An Analysis on the Impact of Commodity Prices and Exchange Rates on the Price of Bitcoin

Dr. Alicemani*, Likithakariappa P.

Department of Commerce, Christ University, Bangalore-560029

*Corresponding Author E-mail: likithakariappa412@gmail.com

ABSTRACT:

Bitcoin is the first decentralized cryptocurrency to be traded. There has been drastic increase in the price of bitcoin since 2013. Granger Causality analysis has been carried out to examine whether the price of commodities and the exchange rates helps in predicting the future price of bitcoin. For this study, the price of bitcoin, commodity prices and exchange rates have been considered from Jan 2103–Sep 2017.After the analysis it can be concluded that the price of commodities and the exchange rates does not help in predicting the future price of bitcoin. The past data of the price of bitcoin helps in predicting the future price of copper and British pound exchange rate with that of U.S dollars.Using Regression analysis, it can be determined that when the price increases by 0.0084 dollars there is one unit increase in the volume of transaction .Using variance analysis it can be observed that the price of bitcoin is more volatile compared to the price of commodities and the exchange rates.

KEYWORDS: Bitcoin price, commodity price, Granger Causality, Exchange rate, regression analysis, bitcoin exchange.

INTRODUCTION:

During the medieval times, gold, silver and copper coins were used as the mode of currency for trading purposes. Due to the passage of times, it shifted to paper money, plastic cards, and digital wallets now to bitcoin.This shift in the mode of currency for trading was to reduce the cost of transaction and avoid the risk of physical money. Bitcoin has brought a revolution in the field of cryptocurrency as it is the first cryptocurrency to be traded and used. It is a virtual currency, which is controlled by its developer, Satoshi Nakamato. It was introduced in the year 2009.

Bitcoin is a virtual currency or commodity which does not have a central authority or a bank as the transaction takes place directly between the users.

The number of bitcoins in circulation is limited to 21 million. All the transactions that take place in bitcoin are transparent as it is recorded in open ledger called as ‘’Blockchain”. Currently bitcoin is being regulated by commodity future trading commission (CFTC) but it is not confirmed if CFTC will permanently take up the responsibility of regulating bitcoins.

How to get bitcoins? Bitcoin can be earned by exchanging the fiat currency with bitcoins in various bitcoin exchanges. Bitcoin ATMs was introduced in the year 2016.

This ATM machine empowers both purchase of bitcoin and also reclamation of bitcoin for money. It can be earned by accepting payments in bitcoins and through mining process. Mining is an attempt to verify whether the sender is the real proprietor and has not sent to numerous clients. There is a fixed reward for mining.In the year 2010 it was 50 bitcoins per block, 2014 -25 bitcoins and now it is decreased to 12.5 bitcoins. The reward is halved every four years. The price of bitcoin in the year 2011 was 5 dollarsand currently in the year 2017, the price is approximately 4000 dollars.There has been a drastic increase in the price of bitcoin since 2013. Therefore, this study has been conducted to examine if there is a relationship between bitcoin price with that of the commodity price and the exchange rates.

REVIEW OF LITERATURE:

(Lio, 2016)Is trying to find out if bitcoin has a systematic risk by using CAPM model and what is the proportionof bitcoin that must be included in the investment portfolio by using mean variance portfolio. His findings show that bitcoin does not have a systematic risk and the proportion of bitcoin that must be included in the investment portfolio is 4.4% to 21.5%.

The author studies the determinants of bitcoin price in the long run and short run using ARDL model ,granger causality and concludes that in the long run volume of transaction positively influence the price of bitcoin . Gold price and financial stress index have negative impact on the price of bitcoin.

(Li, 2016) use Granger Causality test to test the efficient market hypothesis of bitcoin return by examining the relationship between social media information and the bitcoin returns .social media information is collected from twitter which contains more than 1,30,000 bitcoins related tweets. He concludes that bitcoin return in short run is affected by market sentiment information.

(woo, Gordon, and laralov, 2013) Examines the relationship between the volume of transactions in all bitcoin exchanges and the price of bitcoin and concludes that the correlation between the volume of all bitcoin exchange in China and the price of bitcoin is high and rising.

(Hill, 2016) Study the advantages and drawbacks of bitcoin. He states that after the price surge to $1000 on December 2013 there is a billion dollar increase in venture capital funding in bitcoin payment process, mining operation and bitcoin exchanges.

(Marse, 2015) Talks about coming up with a regulatory authority for bitcoin to avoid malpractices, black marketing and money laundering. Currently CFTC regulates bitcoin and other cryptocurrencies. The dilemma is if CFTC will permanently take up the in charge to regulate the bitcoin, Will It regulate it has a foreign exchange transaction or has a commodity?

(Negurita, 2014) Is of the opinion that the “occurrence of bitcoin is natural” because it was introduced to decrease the cost of printing bank notes. He explains about the five risks that are associated with bitcoin, i.e. difficulty in determining the intrinsic value, unidentifiable, high inflation, illicit activity and high volatility.

(Turpin, 2014) explains in a very simple manner about the private and public key used in bitcoin transactions i.e. public key is the street address and private key is the door. It was advised that the government, instead of discouraging the usage of bitcoin, must come up with a regulatory authority, to strengthen the virtual currency industry.

OBJECTIVES:

1. To verify whether the price of bitcoin is caused by the price of the commodities

2. To examine the causal relationship of price of bitcoin with that of exchange rates.

3. To analyse the impact of volume of transactions on the price of bitcoin.

4. To compare the degree of volatility among the bitcoin prices, the exchange rates and the commodity prices.

RESEARCH METHODOLOGY:

For this study, data of prices of bitcoin, commodities and the exchange rates were considered. The commodities used for the study are gold, crude oil, natural gas, silver and copper because they come under the most traded commodity.

