quieting the chaos - the economist · 2020. 4. 3. · both ether and bitcoin. investment strategy...
TRANSCRIPT
October 17, 2016
Team Hullabaloo
Jon-Paul Navarro
Alex Moore
Jake Tremblay
Quieting the Chaos Kraken Investment Case Study: An Analysis and Investment Strategy for
Bitcoin and Ether
Introduction
Bitcoin (BTX) and Ether (ETH) are two of the highest profile members of crypto-currencies—a new,
exciting asset class that has come into being within the past decade. These assets run on decentralized
networks that produce a ledger of transactions using the computing power of all machines on the
network. This running account of historical transactions, with each step having its own unique
cryptographic signature, creates a record that is nearly impossible to alter without detection. This
technology, popularly referred to as Blockchain, has been referenced by many as having the potential to
revolutionize a wide range of transactions inside and outside of the financial industry.
Unlike traditional fiat currencies, no government or central body guarantees the value of these assets.
Market sentiment regarding the future utility and value of these assets can therefore produce large
swings in value. Further compounding this issue, there are dozens of crypto-currencies vying for market
dominance. Despite these enduring questions, the market performances of Ether and Bitcoin, the two
crypto-currencies with the highest market capitalization, as of the publishing date of this analysis, have
been objectively impressive. In evaluating how to invest one million dollars in Bitcoin, Ether, or some
combination of both for the next five years, balancing the large potential upside of these assets with
their volatility played a large role in our deliberations.
Current State of the Crypto-Currency Market
At present, Bitcoin has the largest market capitalization of any cryptocurrency, equivalent to
approximately $9.8 billion USD as of October 2016. This market capitalization eclipses that of the next
most prominent cryptocurrency, Ether (which we will refer to interchangeably as Ethereum) by nearly
an order of magnitude. In turn, Ethereum’s market capitalization is approximately four times greater
than the next closest competitor (Table 1).
Table 1. Snapshot of Crypto-Currency Market October 9, 2016
Asset Market Capitalization (USD)
Price (USD) Trading Volume (24hr)
Bitcoin $9,829,675,887 $617.72 $35591448
Ethereum $1,044,348,129 $12.32 $9,981,326
Ripple $261,532,818 $0.007372 $2464,481
Litecoin $183,515,682 $3.83 $1,038,614 Source: coinmarketcap.com
As the oldest crypto-currency, Bitcoin obtained first mover advantage in this space and spawned a
plethora of imitators. There is no central bank regulating Bitcoin, and total supply is capped at 21 million
Bitcoins. Generation of new Bitcoin is determined by a process called mining. In essence, network users
supply computational power to verify transactions on the Bitcoin network; this computational work is
rewarded with Bitcoin according to predetermined mining rates. Mining rates decline each year, and
current projections estimate that Bitcoin mining will halt in approximately the year 2140. After this
point, no new Bitcoins will enter into circulation. Given a small amount of Bitcoin lost yearly due to
various causes, Bitcoin circulation will almost certainly contract slightly after mining halts. This eventual
monetary contraction reinforces Bitcoin’s central purpose to act as a relatively stable, easily
transferrable store of value.
Ether is a relatively new entrant into the crypto-currency market. Announced in January 2014 and
initially traded in late July 2015, Ether has quickly attained the second largest market capitalization of
any crypto-currency. Ether serves as the “fuel” for the broader Ethereum, a Blockchain platform that
enables smart contracts based on Turing complete architecture. In lay terms, Ethereum allows
developers impressive flexibility in using the network to facilitate a variety of smart contracts. In theory,
Ethereum’s large community of developers will expand Blockchain technology to a variety of everyday
uses. This ideally creates and encourages a network effect in which the more users adopt Ether and use
it as a currency to execute smart contracts, the more valuable Ether becomes. Based on the velocity of
the price increase of Ether, there are a number of people who believe in this optimistic view of Ether’s
future.
