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Data on Bitcoin-Exchange Closures Survival Analysis of Exchange Closure

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Data on Bitcoin-Exchange Closures Survival Analysis of Exchange Closure
Data on Bitcoin-Exchange Closures
Survival Analysis of Exchange Closure
Regression Analysis of Exchange Breaches
Beware the Middleman: Empirical Analysis of
Bitcoin-Exchange Risk
Tyler Moore1
1
Nicolas Christin2
Computer Science & Engineering, Southern Methodist University, USA,
[email protected]
2 INI & CyLab, Carnegie Mellon University, USA, [email protected]
Financial Crypto 2013
Okinawa, Japan
April 2, 2013
Tyler Moore & Nicolas Christin
Empirical Analysis of Bitcoin-Exchange Risk
Data on Bitcoin-Exchange Closures
Survival Analysis of Exchange Closure
Regression Analysis of Exchange Breaches
Motivation
Decentralization is a key feature of Bitcoin’s design
Viewed as a security benefit: protects against inflation risk,
sovereign risk, etc.
Yet an extensive ecosystem of 3rd-party intermediaries now
supports Bitcoin transactions: currency exchanges, escrow
services, online wallets, mining pools, investment services, . . .
Most risk Bitcoin holders face stems from interacting with
these intermediaries, who act as de facto central authorities
We focus on risk posed by failures of currency exchanges
Tyler Moore & Nicolas Christin
Empirical Analysis of Bitcoin-Exchange Risk
Data on Bitcoin-Exchange Closures
Survival Analysis of Exchange Closure
Regression Analysis of Exchange Breaches
Motivation
Decentralization is a key feature of Bitcoin’s design
Viewed as a security benefit: protects against inflation risk,
sovereign risk, etc.
Yet an extensive ecosystem of 3rd-party intermediaries now
supports Bitcoin transactions: currency exchanges, escrow
services, online wallets, mining pools, investment services, . . .
Most risk Bitcoin holders face stems from interacting with
these intermediaries, who act as de facto central authorities
We focus on risk posed by failures of currency exchanges
Tyler Moore & Nicolas Christin
Empirical Analysis of Bitcoin-Exchange Risk
Data on Bitcoin-Exchange Closures
Survival Analysis of Exchange Closure
Regression Analysis of Exchange Breaches
Motivation
Decentralization is a key feature of Bitcoin’s design
Viewed as a security benefit: protects against inflation risk,
sovereign risk, etc.
Yet an extensive ecosystem of 3rd-party intermediaries now
supports Bitcoin transactions: currency exchanges, escrow
services, online wallets, mining pools, investment services, . . .
Most risk Bitcoin holders face stems from interacting with
these intermediaries, who act as de facto central authorities
We focus on risk posed by failures of currency exchanges
Tyler Moore & Nicolas Christin
Empirical Analysis of Bitcoin-Exchange Risk
Data on Bitcoin-Exchange Closures
Survival Analysis of Exchange Closure
Regression Analysis of Exchange Breaches
Outline of today’s talk
1
Data on Bitcoin-Exchange Closures
Data Collection Methodology
Summary Statistics
2
Survival Analysis of Exchange Closure
Statistical Model
Results
Risk Ratio for Bitcoin Exchanges
3
Regression Analysis of Exchange Breaches
Statistical Model
Results
Tyler Moore & Nicolas Christin
Empirical Analysis of Bitcoin-Exchange Risk
Data on Bitcoin-Exchange Closures
Survival Analysis of Exchange Closure
Regression Analysis of Exchange Breaches
Data Collection Methodology
Summary Statistics
Outline
1
Data on Bitcoin-Exchange Closures
Data Collection Methodology
Summary Statistics
2
Survival Analysis of Exchange Closure
Statistical Model
Results
Risk Ratio for Bitcoin Exchanges
3
