IN BLOCKCHAIN WE TRUST: A COMPARISON OF THE INVESTMENT

POTENTIAL OF BITCOIN AND ETHER OVER A FIVE-YEAR TIME HORIZON

EconoMIIS Team Courtney Kemp, Laura Reid, Mario Romero

Middlebury Institute of International Studies at Monterey

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Table of Contents

Introduction 4

Methodology 5

Supply and Demand Estimation Model 5

Table 1 7

Optimization Model 8

Results 9

Regression and Correlation Analyses 9

Table 2 9

Table 3 10

Historical Events Analysis 10

Figure 1 12

Graph 1 13

Figure 2 13

Graph 2 15

Discussion 16

Conclusion 17

Appendices 19

A. Abstract 19

B. Scenarios 19

C. Investment Scenarios 20

D. Optimal Portfolio Mix Results 20

E. Bitcoin Price Fluctuations Examples 20

F. Ether vs. Bitcoin Price Fluctuation Examples 22

G. Market Capitalization Graph 22

H. Velocity Demonstration 23

Bibliography 24

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4

Introduction

In 2009, Satoshi Nakomoto launched what has been called the “greatest technological

breakthrough since the Internet”1 when he anonymously released the first blockchain program

code and dubbed Bitcoin the world’s first decentralized virtual currency. Since its inception,

Bitcoin has followed an unsteady trajectory of value creation while numerous competitors -

notably Ether2 - have emerged to rival Bitcoin. Despite an influx of media buzz and venture

capital,3 digital currencies face an uncertain future amid an ever-changing global landscape.

Investment requires careful consideration of the potential use cases and risks associated with

various cryptocurrencies.

On the surface, Bitcoin and Ether do not lend themselves to direct comparison. They are

at different stages of market adoption, with Bitcoin benefiting from a first-mover advantage. The

two currencies also have the potential to act as complements rather than competitors: Bitcoin as a

store of value and medium of exchange and Ether as a technology platform powered by Ether.

Their unique uses subject them to different global risks, some unknown and others anticipated,

such as the imminent Brexit. Given the turbulent status of digital currencies and the

unpredictable global setting in general, the design of any cryptocurrency portfolio must seek to

minimize risk while still pursuing profit.

This project seeks to maximize risk-adjusted returns for a $1 million portfolio by

optimizing its Sharpe ratio. Though historical prices and volatility seem to indicate that Bitcoin

is a better investment, the forward-looking model independently suggests 30% investment in

1 Gertrude Chavez-Dreyfuss and Michael Connor, “All the rage a year ago, Bitcoin sputters as adoption stalls,”

Reuters News , December 11, 2014, accessed on Factiva on June 16, 2015. 2 “What is Ether”. Coinbase. https://www.coinbase.com/what-is-Ether, 2016 3“Bitcoin Venture Capital”, Coin Desk, September 2016

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Ether and 70% in Bitcoin based on the anticipated use cases and global risks affecting each

digital currency over the next five years. A second result of this project is the creation of the

model itself, which offers a template to estimate the future growth trajectory of each currency

and optimize the Sharpe ratio, and hence the risk-adjusted returns, for a cryptocurrency portfolio.

Methodology

In order to reconcile the differences between Bitcoin and Ether, regression and

correlation analyses were conducted to examine the cryptocurrencies’ behavior relative to global

markets and traditional commodities. This was followed by a historical event analysis to evaluate

the past impact of global shocks on Bitcoin and Ether prices. Together, these analyses informed a

supply and demand model that generated several scenarios for Bitcoin and Ether’s future prices,

reflecting various use cases and systemic risks. Finally, the Sharpe ratio optimization model

utilized the behavior of these scenarios to identify the ideal mix of Bitcoin and Ether to minimize

risk within the portfolio while maintaining profitability.

Supply and Demand Estimation Model

The supply and demand estimation model distills Bitcoin and Ether into a comparable

price per unit, with sensitivity built in for growing use cases and global shocks. Price is

calculated as follows:

Price = (Investment Demand + (Transactional Demand*Days Destroyed)) Supply

The model generates nine possible outcomes for each currency, with variations according

to the generation rate and the initial proportion of investment demand to transactional demand, as

depicted in Appendix B. Days destroyed is included as an inverse measure of velocity, although

in initial tests it was maintained as a baseline of 1. The model does allow for variation, however,

and the resulting positive impact on price is demonstrated in Appendix B.