In contrast to the declining mining rates of Bitcoin, Ethereum’s developers have projected a constant
rate of Ether issuance of 18,000,000 ETH per year in perpetuity. As the monetary base of Ether
increases, a small yearly percentage loss of Ether from circulation will eventually equilibrate with Ether
issuance, leading to a relatively constant amount of Ether in circulation. Per the Ethereum consortium,
this equilibration is projected to occur approximately 64 years after Ether is initially issued,
corresponding to 2079. A projected change from a proof of work system to proof of stake for Ethereum
may slightly alter this issuance model; per Ethereum literature, however, the change will not materially
affect the monetary base of Ether.
The differing issuance models of Ether and Bitcoin also speak to the broader point that the two assets
were designed for different purposes. Bitcoin was designed primarily as an asset. It was designed as a
digital currency to serve as a relatively stable source of value. Ether, in contrast, was designed with a
broader purpose. It was designed to enable a whole system of smart contracts. While the distinction
may be subtle, we believe it is critical to address. Whether the two assets serve distinct purposes
determines whether the two can coexist for a significant time in the future.
Ultimately, however, the subtle differences between Bitcoin and Ether distract from the broader issue
that a great deal of uncertainty remains around the future of crypto-currencies. Whereas some
countries have moved to embrace crypto-currencies, a number still do not recognize them as legal
tender (see Exhibit 1 for an example in Kenya). This uncertainty is reflected in significant fluctuations in
the price of both Bitcoin and Ethereum. Weekly volatility in bitcoin prices, for instance, has exceeded
the volatility in US equities, US real estate, oil prices, and emerging market equities for the past five
years. Over the past year, volatility in Ether has surpassed the volatility of bitcoin (see Figure 1 for price
comparison of Bitcoin and Ether over the past fourteen months). Any reasonable investment strategy in
these two assets must, therefore, address and at least partially mitigate this volatility.
Figure 1: Price Comparison- Ether vs Bitcoin Over Lifespan of Ether
Data Courtesy of Bloomberg, October 2016
Investment Thesis
The fact that crypto-currencies are being evaluated in the framework of an investment case competition
highlights that these securities do not act like traditional fiat currencies. No investor looks to park a
million dollars worth of Japanese yen or British pounds or some combination thereof in a vault for five
years. The reason for this is relatively simple – most currencies are expected to decline in value. Some
expectation of inflation is built in. Five years from now, one million dollars will not have the same
purchasing power it does today.
We do not conceptualize crypto-currencies in the same fashion. There is an expectation of return on
investment. We argue therefore that a more constructive framework for evaluating investment in these
entities is to treat them as assets. For the sake of simplicity, we will continue to refer to Ether and
Bitcoin as crypto-currencies, but a more accurate term is likely crypto-assets. Like any assets, the value
of Ether and Bitcoin are determined by supply and demand. Advantageously, the developers of Bitcoin
and Ethereum have defined the supply schedule for both currencies, as has been described above.
The second determinant of cryptocurrency value (demand) is much harder to project. This difficulty is
compounded by the fact that the purposes of these two currencies differ. Bitcoin is designed to be a
stable source of value. A valuable analogy is gold. The price of gold increases and decreases with supply
and consumer sentiment, but the primary determinant of its value is that financial actors believe it will
continue to have value in the future. They do not expect to use gold for any kind of application; they
expect to exchange it for goods or services in the future.
Alternately, Ether is probably more analogous to oil. Demand is not dependent solely on an expectation
of future value; it is also a function of utility. Oil prices historically have increased when the potential
uses of oil have increased. Ether’s value will be determined in a similar fashion; it depends on the
number of applications created on the Ethereum framework that will use Ether as a fuel. Prices have
risen recently in large part because investors are bullish on the possibility that Ethereum’s Blockchain
technology will be used in an increasing variety of transactions. With prominent firms like Microsoft and
Thomson Reuters already beginning to build projects on the application development platform, it is a
reasonable expectation that Ethereum will continue to expand, increasing the demand for Ether.
