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Chunqi Xu (220000)

Instructor: Dr. Martin A. Negron

ANLY 515-51-R-2018/Spring

12 April 2018

Bitcoin Crash Simulation and Analysis

A brief description of the event and objectives

Bitcoin is a kind of cryptocurrency and payment system around the world. It is the first

decentralized digital currency, and the system operates without any single administrator or

central bank. As of February 2015, about one hundred thousand merchants accepted

Bitcoin as payment. Research estimates that in 2017, there will be 2.9 to 5.8 million users

using a cryptocurrency wallet, and most of them will use Bitcoin.

As all cryptocurrencies, Bitcoin is subject to market fluctuations, where lies potential for

large gains but also significant losses. Just a few years ago, the only people interested in

Bitcoin were Computer Scientists. If you tried to talk to anyone else about cryptocurrencies,

they would surely have had a very confused look on their faces. In recent years, the growth

of Bitcoin, not only its market value growth, but also its popularity and general

understanding by the wider community have been phenomenal.

But going into 2018, Bitcoin's price has dropped significantly, from around $19,900 on 17th

December 2017 right down to $8,036 on 4th February 2018. Each time Bitcoin's price

crashes, there is a very real chance that it could mean the end of Bitcoin, regardless of what

anyone says you need to be aware of this risk. After the slumps of January and February, it

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seems that the first significant Bitcoin price crash has just arrived, taking the price well

below the $10,000 mark that makes many people feel safe for the sixth time this year.

So regardless of how many people say a current crash is the last, it might or might not be,

and no-one really knows for sure.

Risks associated with the event

If Bitcoin crash happens, then some stocks of computer hardware companies will follow

Bitcoin downward.

If Bitcoin crash is so heavy that it influences the Cryptocurrency Ecosystem, then the

prices of most cryptocurrencies will also decrease.

If the economic conditions become bad, then the Bitcoin crash will be more likely to

happen.

Research Questions

What’s the percentage of some hardware company’s stock price that is going to be

decreased for after the Bitcoin crash?

Will the Bitcoin crash when the economic conditions are good?

Variables used for the model and how the values were determined

To solve my research questions, I choose ten variables.

1. Bitcoin (BTC - USD) price

The historical data of Bitcoin price

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2. BTCS Inc (BTCS) stock price

BTCS, Inc. (also called Bitcoin Shop, Inc.) is a publicly traded company based in the US,

whose stated line of business is development of applications related to blockchain

databases and digital currencies.

3. Bitcoin Services, Inc. (BTSC) stock price

Bitcoin Services, Inc. engages in the Bitcoin and mining of other crypto currencies. The

company offers Bitcoin escrow service and Bitcoin mining services in order to validate

Bitcoin transactions and provide the requisite security for the public ledger of the

Bitcoin network. It is also involved in the development and sale of blockchain software.

4. Litecoin (LTC - USD) price

Litecoin is a peer-to-peer cryptocurrency and open source software project. Creation

and transfer of coins are based on an open source cryptographic protocol and are not

managed by any central authority. The coin was inspired by, and in technical details is

nearly identical to, Bitcoin (BTC).

5. Overstock.com, Inc. (OSTK) stock price

Overstock.com, Inc. is an American internet retailer. The company offers home and

garden products, including furniture, garden, and other related products; jewelry and

watches; clothing and accessories; electronics and computers; and other products and

services. The company was introduced to blockchain technology in 2014 as the first

major retailer to accept Bitcoin.

6. Microsoft Corporation (MSFT) stock price

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Microsoft Corporation is an American multinational technology company. It develops,

manufactures, licenses, supports and sells computer software, consumer electronics,

personal computers, and services. The company announced that users can buy content

with Bitcoin on Xbox and Windows store.

7. Expedia Group, Inc. (EXPE) stock price

Expedia Group, Inc. is a global travel company. Its websites, which are primarily travel

fare aggregators and travel metasearch engines, include Expedia.com, Hotels.com,

Hotwire.com, CarRentals.com, trivago, Venere.com, Travelocity, Orbitz, and HomeAway.

The company accepts Bitcoin for hotel bookings.

8. S&P 500 (^GSPC) historical data

S&P 500 is an American stock market index based on the market capitalizations of 500

large companies having common stock listed on the NYSE or NASDAQ. It is one of the

most commonly followed equity indices, and many consider it one of the best

representations of the U.S. stock market, and a bellwether for the U.S. economy.

9. Gross Domestic Product (GDP) historical data

Gross domestic product (GDP) is a monetary measure of the market value of all final

goods and services produced in a period (quarterly or yearly) of time.

10. Unemployment Rate

The unemployment rate is the share of the labor force that is jobless, expressed as a

percentage. When the economy is in poor shape and jobs are scarce, the

unemployment rate can be expected to rise. When the economy is growing at a healthy

rate and jobs are relatively plentiful, it can be expected to fall.

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The independent variables can be divided into four categories.

1) Computer company providing support for Bitcoin:

BTCS Inc (BTCS)

Bitcoin Services, Inc. (BTSC)

2) Other cryptocurrency

Litecoin (LTC - USD)

3) Company accepting Bitcoin

Overstock.com, Inc. (OSTK)

Microsoft Corporation (MSFT)

Expedia Group, Inc. (EXPE)

4) Economic condition

S&P 500 (^GSPC)

Gross Domestic Product (GDP)

Unemployment Rate

The process used to develop the model (simulation)

Since the first stock price of Litecoin is on 10/23/2013, which is the latest of all variables, I

choose the period range of the data set from 10/23/2013 to 3/29/2018. For Bitcoin and

Litecoin, there are 1619 records, while for the stock price of BTCS Inc, Bitcoin Services, Inc.,

Overstock.com, Inc., Microsoft Corporation, Expedia Group, Inc. and S&P 500 index, there are

only 1116 records. The reason is that Bitcoin and other cryptocurrency like Litecoin are traded

via online platforms, so we can have their daily prices, including Saturday and Sunday.