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An endogenous relationship exists between supply and demand because Bitcoin and

Ether offer mining rewards for transaction verification. With Bitcoin supply capped at 21 million

Bitcoins, the mining reward is halved every 210,000 blocks mined.4 The next halving is expected

in July 2020, but the model builds in three possible rates for Bitcoin supply growth to reach

halving in year 2019, on schedule, and in year 2021 respectively. A similar range of three rates

was developed for Ether (Appendix C). The model also accounts for the implementation of

Ether’s proof of stake5 - beginning in year 1 but not projected to be completed until year 5 -

which reduces the mining reward to transaction fees only, effectively limiting future generation.

At the same time, the gradual implementation of POS is likely to boost investment demand

immediately because it requires staking a quantity of Ether in order to receive a verification

reward.

The first step in estimating the demand for these two currencies is to determine the initial

split between transactional and investment demand. The model defines transactional demand as

the sum of fuel for contracts, individual consumer purchases and ATM services, currency

exchange including remittances, and “vice” use cases such as shadow markets, gambling, and

money laundering.6 Investment demand represents the store of value use case alone. For Bitcoin,

studies estimate that investment demand represented 64% of the monetary base in 2015, up from

55% in 2014.7 Three scenarios were developed to estimate the 2016 ratio: 55%, 64%, and 75%.

Given that Ether is not yet considered a fully-fledged currency, and therefore is not often used as

4 Blockchain Half. http://www.Bitcoinblockhalf.com/, 2016 5 Coin Pursuit. https://www.coinpursuit.com/pages/proof-of-work-proof-of-stake-bitcoin-mining/, 2014 6 Swanson, Tim. Great Wall of Numbers . “What did Bitcoin numbers look like in 2015?”

http://www.ofnumbers.com/2016/01/10/what-did -Bitcoin-movements-look-like-in -2015/, 2015 7 Burniske, White. “Bitcoin: Ringing the bell for a new asset class”, Ark Invest, 2016

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a store of value, scenarios for its proportion of investment demand are comparatively low at 5%,

10%, and 15% (Appendix C).

Under transactional demand, each use case is assigned a starting value as a proportion of

the market capitalization for transactional demand in U.S. dollars. The proportions are intended

to reflect the current state of the market but were reconciled from several conflicting sources to

yield the proportions in Table 1. Though minimal information is available about Ether use cases,

its present use is predominantly as a fuel for contracts.

Table 1

The base growth rate for Bitcoin demand in year 1 is set as its growth rate from April to

October 2016. This base growth rate is reduced by 5% for each of the following years to account

for its slowing growth as it reaches broader adoption. Ether’s base growth rate in year 1 is set to

equal its growth rate for the same period for comparability, but due to the expected

implementation of POS, the model boosts its growth in demand beginning in year 2. In addition

to the base growth rates, additional growth or decline may be applied to a use case when

exogenous shocks are expected to alter its demand, such as in response to new technology or

regulatory signals. A similar process is conducted for investment demand with six identified

potential shocks that would create a lasting impact on price over the five-year time horizon:

Brexit and general political uncertainty, internal security breaches, the impending burst of

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China’s real estate bubble, regulatory signals for digital currencies, capital flight from emerging

markets, and a global financial crisis. The magnitudes for these events were informed by the

historical event analysis and the relative sensitivity of Bitcoin and Ether to market trends.

Optimization Model

Utilizing the estimated prices for every year under each scenario, an optimization model

is set to maximize the Sharpe ratio of the $1 million digital currency portfolio. The Sharpe ratio

is an indication of the risk-adjusted returns of a portfolio,8 and its optimization here is a means of

diversifying the portfolio. It is calculated as follows, with the risk-free rate equal to the 1.8%

yield on a 10-year U.S. Treasury bond:9

Sharpe Ratio = (Mean Portfolio Return - Risk-Free Rate)

Standard Deviation of Portfolio Return

The Solver function in Excel manipulates the proportion of each currency in the portfolio in

order to optimize the portfolio Sharpe ratio. The output serves as a recommendation for how to

divide the $1 million to minimize portfolio risk and profitably invest in the two cryptocurrencies

for the next five years. However, qualitative analysis must verify the quantitative output before

adopting it as the final strategy.