Regression Analysis of Exchange Breaches
Statistical Model
Results
Tyler Moore & Nicolas Christin
Empirical Analysis of Bitcoin-Exchange Risk
Data on Bitcoin-Exchange Closures
Survival Analysis of Exchange Closure
Regression Analysis of Exchange Breaches
Data Collection Methodology
Summary Statistics
Data collection methodology
Data sources
1
2
3
Daily transaction volume data on 40 exchanges converting into
33 currencies from bitcoincharts.com
Checked for closure, mention of security breaches and whether
investors were repaid on Bitcoin Wiki and forums
To assess impact of pressure from financial regulators, we
identified each exchange’s country of incorporation and used a
World Bank index on compliance with anti-money laundering
regulations
Key measure: exchange lifetime
Time difference between first and last observed trade
We deem an exchange closed if no transactions are observed at
least 2 weeks before data collection finished
Tyler Moore & Nicolas Christin
Empirical Analysis of Bitcoin-Exchange Risk
Data on Bitcoin-Exchange Closures
Survival Analysis of Exchange Closure
Regression Analysis of Exchange Breaches
Data Collection Methodology
Summary Statistics
Some initial summary statistics
40 Bitcoin currency exchanges opened since 2010
18 have subsequently closed (45% failure rate)
Median lifetime is 381 days
45% of closed exchanges did not reimburse customers
9 exchanges were breached (5 closed)
Tyler Moore & Nicolas Christin
Empirical Analysis of Bitcoin-Exchange Risk
Data on Bitcoin-Exchange Closures
Survival Analysis of Exchange Closure
Regression Analysis of Exchange Breaches
Data Collection Methodology
Summary Statistics
18 closed Bitcoin currency exchanges
Exchange
Origin
Dates Active
BitcoinMarket
Bitomat
FreshBTC
Bitcoin7
ExchangeBitCoins.com
Bitchange.pl
Brasil Bitcoin Market
Aqoin
Global Bitcoin Exchange
Bitcoin2Cash
TradeHill
World Bitcoin Exchange
Ruxum
btctree
btcex.com
IMCEX.com
Crypto X Change
Bitmarket.eu
US
PL
PL
US/BG
US
PL
BR
ES
?
US
US
AU
US
US/CN
RU
SC
AU
PL
4/10 – 6/11
4/11 – 8/11
8/11 – 9/11
6/11 – 10/11
6/11 – 10/11
8/11 – 10/11
9/11 – 11/11
9/11 – 11/11
9/11 – 1/12
4/11 - 1/12
6/11 - 2/12
8/11 – 2/12
6/11 – 4/12
5/12 – 7/12
9/10 – 7/12
7/11 – 10/12
11/11 – 11/12
4/11 – 12/12
Tyler Moore & Nicolas Christin
Daily vol.
2454
758
3
528
551
380
0
11
14
18
5082
220
37
75
528
2
874
33
Closed?
Breached?
Repaid?
AML
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
no
yes
no
no
no
no
no
no
yes
yes
no
no
no
no
no
no
–
yes
–
no
–
–
–
–
–
–
yes
no
yes
yes
no
–
–
no
34.3
21.7
21.7
33.3
34.3
21.7
24.3
30.7
27.9
34.3
34.3
25.7
34.3
29.2
27.7
11.9
25.7
21.7
Empirical Analysis of Bitcoin-Exchange Risk
Data on Bitcoin-Exchange Closures
Survival Analysis of Exchange Closure
Regression Analysis of Exchange Breaches
Data Collection Methodology
Summary Statistics
22 open Bitcoin currency exchanges
Exchange
Origin
Dates Active
Daily vol.
bitNZ
ICBIT Stock Exchange
WeExchange
Vircurex
btc-e.com
Mercado Bitcoin
Canadian Virtual Exchange
btcchina.com
bitcoin-24.com
VirWox
Bitcoin.de
Bitcoin Central
Mt. Gox
Bitcurex
Kapiton
bitstamp
InterSango
Bitfloor
Camp BX
The Rock Trading Company
bitme
FYB-SG
NZ
SE
US/AU
US?
BG
BR
CA
CN
DE
DE
DE
FR
JP
PL
SE
SL
UK
US
US
US
US
SG
9/11 – pres.
3/12 – pres.
10/11 – pres.
12/11 – pres.
8/11 – pres.
7/11 – pres.
6/11 – pres.
6/11 – pres.
5/12 – pres.
4/11 – pres.
8/11 – pres.
1/11 – pres.
7/10 – pres.
7/12 – pres.
4/12 – pres.
9/11 – pres.
7/11 – pres.
5/12 – pres.
7/11 – pres.
6/11 – pres.
7/12 – pres.
1/13 – pres.
27
3
2
6
2604
67
832
473
924
1668
1204
118
43230
157
160
1274
2741
816
622
52
77
3
Tyler Moore & Nicolas Christin
Closed?
Breached?
Repaid?
