"Beware the Middleman: Empirical Analysis of Bitcoin-Exchange Risk", Moore & Christin 2013 (for R code implementing their results, see Reddit comment http://www.reddit.com/r/Bitcoin/comments/1d7qkj/study_45_percent_of_bitcoin_exchanges_end_up/c9pc7la ):
"...We study the risk investors face from Bitcoin exchanges, which convert between Bitcoins and hard currency. We examine the track record of 40 Bitcoin exchanges established over the past three years, and find that 18 have since closed, with customer account balances often wiped out. Fraudsters are sometimes to blame, but not always. Using a proportional hazards model, we find that an exchange’s transaction volume indicates whether or not it is likely to close. Less popular exchanges are more likely to be shut than popular ones. We also present a logistic regression showing that popular exchanges are more likely to suffer a security breach.
We begin by collecting historical data on the Bitcoin exchange rates maintained by the website bitcoincharts.com. This includes the daily trade volumes and average weighted daily price for 40 Bitcoin exchanges converting into 33 currencies until January 16, 2013, when the data collection was made. We calculated the average daily trade volume for each exchange by tallying the total number of Bitcoins converted into all currencies handled by the exchange for the days the exchange was operational. We also calculate the “lifetime” of each exchange, that is, the number of days the exchange is operational, denoted by the difference between the first and last observed trade. We deem an exchange to have closed if it had not made a trade in at least two weeks before the end of data collection. We further inspected the existence of a report on the Bitcoin Wiki [11] or on Bitcoin forums [12] to confirm closure, and determine whether closure was caused by a security breach (e.g., hack or fraud). We also checked for reports on whether or not investors were repaid following the exchange’s closure. Finally, to assess regulatory impact, we attempted to identify the country where each exchange is based. We then used an index (ranging between 0 and 49) computed by World Bank economists [13] to identify each country’s compliance with “Anti-Money-Laundering and Combating the Financing of Terrorism” (AML-CFT) regulations [13].
Table 1 lists all 40 known Bitcoin currency exchanges, along with relevant facts about whether the exchange later closed. Nine exchanges experienced security breaches, caused either by hackers or other criminal activity. Five of these exchanges subsequently closed, but four have survived so far (Mt. Gox, btc-e.com, Bitfloor, and Vircurex). Another nine closed without experiencing a publicly-announced breach.
The popularity of exchanges varied greatly, with 25% of exchanges processing under 25 Bitcoins each day on average, while the most popular exchange, Mt. Gox, has averaged daily transactions exceeding 40 000 BTC. The median daily transactions carried out by exchanges is 290, while the mean is 1 716. One key factor affecting the risk posed by exchanges is whether or not its customers are reimbursed following closure. We must usually rely on claims by the operator and investors if they are made public. Of the 18 exchanges that closed, we have found evidence on whether customers were reimbursed in 11 cases. Five exchanges have not reimbursed affected customers, while six claim to have done so. Thus, the risk of losing funds stored at exchanges is real but uncertain. As a first approximation, the failure rate of Bitcoin exchanges is 45%. The median lifetime of exchanges is 381 days.
This can help Bitcoin investors weigh their risks before putting money into an exchange-managed account. The black solid line plots the estimated survival function for the best fit parameters outlined above for the mean values of exchange volume, whether a site has been hacked, and AML score. For instance, S(365) = 0.711 with 95% confidence interval (0.576, 0.878): there is a 29.9% chance a new Bitcoin exchange will close within a year of opening (12.2%–42.4% with 95% confidence).
Transaction volume is positively correlated with experiencing a breach. Months operational, meanwhile, is negatively correlated with being breached, but the association just falls short of statistical significance (p = 0.14). Thus, we face a conundrum: according to the results of Section 3, high-volume exchanges are less likely to close but more likely to experience a breach. Bitcoin holders can choose to do business with less popular exchanges to reduce the risk of losing money due to a breach, or with more popular exchanges that may be breached, but are less likely to shut down without warning.
Figure 2 takes the coefficients for a best-fit logit model and plots the probability that an exchange operational for the average duration of one year will be breached as transaction volume increases. For example, exchanges handling 275 Bitcoins’ worth of transactions each day have a 20% chance of being breached, compared to a 70% chance for exchanges processing daily transactions worth 5570 Bitcoins.
Our statistical analysis presents two notable limitations. First, there is substantial randomness affecting when an exchange closes or is breached that is not captured by our model. Future work might investigate additional explanatory variables, such as the exchange reputation. Second, some of the explanatory variables did not achieve statis- tical significance due to the data set’s modest size. The analysis is worth revisiting as time passes and new exchanges are opened and old ones close.
Finally, we focused on economic considerations, such as closure risks, that a rational actor would want to estimate before investing in a given exchange. However, reducing Bitcoin to a mere speculative instrument likely misses an important part of the puzzle. For all its recent success, Bitcoin remains a rather small financial network. Bitcoin users are still by and large early adopters, for whom non-economic aspects may play a significant role in the selection of a given exchange. For instance, Silk Road users, who constitute a non-negligible share of the Bitcoin economy [7], may shy away from exchanges that require identification, and instead prefer assurances of anonymity. This may in turn lead them to participate in exchanges with greater economic risk. Studying the unique characteristics of Bitcoin users and investors – compared to typical foreign exchange traders – is an avenue for future work we think is well worth exploring."