Results

Regression and Correlation Analyses

Following Ciaian et al.10 and Burniske,11 the historical price of Bitcoin was regressed on

historical prices for the Dow Jones, gold, oil, as well as the number of Bitcoin transactions, using

logarithmic transformations. With the exception of the price of oil, each of these variables

8 Investopedia. http://www.investopedia.com/terms/s/sharperatio.asp, 2016 9 Bloomberg. http://www.bloomberg.com/markets/rates -bonds/government-bonds/us, 2016 10 Pavel Ciaian, Miroslava Rajcaniova, d'Artis Kancs. “The Economics of Bitcoin Price Formation”, Cornell

University Library, 2014 11 Burniske, White. “Bitcoin: Ringing the bell for a new asset class”, Ark Invest, 2016

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demonstrate a statistically significant effect on the price of Bitcoin (Table 1). These findings

were supported by a correlation matrix of actual prices (Table 2) and indicate that, particularly

with regards to specific market exchanges, Bitcoin is treated as a means for hedging investment

and a potential safe haven in the event of an economic downturn.

Table 2

Cryptocurrency-Asset Regression Analysis12

Table 3

Cryptocurrency-Asset Correlation Analysis1314

If global recessions or a series of isolated Black Swan events occur, consumers may be driven to

adopt Bitcoin over competitors at even higher rates. Notably, the Shanghai Composite Exchange

12 Note: Optimal lag structures were tested for explanatory and independent variables resulting in there no

materially significant differences detected. Data are from quandl.com. 13 The Wall Street Journal. http://online.wsj.com/mdc/public/page/mdc_international.html?refresh=on, 2016 14 Blockchain Info. https://blockchain.info/charts/total-Bitcoins?timespan=all, 2016

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exhibited an inverse relationship with the price of Bitcoin. Since 77% of the Bitcoin trading

volume is exchanged in Chinese yuan,15 this tendency to invest in Bitcoins during economic

slumps in the Chinese market is expected to have a substantial impact on future prices.

Historical Events Analysis

Since the first genesis block kicked off Bitcoin’s blockchain in 2009, Bitcoin has become

the largest currency of its kind in total market value. The coin’s price, however, has experienced

tremendous volatility since its inception (Figure 1, Graph 1, and Appendix E). Analysis of Coin

Desk’s price index shows that Bitcoin responds most to an ecosystem of risks around :

Government Regulation: Government regulation has proven to cause significant fluctuation in

Bitcoin’s price.

Security Breaches: Both Ether and Bitcoin have experienced hacks, but Ether is widely

considered more secure. A host of large banks, technology companies, and financial service

firms have a vested interest in the development of Ether technology16 17 18 19. On the other hand,

Bitcoin’s structure has been questioned due to the ability of miners to obtain over 50% of mining

nodes which allows select mining pools to have the community influence to alter Bitcoin in their

favor. Interestingly, the conducted price analysis shows that security breaches seem to have

15 "Global Market for Bitcoin Trading Volume, 2015." Market Share Reporter. Ed. Robert S. Lazich and Virgil L. Burton, III. 26th ed. Farmington Hills, Mich.: Gale Group, 2016. 844 pp. 2 vols. Gale Directory Library. Gale. Middlebury Institute of Intl

Studies. 17 Oct. 2016 <http://find.galegroup.com/gdl/start.do?prodId=GDL>. 16 Pete Rizzo, “IBM Director Declares 'We’re All in on Blockchain’,” Coin Desk, February 10, 2016 17 Justin Reynolds, “Move over, Bitcoin: Ether is about to change everything,” KNote 18 Robert Hackett, “Why J.P. Morgan Chase Is Building a Blockchain on Ether,” Fortune, October 4, 2016 19 Andrew Quentson, “CNN catches up with the CEO of CHBTC, one of China’s largest exchanges,” CNN, August

23, 2016

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resulted in a slowly decreasing impact over time, indicating that Bitcoin users are increasingly

accepting of occasional security breaches as they learn how the market behaves. As the volume

of users and investors increases, the overall value of the cryptocurrency will also increase,

allowing the market to sustain shocks more easily.