AML
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
no
yes
yes
no
no
no
no
no
no
no
yes
no
no
no
no
yes
no
no
no
no
–
–
–
–
yes
–
–
–
–
–
–
–
yes
–
–
–
–
no
–
–
–
–
21.3
27.0
30.0
27.9
32.3
24.3
25.0
24.0
26.0
26.0
26.0
31.7
22.7
21.7
27.0
35.3
35.3
34.3
34.3
34.3
34.3
33.7
Empirical Analysis of Bitcoin-Exchange Risk
Data on Bitcoin-Exchange Closures
Survival Analysis of Exchange Closure
Regression Analysis of Exchange Breaches
Statistical Model
Results
Risk Ratio for Bitcoin Exchanges
Outline
1
Data on Bitcoin-Exchange Closures
Data Collection Methodology
Summary Statistics
2
Survival Analysis of Exchange Closure
Statistical Model
Results
Risk Ratio for Bitcoin Exchanges
3
Regression Analysis of Exchange Breaches
Statistical Model
Results
Tyler Moore & Nicolas Christin
Empirical Analysis of Bitcoin-Exchange Risk
Data on Bitcoin-Exchange Closures
Survival Analysis of Exchange Closure
Regression Analysis of Exchange Breaches
Statistical Model
Results
Risk Ratio for Bitcoin Exchanges
What factors affect whether an exchange closes?
We hypothesize three variables affect survival time for a
Bitcoin exchange
1
2
3
Average daily transaction volume (positive)
Experiencing security breach (negative)
AML/CFT compliance (negative)
Since lifetimes are censored, we construct a Cox proportional
hazards model:
hi (t) = h0 (t) exp(β1 log(Daily vol.)i +β2 Breachedi +β3 AMLi ).
Tyler Moore & Nicolas Christin
Empirical Analysis of Bitcoin-Exchange Risk
Data on Bitcoin-Exchange Closures
Survival Analysis of Exchange Closure
Regression Analysis of Exchange Breaches
Statistical Model
Results
Risk Ratio for Bitcoin Exchanges
Cox proportional hazards model: results
log(Daily vol.)i
Breachedi
AMLi
β1
β2
β3
coef.
−0.173
0.857
0.004
exp(coef.)
0.840
2.36
1.004
Std. Err.)
0.072
0.572
0.042
Significance
p = 0.0156
p = 0.1338
p = 0.9221
log-rank test: Q=7.01 (p = 0.0715), R2 = 0.145
Higher daily transaction volumes associated with longer
survival times (statistically significant)
Experiencing a breach associated with shorter survival times
(not quite statistically significant)
Tyler Moore & Nicolas Christin
Empirical Analysis of Bitcoin-Exchange Risk
Data on Bitcoin-Exchange Closures
Survival Analysis of Exchange Closure
Regression Analysis of Exchange Breaches
Statistical Model
Results
Risk Ratio for Bitcoin Exchanges
1.0
Survival probability for Bitcoin exchanges
0.6
0.4
0.2
0.0
Survival probability
0.8
Average
0
200
400
600
800
Days
Tyler Moore & Nicolas Christin
Empirical Analysis of Bitcoin-Exchange Risk
Data on Bitcoin-Exchange Closures
Survival Analysis of Exchange Closure
Regression Analysis of Exchange Breaches
Statistical Model
Results
Risk Ratio for Bitcoin Exchanges
1.0
High-volume exchanges have better chance to survive
0.6
0.4
0.2
0.0
Survival probability
0.8
Mt. Gox
Intersango
Average
0
200
400
600
800
Days
Tyler Moore & Nicolas Christin
Empirical Analysis of Bitcoin-Exchange Risk
Data on Bitcoin-Exchange Closures
Survival Analysis of Exchange Closure
Regression Analysis of Exchange Breaches
Statistical Model
Results
Risk Ratio for Bitcoin Exchanges
1.0
Low-volume exchanges have worse chance to survive
0.6
0.4
0.2
0.0
Survival probability
0.8
Mt. Gox
Intersango
Bitcoin2Cash
Average
0
200
400
600
800
Days
Tyler Moore & Nicolas Christin
Empirical Analysis of Bitcoin-Exchange Risk
Data on Bitcoin-Exchange Closures
Survival Analysis of Exchange Closure
Regression Analysis of Exchange Breaches
Statistical Model
Results
Risk Ratio for Bitcoin Exchanges
1.0
Yet some lower-risk exchanges collapse, high-risk survive
Mt. Gox
Intersango
0.2
0.4
0.6
Vircurex
Exchange
BitCoins.com
Average
0.0
Survival probability
0.8
Bitcoin2Cash
0
200
400
600
800
Days
Tyler Moore & Nicolas Christin
Empirical Analysis of Bitcoin-Exchange Risk
Data on Bitcoin-Exchange Closures
Survival Analysis of Exchange Closure
Regression Analysis of Exchange Breaches
Statistical Model
Results
Risk Ratio for Bitcoin Exchanges
Risk ratio for all 40 exchanges
Survival Risk Ratio for Bitcoin Exchanges
Open (Breached)
4
● Open (Not Breached)
Closed (Breached)
3
● Closed (Not Breached)
2
●
●●
●
1
●●
●
●●
●●
●
●●
●
●●
●●●
●
●●
●● ●
0
risk ratio (1 = average)
●
1
10
100
1000
10000
average daily BTC transaction volume
Tyler Moore & Nicolas Christin
Empirical Analysis of Bitcoin-Exchange Risk
Data on Bitcoin-Exchange Closures
Survival Analysis of Exchange Closure
Regression Analysis of Exchange Breaches
Statistical Model
Results
Outline
1
Data on Bitcoin-Exchange Closures
Data Collection Methodology
Summary Statistics
2
Survival Analysis of Exchange Closure
Statistical Model
Results
Risk Ratio for Bitcoin Exchanges
3
Regression Analysis of Exchange Breaches
Statistical Model
Results
Tyler Moore & Nicolas Christin
Empirical Analysis of Bitcoin-Exchange Risk
Data on Bitcoin-Exchange Closures
Survival Analysis of Exchange Closure
Regression Analysis of Exchange Breaches
Statistical Model
Results
What factors affect whether an exchange is breached?