#bitcoin #R
"...We study the risk investors face from Bitcoin exchanges, which convert between Bitcoins and hard currency. We examine the track record of 40 Bitcoin exchanges established over the past three years, and find that 18 have since closed, with customer account balances often wiped out. Fraudsters are sometimes to blame, but not always. Using a proportional hazards model, we find that an exchange’s transaction volume indicates whether or not it is likely to close. Less popular exchanges are more likely to be shut than popular ones. We also present a logistic regression showing that popular exchanges are more likely to suffer a security breach.
We begin by collecting historical data on the Bitcoin exchange rates maintained by the website bitcoincharts.com. This includes the daily trade volumes and average weighted daily price for 40 Bitcoin exchanges converting into 33 currencies until January 16, 2013, when the data collection was made. We calculated the average daily trade volume for each exchange by tallying the total number of Bitcoins converted into all currencies handled by the exchange for the days the exchange was operational. We also calculate the “lifetime” of each exchange, that is, the number of days the exchange is operational, denoted by the difference between the first and last observed trade. We deem an exchange to have closed if it had not made a trade in at least two weeks before the end of data collection. We further inspected the existence of a report on the Bitcoin Wiki [11] or on Bitcoin forums [12] to confirm closure, and determine whether closure was caused by a security breach (e.g., hack or fraud). We also checked for reports on whether or not investors were repaid following the exchange’s closure. Finally, to assess regulatory impact, we attempted to identify the country where each exchange is based. We then used an index (ranging between 0 and 49) computed by World Bank economists [13] to identify each country’s compliance with “Anti-Money-Laundering and Combating the Financing of Terrorism” (AML-CFT) regulations [13].
Table 1 lists all 40 known Bitcoin currency exchanges, along with relevant facts about whether the exchange later closed. Nine exchanges experienced security breaches, caused either by hackers or other criminal activity. Five of these exchanges subsequently closed, but four have survived so far (Mt. Gox, btc-e.com, Bitfloor, and Vircurex). Another nine closed without experiencing a publicly-announced breach.
The popularity of exchanges varied greatly, with 25% of exchanges processing under 25 Bitcoins each day on average, while the most popular exchange, Mt. Gox, has averaged daily transactions exceeding 40 000 BTC. The median daily transactions carried out by exchanges is 290, while the mean is 1 716. One key factor affecting the risk posed by exchanges is whether or not its customers are reimbursed following closure. We must usually rely on claims by the operator and investors if they are made public. Of the 18 exchanges that closed, we have found evidence on whether customers were reimbursed in 11 cases. Five exchanges have not reimbursed affected customers, while six claim to have done so. Thus, the risk of losing funds stored at exchanges is real but uncertain. As a first approximation, the failure rate of Bitcoin exchanges is 45%. The median lifetime of exchanges is 381 days.
This can help Bitcoin investors weigh their risks before putting money into an exchange-managed account. The black solid line plots the estimated survival function for the best fit parameters outlined above for the mean values of exchange volume, whether a site has been hacked, and AML score. For instance, S(365) = 0.711 with 95% confidence interval (0.576, 0.878): there is a 29.9% chance a new Bitcoin exchange will close within a year of opening (12.2%–42.4% with 95% confidence).
Transaction volume is positively correlated with experiencing a breach. Months operational, meanwhile, is negatively correlated with being breached, but the association just falls short of statistical significance (p = 0.14). Thus, we face a conundrum: according to the results of Section 3, high-volume exchanges are less likely to close but more likely to experience a breach. Bitcoin holders can choose to do business with less popular exchanges to reduce the risk of losing money due to a breach, or with more popular exchanges that may be breached, but are less likely to shut down without warning.
Figure 2 takes the coefficients for a best-fit logit model and plots the probability that an exchange operational for the average duration of one year will be breached as transaction volume increases. For example, exchanges handling 275 Bitcoins’ worth of transactions each day have a 20% chance of being breached, compared to a 70% chance for exchanges processing daily transactions worth 5570 Bitcoins.
Our statistical analysis presents two notable limitations. First, there is substantial randomness affecting when an exchange closes or is breached that is not captured by our model. Future work might investigate additional explanatory variables, such as the exchange reputation. Second, some of the explanatory variables did not achieve statis- tical significance due to the data set’s modest size. The analysis is worth revisiting as time passes and new exchanges are opened and old ones close.
Finally, we focused on economic considerations, such as closure risks, that a rational actor would want to estimate before investing in a given exchange. However, reducing Bitcoin to a mere speculative instrument likely misses an important part of the puzzle. For all its recent success, Bitcoin remains a rather small financial network. Bitcoin users are still by and large early adopters, for whom non-economic aspects may play a significant role in the selection of a given exchange. For instance, Silk Road users, who constitute a non-negligible share of the Bitcoin economy [7], may shy away from exchanges that require identification, and instead prefer assurances of anonymity. This may in turn lead them to participate in exchanges with greater economic risk. Studying the unique characteristics of Bitcoin users and investors – compared to typical foreign exchange traders – is an avenue for future work we think is well worth exploring."
#bitcoin #R