Internal Governance: Though Bitcoin began as a wholly-decentralized model, programmers have

initiated “hard forks” to correct or improve upon the system, which have been perceived as

violations of the public ledger’s core principal20. Comparatively, resistance from the Ether

community to similar instances has been minimal.

External Shocks: Capital flight and capital controls could become a particularly significant factor

in the future, especially when the volume of capital stored in emerging markets is taken into

account - particularly those of the BRIC economies21. As global uncertainty and mistrust of

traditional banks continue to grow, so might capital flight.

20Bailey Reutzel, “Preparing for a Bitcoin Hard Fork,” CoinDesk, September 14, 2016 21Volatility behavior of BRIC capital markets in the 2008 international financial crisis,“ African Journal of

Business Management, June 14, 2014

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Figure 1

BTC Historical Price from January 2013 - October 2016

Graph 1

22 23 24 25

22 Cryptocompare. https://www.cryptocompare.com/coins/eth/charts/USD , 2016 23 The Wall Street Journal. http://online.wsj.com/mdc/public/page/mdc_international.html?refresh=on, 2016 24 Blockchain Info. https://blockchain.info/charts/total-Bitcoins?timespan=all, 2016 25 Etherscan. https://Etherscan.io/, 2016

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Simply because the two blockchain technologies are popularly combined into one group,

however, does not mean that they move in tandem or respond to events in the same manner (see

Figure 2 and Appendix F).

Figure 2

BTC and ETH Historical Price from February to October 2016

A historical event analysis was able to provide a concrete anchoring for the estimation of

potential magnitude of future global shocks. Two events in particular serve as proxies for both

market crashes and geopolitical uncertainty. The Brexit referendum vote was planned for June

23rd, 2016. Prior to the vote, there is a clear increase of Bitcoin’s market capitalization of almost

$3 billion from $9.6 billion on June 11, to $12 billion on June 19. Although this spike partially

moderated just before the vote, the subsequent increase following the “yes” vote led to a

stabilization of about $10 billion market cap. As of now, the United Kingdom expects to trigger

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Article 50 in March 2017. While the announcement is unlikely to have the same type of surprise

effect as the referendum, the anticipated economic change could create significant capital flight

toward safe-haven assets that are considered to be safe from drastic market disruptions and

crises, in particular if they are considered to be highly liquid. In addition, by its unpredictable

and geopolitical nature, the Brexit provides a clear proxy for other potential geopolitical crises,

such as the ongoing rise of populist political movements in Europe and the U.S., as well as

amplification of other global conflicts.

The 2015 Chinese stock market crash provided a baseline understanding of how financial

market shocks influenced cryptocurrencies. Data shows that on July 10, the Shanghai Composite

Exchange dropped by almost 30% while the value of Bitcoin rose by over 20% (Graph 2).

Graph 2

Price Change Comparison: Bitcoin vs. Shanghai Composite Exchange July 201526

26 Samman, George. Coin Telegraph. “ China’s Stock Market Freefall a Boon for Bitcoin”.

https://cointelegraph.com/news/chinas -stock-market-freefall-a-boon-for-Bitcoin, 2015

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These dynamics support the general hypothesis that Bitcoin acts as a significant store of value

and is used to hedge against negative shocks to equity markets. Running regressions with

logarithmic transformation of the data, determined that the value of the Shanghai Composite

Exchange statistically significantly influenced the price of Bitcoin in an inverse relationship. The

2015 crash was considered relatively small, yet linked to a significant buildup of instability

within the Chinese economy, and the possibility of future systemic correction cannot be ignored.

By using the historical data of the relatively small 2015 Chinese stock market crash as a proxy, it

can be estimated that the magnitude of a larger Chinese stock market crash in the future could

have up to a 20% lasting impact on global stock markets. In addition to the potential China real

estate collapse, there are other signals that other financial crises27 could occur, such as the

growing distrust in Wells Fargo or the litigation currently underway against Deutsche Bank

which could create waves of global financial instability. Understanding the impacts of historical

data on cryptocurrency prices provides us with baseline data in examining long term impacts of

these financial shocks.

The optimization model resulted in a maximum Sharpe ratio of 17.36 for a portfolio mix

of 30% Ether and 70% Bitcoin. This resulted in an ending value of $6,739,610, representing a

574% return. This return is within the range typically expected by conservative venture capital

firms for a five-year time horizon.