Further evidence of the promising nature of this Blockchain technology is the fact that major financial
institutions including JP Morgan, Credit Suisse, Goldman Sachs, and RBS are all exploring potential
Blockchain applications within their internal operations.
In summary, therefore, we have two fundamentally different assets. One is designed to be a vehicle for
value storage and transfer; the other is designed to act as fuel for a platform utilized in a wide variety of
applications. There is no question that Bitcoin has the more prominent market position at present.
Bitcoin’s market capitalization exceeds that of Ethereum by almost an order of magnitude. It has been
present for a longer period of time and has experienced significantly less volatility than Ethereum over
the short period that the two currencies can be compared head to head. Ethereum, however, offers
significantly higher upside and more impressive recent financial performance. By extending Blockchain
technology to a variety of transactions, Ethereum may serve to make Blockchain technology and crypto-
currencies mainstream. If Ethereum can achieve this goal, the value of Ether will increase accordingly.
This outcome, however, is far from certain, and this uncertainty is reflected in the marked volatility of
both Ether and Bitcoin.
Investment Strategy
An ideal investment strategy in these two cryptocurrencies would expose an investor to the positive
upside potential of Ether while using the comparative stability of Bitcoin and diversification effects to
reduce portfolio variance. Based on historical data of these two currencies, we determined that the
returns of the two currencies are essentially uncorrelated (Figure 2). Holding a portfolio of these two
assets therefore offers the potential for diversification. Using the past six months of data to minimize
any pricing aberrations surrounding the first months of the release of Ether, we used a nonlinear
optimization model in Microsoft Excel to construct a minimum variance portfolio of these two assets
that consists of 67% Bitcoin and 33% Ether.
Figure 2: Ether Return (Y axis) vs Bitcoin Return (X axis)
Data courtesy of Bloomberg, October 2016
Investment Strategy Verification
In order to verify that the Minimum Variance Portfolio (MVP) was the optimal portfolio strategy, three
approaches were used for the quantitative analysis: a 5-year regression forecast, a back-test of six
months of weekly historical prices , and a 52-week Monte Carlo simulation. These tests included three
alternative portfolio strategies in addition to the MVP: 100% Bitcoin, 100% Ether, and a 50% Bitcoin/50%
Ether portfolio.
Regression Model Forecasting
The first step for this forecast method was to analyze the correlation between Bitcoin and Ether along
with more traditional assets. All selected assets were categorized into three “superclasses”: capital
assets, consumable/transformable assets, and store of value assets. Then the correlations were
computed to determine the sensitivity of the crypto-currencies to these comparable assets
For capital assets, we measured the correlation between Bitcoin and Ether to the S&P 500 Index (SPX).
It is difficult to select an individual equity or fixed income security that would best relate to the crypto-
currencies, and it is highly unlikely that a single asset of this nature has such an influential relationship
with the crypto-currencies. Therefore we thought it prudent to use a widely-accepted and diverse index
to replicate the capital market.
For consumable/transformable assets, we analyzed the relationship between Bitcoin and Ether with
several commodities and valuable minerals. We looked at commodities with varying supplies but with
high and stable intrinsic values. The assets that were analyzed were: Gold, Palladium, Neodymium,
Copper, Crude Oil, and Platinum.
Finally for store of value assets, we measured the relationship between the two crypto-currencies and
several fiat currencies. We chose five major currencies: the Japanese Yen, New Zealand Dollar,
Norwegian Krone, British Pound, and the Euro. We also chose five emerging market currencies: Czech
Koruna, Romanian Leu, Argentinian Peso, Hungarian Forint, and the Chinese Renminbi. The emerging
market currencies provided interesting feedback in terms of their correlation to each other and their
significance in the regression forecast models (see Exhibit 2). This could suggest that as some of these
nations face inflation, or even devaluation, pressures perhaps there is a flight to alternative assets, like
crypto-currencies, to protect investor worth.