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However, the stocks of other companies are traded through stock exchanges, which are closed

at weekend. In addition, the stock price of Bitcoin Services, Inc. is incomplete, with some

missing data. To make up the differences in record number of variables and the missing data,

the method of simulation is necessary to develop the model.

For BTCS Inc, its stock price covers six years, from 2013 to 2018. Firstly, I calculate the mean

and standard deviation of its adjusted close stock price (adjusted for both dividends and splits)

for every year.

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I assume that the daily stock price of BTCS Inc is normally distributed. Then I simulate its daily

stock price with the mean and standard deviation calculated, including Saturday and Sunday in

2013, 2014, 2015, 2016, 2017, and 2018 respectively.

Since the simulated results will change every time we click on the Excel, I copy the simulated

results and paste them as values into the next column.

Because the normal distribution is symmetrical, I get some negative values from simulation.

However, we will never have a negative stock price. To solve this problem, I use another

function to make all the simulation values positive.

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When the value in column O is positive, I will use that value; when the value in column O is not

positive, I will use the mean value of that year instead.

I use the same simulation method and get daily stock price of Bitcoin Services, Inc.,

Overstock.com, Inc., Microsoft Corporation, Expedia Group, Inc. and indexes of S&P 500 from

2013 to 2018.

For GDP, there is a little difference because I can only get the yearly data. So I divide the yearly

GDP by 360 to get the daily mean value of every year and set the standard deviation to be 1.

The following steps are the same with stock price.

Although I only get the monthly data of unemployment rate, I calculate the mean and standard

deviation of monthly data for every year and do the simulation as for stock price, because the

unemployment rate is not cumulative.

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At last, I get the 10 variables with the same number of records.

Findings description

After the simulation, I perform the regression analysis to find out the relationship between the

price of Bitcoin and the other independent variables.

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The Multiple R, which is the correlation coefficient, tells us how strong the linear relationship is.

According to the regression result, the Multiple R is 0.968, meaning a strong positive

relationship.

Since there is more than one independent variable, I use Adjusted R Square instead of R Square,

which adjusts for the number of terms in the model. The Adjusted R Square is 0.937 in this

model, indicating that the model explains more than 90% variability of the dependent data

around its mean. In other words, more than 90% of the values fit the model.

According to the third table, the linear regression equation of the model is

BTC-USD = -16597.47 + 3.04*BTCS + 1058.18*BTSC + 56.41*LTC-USD - 13.97*OSTK - 2.55*

MSFT + 3.79*EXPE - 0.07*^GSPC + 0.30*GDP (M$) + 355.52*UNEMPLOYMENT

The p-value in the third table for each variable tests the null hypothesis that the coefficient is

zero. We can reject the null hypothesis if the p-value is less than 0.05. That is, an independent

variable with a low p-value is likely to be a term can be kept in the model because the changes

in that independent variable are meaningful to the changes in the dependent variable. The p-

value for Bitcoin Services, Inc. (BTSC), Microsoft Corporation (MSFT) and S&P 500 (^GSPC) are

greater than the alpha level of 0.05, indicating that they are not statistically significant and can

be removed from the model. So I do the regression analysis again without these three variables

and the new linear regression equation is:

BTC-USD = -17078.42 + 3.12*BTCS + 56.33*LTC-USD – 14.07*OSTK + 3.95*EXPE + 0.30*GDP

(M$) + 376.67*UNEMPLOYMENT

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The table shows that there is a strong positive relationship between the price of Bitcoin and

independent variables, and most of the values fit the model.

Findings analysis and research questions answer

1. What’s the percentage of some hardware company’s stock price that is going to be

decreased for after the Bitcoin crash?

To answer this question, I keep the value of independent variables constant and use the 2018

mean value of them, except BTCS Inc (BTCS). Since market crashes are generally defined by an

abrupt and rapid decline of 20% or more, I define the Bitcoin crash as that the price of Bitcoin

declines by 20% comparing to its average value in 2018, which will be 10530.44*(1 – 20%) =

8424.352. Substitute the values into the model, we can get that

8424.352 = -17078.42 + 3.12*BTCS + 56.33*189.783 – 14.07*62.39 + 3.95*116.15 +

0.30*53850.57 + 376.67*4.1

Then,

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BTCS = -791.086

It seems that after Bitcoin crash, the stock price of BTCS Inc (BTCS) will be -791.086. However,

as we all know, the stock price will never be negative. So we can say that after the Bitcoin crash,

the stock price of some hardware company will decrease dramatically.

2. Will the Bitcoin crash when the economic conditions are good?

Now there are only two variables in the model indicating economic conditions, one is GDP, and

another is unemployment rate. The healthy GDP growth rate is one that is sustainable so that

the economy stays in the expansion phase of the business cycle as long as possible. The ideal

GDP growth is between 2-3 percent, and the natural rate of unemployment will be between 4.7

percent and 5.8 percent. I choose 2.5% as GDP growth rate and 5.25% as unemployment rate in

good economic conditions, so the GDP will be 53850.57*(1+2.5%) = 55196.83. Then I substitute

the 2018 mean values of other variables into the model and get that,

BTC-USD = -17078.42 + 3.12*0.10 + 56.33*189.783 – 14.07*62.39 + 3.95*116.15 +

0.30*55196.83 + 376.67*5.25

So BTC-USD = 11729.9

It looks like that Bitcoin will not crash when the economic conditions are good.