Discussion

Despite the results from the optimization model, there are various challenges that Ether

must overcome before it can truly rival Bitcoin as a better risk-adjusted investment. First, Bitcoin

has the advantage of being a first mover and benefits from a flywheel effect that results in its

27 Bitcoinist.net. “What will happen to Bitcoin when the Economy Goes Bust?”.

http://insideBitcoins.com/news/what-will-happen-to-Bitcoin-when-the-economy-goes-bust/35243, 2015

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self-perpetuation. In addition, Bitcoin has established itself as being highly liquid, this is a

quality that Ether has yet to obtain, in part because its volume and number of transactions pales

in comparison to Bitcoin’s. Yet, Ether has taken steps in order to improve its liquidity, such as

through the establishment of ATMs.

Moreover, the advantage afforded to Ether as the first cryptocurrency to execute ‘smart

contracts” may not actually result in additional creation for Ether. While smart contracts are

gaining traction among large financial institutions, for example, large movers are utilizing

private rather than public blockchains that generate and utilize their own coins to fuel the

contracts, which does not increase stored value for Ether. If the technology were proprietary,

then the potential return would be even greater than our model predicts but this remains unlikely.

Finally, with these use cases, Ethereum has opened doors for other players to develop even more

innovative and flexible technology to compete and potentially overtake it. Indeed, it has already

experienced several attacks that have delayed its progression to the third phase.

Conclusion

Prior to crafting the final projection, an optimization model based on historical prices

from the last six months determined that the optimal split would be 91% Bitcoin and 9% Ether

with a Sharpe portfolio ratio of 0.06. Considering that cryptocurrencies are so new and have high

volatility, their past prices are poor indicators of their future outlook and therefore are not

reliable in particular when considering the five-year time horizon. The new, forward-looking

recommendation, which is based on a future projection based on the global landscape is a better

depiction of how to maximize risk-adjusted return and resulted in an optimized recommendation

of 70% investment in Bitcoin and 30% investment in Ether. The model, with its various

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scenarios, successfully takes many of the qualitative uncertainties that strictly a strictly

quantitative account would have overlooked.

Appendices

A. Abstract Ether and Bitcoin are in a race to dominate the cryptocurrency market, and investors are scrambling to

decide which currency yields the better risk-adjusted investment. Both cryptocurrencies have significant

growth projections, but uncertainty exists around Ether’s prospects as well as its current weakness as a

store of value. In valuing Bitcoin and Ether, a regression and correlation analysis examined the

relationships of the currencies with other asset classes, and a historical event analysis produced a model

adjusted for global shocks. These analyses permit the development of a number of scenarios, which can

be used to optimize the portfolio Sharpe ratio. Further qualitative research regarding strengths,

weaknesses, and uncertainties led us to conclude that Kraken should invest 30% in Ether and 70% in

Bitcoin. Although large companies are investing in Ether technology, they will be largely using private

blockchains, so it is doubtful that the number of transactions they bring will create a significant increase

in value when compared to Bitcoin’s established market share.

B. Scenarios

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C. Investment Scenarios

This table describes the ranges of proportion of investment and supply growth informing the nine different scenarios for both Bitcoin and Either. D. Optimal Portfolio Mix Results

E. Bitcoin Price Fluctuations Examples

Government Regulation: Bitcoin’s price responded favorably in November 2013 when the US

Senate declared the coin to hold great promise and innovation that should advance unhindered by

law enforcement and undue regulation28 and China accepted Bitcoin as a legal economic

activity.29 Favorable regulatory environments in both of Bitcoin’s major markets energized

consumers and spurred trade volumes, leading to an increase in price from $685.75 to $1075.16

28 Full Committee Hearing, “Beyond Silk Road: Potential Risks, Threats, and Promises of Virtual Currencies,” US

Senate, November 18, 2013 29 Adam Century, “Bitcoin gets a cautious nod from china’s central bank,” The New York Times , November 22,

2014

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over a 10-day period. Similarly, when the European Court of Justice ruled that the exchange of

virtual currencies was not subject to value-added-tax (VAT) in the European Union, Bitcoin and

its alternatives were classified as a currency rather than mere goods or property30, and Bitcoin’s

price rose nearly $50 over the next 10 days.. On the other hand, regulation has also caused the

coin’s price to decrease. When China declared Bitcoin not to be a currency in December 2013, it

imposed its first policy restraints on Bitcoin31 and prices sank dramatically from $1022.37 to

$839.93 over a 10-day period. Prices rebounded almost $100 next April when China updated its

restrictions against the coin’s exchanges32.