Table 2: Correlation Results
After analyzing the correlation of each superclass asset with Bitcoin and Ether (see above Table 2), we
chose the most significant commodity from the transformable asset category and the most significant
fiat currency from the store of value asset by finding the individual assets with the lowest p-values (see
Exhibit 3). We accomplished this by running several multivariate regressions against five years of
historical Bitcoin prices (October 7, 2011 to October 6, 2016) and then against all historical weekly prices
of Ether (August 6, 2015 to October 6, 2016). Assets were eliminated until only three variables remained
for each regression: the S&P 500 index, one statistically significant commodity, and one statistically
significant fiat currency.
Using this three-variable regression formula for each crypto-currency, we proceeded to forecast the end
of year prices for five years. The growth rate of the S&P 500 was calculated using the 10-year U.S.
treasury rate plus a 5.7% market risk premium. Growth rates for commodities and fiat currencies were
derived from prevailing prices quoted on futures markets. Values were then entered into our regression
model to calculate yearly prices of Bitcoin and Ether, which can be seen in Table 3. At the end of Year 5,
the MVP is the second most valuable (see Table 4).
Table 3: Yearly Price Comparison of Regression Forecast
BTX Correlation ETH Correlation
SPX Index 0.71922 0.5432457
Gold -0.66627 0.8710952
Palladium 0.19623 0.1843996
Neodymium -0.17775 0.7405717
Copper -0.53426 -0.2771128
Crude Oil -0.28977 0.3326146
Platinum -0.46036 0.6019956
Japan (Yen) 0.52740 -0.8788721
New Zealand (Dollar) -0.13500 0.7347087
Norweigan (Krone) 0.42441 -0.3979021
Czech Repubic (Koruna) 0.39868 -0.4836093
Romanian (Leu) 0.20064 -0.2590778
Argentina (Peso) 0.65229 0.8016911
Hungary (Forint) 0.32231 -0.4518543
China (RMB) 0.11155 0.7230970
Great Britain (Pound) -0.09889 -0.7360760
Euro -0.14748 0.4467235
Annual
Return Rate Year 0 Year 1 Year 2 Year 3 Year 4 Year 5
SPX Index 7.43% 2,161.04 2,321.61 2,494.10 2,679.41 2,878.49 3,092.36
Gold 0.14% 1,268.90 1,270.69 1,272.49 1,274.29 1,276.09 1,277.89
Argentina Peso 1.53% 15.19 15.42 15.66 15.90 16.14 16.39
Ether Value 12.98$ 13.77 15.94 18.26 20.74 23.38
SPX Index 7.43% 2,161.04 2,321.61 2,494.10 2,679.41 2,878.49 3,092.36
Palladium -1.74% 668.70 657.04 645.59 634.33 623.27 612.41
Euro 3.45% 1.12 1.16 1.20 1.24 1.28 1.33
BTX Value 610.82$ 737.23 1,015.98 1,311.09 1,623.69 1,954.97
Table 4: Portfolio Value Comparison of Regression Forecast
Back-Testing
The next method applied was a back-test of the four portfolio strategies to weekly historical prices. The
time range for this test was from April 7, 2016 to October 6, 2016. While the MVP finished third in this
test (see table 5), the MVP had the least volatility of the four strategies (see table 6). It is encouraging to
note that the MVP is only 27 basis points short of the return of the all-Ether portfolio and has less than
half its volatility.
Table 5: Portfolio Value Comparison of Back-Test
Table 6: Weekly Return Statistics Comparison of Back-Test
Another piece of evidence supporting the importance of minimizing portfolio variance is the lack of
prevailing movements in the week-to-week price changes from August 6, 2015 to October 6, 2016. Table
7 illustrates the four possible price-changing combinations of Bitcoin and Ether and their respective
probabilities. While the event that both crypto-currencies increase is most likely, there is an even
greater chance that one or both crypto-currency prices decrease (sum of the remaining three events).
Minimizing the exposure to these downturns becomes more important once this evidence is considered.
