7 billion to $45 billion; that is an increase of over 500% in one year. The market cap of other cryptocurrencies surged by even more. In the one-year period ending in mid-May 2017, the market value of cryptocurrencies excluding Bitcoin surged from $1.7 billion to more than $29 billion; that is an increase of more than 1,900%. The markets for these other cryptocurrencies are very lean and subject to manipulation. Given that we now know the Bitcoin price has been artificially inflated by unauthorised trades in the past, we must view the present rise with excellent caution, and not necessarily consider it a ‘healthy bubble’, as recently claimed in The Economist (2017).

As mainstream finance invests in cryptocurrency assets and as countries take steps toward legalising Bitcoin as a payment system (as Japan did in April 2017), it is significant to understand how susceptible cryptocurrency markets are to manipulation. We encourage the nascent cryptocurrency industry to work with regulators and researchers to share anonymised transaction data so that more confidence can be placed in the veracity of exchange rates.

References

Babaioff, M, S Dobzinski, S Oren and A Zohar (2012), “On bitcoin and crimson balloons” in Proceedings of the 13th ACM Conference on Electronic Commerce, pp. 56-73.

Eyal, I and E Sirer (2014), “Majority is not Enough: Bitcoin Mining is Vulnerable”, paper introduced at the Eighteenth International Conference on Financial Cryptography and Data Security, Barbados, 3-7 March.

Gandal, N, J Hamrick, T Moore and T Oberman (2017), “Price Manipulation in the Bitcoin Ecosystem,” CEPR Discussion Paper No. 12061.

Mooser, M, R Bohme and D Breuker (2013), “An inquiry into money laundering devices in the Bitcoin ecosystem”, in Proceedings of the Seventh APWG eCrime Re-searcher’s Summit, pp. 1-14.

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Endnotes

[1] The Bitcoin ecosystem includes the core network for propagating transactions, the blockchain, and many intermediaries such as currency exchanges, mining pools, and payment processors that facilitate trade.

[Two] Markus was primarily active in period Three, but he was also active a few days during periods 1,Two, and Four. He was not active on the same days as Willy, who was only active in period Four.

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