We hypothesize three variables affect whether a Bitcoin
exchange loses money from a security breach
1
2
Average daily transaction volume (positive)
Months operational (positive)
We use a logistic regression model with a dependent variable
denoting whether or not an exchange experiences a breach:
log (pb /(1 − pb )) = c0 + c1 log(Daily vol.)
+ c2 months operational
+ ε.
Tyler Moore & Nicolas Christin
Empirical Analysis of Bitcoin-Exchange Risk
Data on Bitcoin-Exchange Closures
Survival Analysis of Exchange Closure
Regression Analysis of Exchange Breaches
Statistical Model
Results
Logistic regression for exchange breaches
Intercept
log(Daily vol.)
Months operational
coef.
−4.304
0.514
−0.104
Odds-ratio
0.014
1.672
0.901
95% conf. int.
(0.0002,0.211)
(1.183,2.854)
(0.771,1.025)
Significance
p = 0.0131
p = 0.0176
p = 0.1400
Model fit: χ2 = 10.3, p = 0.00579
Transaction volume is positively correlated with experiencing a
breach (statistically significant)
Months operational is negatively correlated with being
breached (not quite statistically significant)
Tyler Moore & Nicolas Christin
Empirical Analysis of Bitcoin-Exchange Risk
Data on Bitcoin-Exchange Closures
Survival Analysis of Exchange Closure
Regression Analysis of Exchange Breaches
Statistical Model
Results
1.0
0.2
0.4
0.6
0.8
Predicted probability
90% C.I.
0.0
Probability exchange has breach
Breach probability as a function of daily transaction volume
5
50
500
5000
50000
Daily transaction volume at exchange
Tyler Moore & Nicolas Christin
Empirical Analysis of Bitcoin-Exchange Risk
Data on Bitcoin-Exchange Closures
Survival Analysis of Exchange Closure
Regression Analysis of Exchange Breaches
Concluding remarks (1)
Currency exchanges pose substantial risk to Bitcoin holders:
45% of exchanges have closed, often leaving customers unable
to withdraw stored funds
Using survival analysis, we found that an exchange’s average
transaction volume is negatively correlated with the
probability it will close prematurely
Using regression, we found that transaction volume is
positively correlated with experiencing a breach
Hence, the continued operation of an exchange depends on
running a high transaction volume, which makes the exchange
a more valuable target to thieves
Tyler Moore & Nicolas Christin
Empirical Analysis of Bitcoin-Exchange Risk
Data on Bitcoin-Exchange Closures
Survival Analysis of Exchange Closure
Regression Analysis of Exchange Breaches
Concluding remarks (2)
Limitations to the statistical analysis
1
2
There is substantial randomness affecting when an exchange
closes or is breached that is not captured by our mode
Some of the explanatory variables did not achieve statistical
significance due to the dataset’s modest size
We focus on economic considerations, such as closure risk,
that a rational actor should consider before transacting with
an exchange
But behavioral factors may explain participation better (e.g.,
Silk Road customers want exchanges that respect anonymity)
Paper: http://lyle.smu.edu/~tylerm/fc13.pdf
Tyler Moore & Nicolas Christin
Empirical Analysis of Bitcoin-Exchange Risk
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