Table 7: Probability of Weekly Price Changes
Year 0 Year 1 Year 2 Year 3 Year 4 Year 5
MVP Portfolio 1,000,000.00 1,158,217.05 1,518,324.25 1,900,004.17 2,304,758.63 2,734,196.41
100% ETH 1,000,000.00 1,060,755.87 1,228,350.52 1,407,114.65 1,597,862.21 1,801,467.34
100% BTX 1,000,000.00 1,206,947.64 1,663,311.11 2,146,448.93 2,658,206.84 3,200,560.95
50/50 Portfolio 1,000,000.00 1,133,851.75 1,445,830.81 1,776,781.79 2,128,034.52 2,501,014.14
Date Ether Price BTX Price MVP Portfolio 100% Ether 100% BTX 50/50 Portfolio
4/7/2016 8.07 422.00 1,000,000.00 1,000,000.00 1,000,000.00 1,000,000.00
10/6/2016 12.98 610.82 1,501,102.60 1,608,426.27 1,447,440.76 1,527,933.51
MVP Portfolio 100% Ether 100% BTX 50/50 Portfolio
1.56% 1.83% 1.42% 1.63%
6.46% 14.23% 9.04% 7.45%Average Weekly Volatility
Average Weekly Return
P(X)
ETH and BTX Up 18 30.00%
ETH and BTX Down 11 18.33%
BTX Down/ ETH Up 14 23.33%
BTX Up/ ETH Down 17 28.33%
Total 60 100.00%
# of Events (X)Type of Event
Monte Carlo Simulation
The final method was to run a 52-week Monte Carlo simulation using Excel’s random number generation
tool simulating a normal distribution of returns (Z). These randomly generated returns were then log-
normally transformed to replicate Bitcoin and Ether prices using the following equation where S is the
price at time t:
( 1) ( )* ZS t S t e
The mean (µ) and sigma (σ) for the above equation were calculated from the weekly returns of both
crypto-currencies from April 7, 2016 to October 6, 2016. Three thousand iterations were run, and the
weekly average was calculated. Table 8 shows average final week prices and portfolio values. Table 9
once again confirms that the MVP has the lowest volatility.
Table 8: Portfolio Value Comparison of Monte Carlo Simulation
Table 9: Weekly Return Statistics Comparison of Monte Carlo Simulation
Conclusion
Ether and Bitcoin are examples of an exciting new asset class that offers significant upside potential.
The potential of Blockchain technology is impressive, and we believe that Ether and Bitcoin, as they are
designed for different purposes, can coexist in the future. Despite the potential of these technologies,
marked volatility remains in the market for these crypto-currencies. To partially offset this projected
volatility, we optimized a portfolio of these two assets to minimize expected variance. This MVP per our
analysis consisted of 67% bitcoin and 33% ether. In addition to the mathematical analysis, we believe
this combination strikes an intuitive balance between the upside potential of Ether and the relative
staying power of Bitcoin. Furthermore, our validation models reinforced the conclusion that this
strategy offers a sound investment approach.