Security: In January 2015, for example, unidentified hackers were able to steal 18,866 Bitcoins

from Bitstamp33 34, resulting in the coin’s price plummeting over $75 in the 10 day period after

the hack. More recently, Bitfinex also declared that about 120,000 Bitcoins from customer

accounts had been stolen following a security breach, a sum worth about $72 million. The price

of Bitcoin plummeted nearly 20% the day of the announcement before beginning a gradual

recovery over the next two weeks35 .

Internal Governance

For example, when ex-Google developer Mike Hearn declared that Bitcoin had failed and that he

was leaving the community on January 14, 2016, Bitcoin price fell $50 within 24 hours. Hearn

cited censorship in the Bitcoin communication, the centralization of mining in China, and the

30 Matt Clinch, “Bitcoin now tax-free in Europe after court ruling,” CNBC, October 22, 2015 31 Gerry Mullany, “China Restricts Banks’ use of Bitcoin,” The New York Times , December 5, 2013 32 Jon Southurst, “Bitcoin Price Drops 10% as Chinese Exchanges Stop Bank Deposits,” Coin Desk, April 10, 2014 33 Stan Higgins, “Bitstamp Claims $5 Million Lost in Hot Wallet Hack,” Coin Desk, January 5, 2015 34 Stan Higgins, “Details of $5 Million Bitstamp Hack Revealed,” Coin Desk, July 1, 2015 35 Stan Higgins, “”The Bitfinex Bitcoin Hack: What We Know (And Don't Know),” Coin Desk, August 3, 2016

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unwillingness of Bitcoin’s current core developers to increase the limit on Bitcoin’s block size as

his main reasons for leaving the community, spurring consumer uncertainty in the coin36. 37

F. Ether vs. Bitcoin Price Fluctuation Examples

The G-2038 meeting caused an increase in the price Bitcoin yet had much less of an impact on the

price of Ether. On the other hand, the release of the Homestead, Ether’s newest set of software

and network improvements, resulted in no significant change for Bitcoin but was a significant

boon for Ether. In other cases, as with the announcement of the Brexit referendum results and the

implementation of Chinese capital controls, both Bitcoin and Ether prices move together. From

these examples, it can be inferred that the asset properties of each of the cryptocurrencies cause

them to react differently in certain circumstances even within events that would be positive for

both.

36 Samburaj Das, “Mike Hearn Says Bitcoin Has Failed and Sees a Price Plunge in the Future,” Coin Desk, January

15, 2016 37 Mike Hearn, “The resolution of the Bitcoin experiment,” Medium, January 14, 2016 38 Tyler Durden, “Bitcoin Surges Almost 10% On Heavy China Buying Amid G-20 Chatter,” Zero Hedge,

September 4, 2016

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G. Market Capitalization Graph

394041

H. Velocity Demonstration

Velocity is a measure of the frequency at which one unit of currency is transacted, and

days destroyed is its inverse. If velocity increases, more coins will be needed to support the same

level of transactional volume. If velocity decreases, price per coin will increase and the number

of days destroyed will also rise. This relationship is built into the supply and demand model, as

demonstrated in the table below. An estimate of the velocity elasticity of Bitcoin price obtained

from regression analysis shows that for every 100% increase in days destroyed, Bitcoin price

increases by approximately 110%. Although beneficial in driving the price of a currency, the

relationship between velocity and price can hurt in the long run. As demand for transactions rises

over time, a tension may be created between consumers who appreciate high velocity of

39 Tradeblock . https://tradeblock.com/markets/index/, 2016 40 Blockchain Info. https://blockchain.info/charts/total-Bitcoins?timespan=all, 2016 41 Kaiko. https://www.kaiko.com/statistics/market-capitalization?range=180d, 2016

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transactions and miners who seek to maximize price. This latency issue has plagued Bitcoin for

the past few years.

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