Date ETH Price BTX Price MVP Portfolio 100% ETH 100% BTX 50/50 Portfolio
Week 1 12.98 610.82 1,000,000.00 1,000,000.00 1,000,000.00 1,000,000.00
Week 52 56.25 1,539.85 3,125,181.08 4,333,639.02 2,520,952.10 3,427,295.56
MVP Portfolio 100% Ether 100% BTX 50/50 Portfolio
2.17% 2.88% 1.81% 2.42%
0.15% 0.31% 0.18% 0.19%
Average Weekly Return
Average Weekly Volatility
EXHIBIT 1: Public Notice Issued by Central Bank of Kenya
EXHIBIT 2: Correlation Matrix of Ether and Bitcoin (BTX) to Superclass Assets
Eth
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-0.7
2679
-0.3
7460
-0.2
9458
-0.9
4909
-0.9
5960
-0.9
6028
0.7
7231
-0.8
9490
1.0
0000
Cze
ch R
epub
0.3
9868
0.8
0778
-0.7
4546
-0.2
4453
-0.2
4769
-0.9
0070
-0.9
3525
-0.9
2857
0.8
1118
-0.8
3479
0.9
6479
1.0
0000
Rom
ani
an
0.2
0064
0.6
3288
-0.5
6472
-0.4
5883
-0.1
4910
-0.8
3832
-0.9
4194
-0.8
7717
0.6
4205
-0.8
7753
0.9
3293
0.9
4655
1.0
0000
Arg
ent
ina
0.6
5229
0.8
1087
-0.6
8041
-0.2
4653
-0.2
8336
-0.9
1082
-0.8
0854
-0.8
3462
0.6
5220
-0.6
7343
0.8
6961
0.8
0565
0.7
3509
1.0
0000
Hun
gary
0.3
2231
0.7
3316
-0.6
7065
-0.3
4815
-0.3
0651
-0.9
0680
-0.9
4438
-0.9
2722
0.7
4781
-0.8
9471
0.9
7461
0.9
7528
0.9
4799
0.8
0439
1.0
0000
Chi
nese
Yua
n0.1
1155
0.1
7954
-0.0
1782
-0.6
3648
-0.1
7223
-0.5
8264
-0.6
3245
-0.5
0566
0.0
1753
-0.6
0740
0.6
0071
0.4
8500
0.6
0811
0.6
4942
0.5
8122
1.0
0000
GB
P-0
.09889
-0.3
5250
0.2
2508
0.4
8058
0.2
2344
0.6
5945
0.7
1846
0.5
9886
-0.2
6165
0.6
6727
-0.6
8642
-0.6
2638
-0.7
1528
-0.6
7198
-0.6
8822
-0.7
6391
1.0
0000
Eur
o-0
.14748
-0.6
1442
0.5
4193
0.4
3668
0.1
7112
0.8
2127
0.9
3882
0.8
6636
-0.6
3659
0.8
8674
-0.9
2659
-0.9
4629
-0.9
8990
-0.7
1062
-0.9
5650
-0.6
0654
0.7
3319
1.0
0000
EXHIBIT 3: Summary Output for Ether and Bitcoin Regressions
Ether Regression Results
Regression Statistics
Multiple R 0.913211 R Square 0.833954 Adjusted R Square 0.825366 Standard Error 2.299073 Observations 62
ANOVA
df SS MS F Significance
F Regression 3 1539.739804 513.2466015 97.1003357 1.3735E-22 Residual 58 306.5726052 5.285734573 Total 61 1846.31241
Coefficients Standard
Error t Stat P-value Lower 95% Upper 95%
Intercept -59.923015 6.972770 -8.593861 0.000000 -73.880531 -45.965500
S&P 500 Index 0.011039 0.004274 2.582875 0.012343 0.002484 0.019594
Gold 0.026324 0.005452 4.828045 0.000010 0.015410 0.037238
Argentina/USD 0.947690 0.189687 4.996074 0.000006 0.567991 1.327390
BitCoin Regression Summary Results
Regression Statistics Multiple R 0.862519 R Square 0.743940 Adjusted R Square 0.743349 Standard Error 122.836655 Observations 1304
ANOVA
df SS MS F Significance
F Regression 3 56989535.96 18996511.99 1258.977311 0 Residual 1300 19615496.93 15088.84379 Total 1303 76605032.89
Coefficients Standard
Error t Stat P-value Lower 95% Upper 95%
Intercept -
3314.862308 79.092466 -41.911227 0.000000 -
3470.025154 -
3159.699463
S&P 500 Index 1.080850 0.018987 56.924579 0.000000 1.043601 1.118099
Palladium -1.146489 0.054429 -21.064064 0.000000 -1.253266 -1.039711
Euro/USD 1982.255847 58.907816 33.650133 0.000000 1866.691055 2097.820640
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