(Patterson, 2017) Exchange rate between US dollars with that of the Euro, British pound, Japanese Yen and Chinese Yen renminbi are considered on the grounds that bitcoin is exceptionally exchanged with these currencies. The duration from1 January 2012 to 31 September 2017 was considered because the price of bitcoin started gaining importance during this period. The data regarding price of bitcoin, commodity price and exchange rates are obtained from investing.com. The country that has been chosen for the analysis is the United States. Regression has been used to find the impact of the volume of transaction on the price of bitcoin.Granger causality is a statistical tool that is used to find if x causes y or y causes x i.e. if the past value of x is useful to determine the future value of y and vice versa(Foreste, 2007).

Granger causality test has been employed to check whether the price of bitcoin is caused by the price of commodities and the exchange rates. Variance analysis had been done to find out the volatility of bitcoin prices, commodity price and exchange rates and unit root test is employed to check the stationarity of the data.

ANALYSIS AND INTERPRETATION

UNIT ROOT TEST:

Before testing regression and Granger causality, assurance of stationarity should be tested. Unit root test is used to determine the stationarity of the data. The table below shows the results of unit root test of each variable, through which we can obtain the level at which the data is stationery and the t-statistic value of the data.Bitcoin price is stationery at second difference and the other variables are required to take thefirst difference to become stationery.

Table 1: unit root test of commodity price and exchange rates

PARTICULARS

DIFFRENCE

T-STATISTIC

STATIONARY STATUS

Bitcoin price

Level

2nd difference

-9.9819

Non stationary

Stationery

Copper price

Level

1st difference

-4.6904

Non stationary

Stationery

Crude oil price

Level

1st difference

-6.7009

Non stationary

Stationery

Natural gas price

Level

1st difference

-8.8019

Non stationary

Stationery

Gold price

Level

1st difference

-7.9946

Non stationery

Stationery

Silver price

Level

1st difference

-8.0547

Non stationary

Stationery

Euro

Level

1st difference

-8.2589

Non stationary

Stationery

GBP

Level

1st difference

-7.8950

Non stationary

Stationery

JPY

Level

1st difference

-7.5510

Non stationary

Stationery

Renminbi

Level

1st difference

-6.2927

Non stationary

Stationery

Table 2: Granger causality test between the price of bitcoin and price of commodities

Pairwise Granger Causality Tests

Date: 09/23/17 Time 12:38

Sample: 2012M012017M08

Lags: 2

Null Hypothesis:

Obs

F-Statistic

Prob.

COPPER_PRICE does not Granger Cause BITCOIN_PRICE

BITCOIN_PRICE does not Granger Cause COPPER_PRICE

0.60612

4.30020

0.5487

0.0179

CRUDE_OIL_PRICE does not Granger Cause BITCOIN_PRICE

BITCOIN_PRICE does not Granger Cause CRUDE_OIL_PRICE

0.06279

0.17102

0.9392

0.8432

NATURAL_PRICE does not Granger Cause BITCOIN_PRICE

BITCOIN_PRICE does not Granger Cause NATURAL_PRICE

1.01501

0.02123

0.3684

0.9790

GOLD_PRICE does not Granger Cause BITCOIN_PRICE

BITCOIN_PRICE does not Granger Cause GOLD_PRICE

1.28177

0.58907

0.2849

0.5580

SILVER_PRICE does not Granger Cause BITCOIN_PRICE

BITCOIN_PRICE does not Granger Cause SILVER_PRICE

0.97426

0.04279

0.3833

0.9581

Table 3: Granger causality test between the price of bitcoin and the exchange rates

Pairwise Granger Causality Tests

Date: 09/21/17 Time 15:05

Sample: 2012M012017M08

Lags: 1

Null Hypothesis:

Obs

F-Statistic

Prob.

EURO does not Granger Cause BITCOINPRICE

BITCOINPRICE does not Granger Cause COPPERPRICE

0.00307

1.27361

0.9560

0.2633

GBP does not Granger Cause BITCOINPRICE

BITCOINPRICE does not Granger Cause GBP

0.63270

6.55397

0.4293

0.0128

JPY does not Granger Cause BITCOINPRICE

BITCOINPRICE does not Granger Cause JPY

0.86614

0.06418

0.3555

0.8008

YEN does not Granger Cause BITCOINPRICE

BITCOINPRICE does not Granger Cause YEN

5.00908

1.35621

0.0287

0.2485

The table above presents the Granger causality results of the price of bitcoin and the exchange rates with the U.S dollar. Exchange rates of four currencies i.e. renminbi, Euro, Japanese yenand British pound with which bitcoin are frequently exchanged are considered as the indicator of the exchange rate. It shows that there is no positive causal relationship between the price of bitcoin and the exchange rates except British pound. Therefore it can be concluded that the past data of exchange rates cannot be used to predict the future price of bitcoin but the past data of bitcoin prices can be used to predict the exchange rate of British Pound. The null hypothesis that is non stationery is rejected at 5% confidence level.

Table 4: Granger causality between the price and volume of bitcoin transaction

Pairwise Granger Causality Tests
Date: 08/19/17 Time: 16:14
Sample: 1 2165
Lags: 1
Null Hypothesis:	Obs	F-Statistic	Prob.
VOLUME__BTC_ does not Granger Cause CLOSE	2129	1.60746	0.2050
CLOSE does not Granger Cause VOLUME__BTC_		12.1543	0.0005

The above table shows the causal relationship between the closing price of bitcoin and the volume of transaction in bitcoin. Therefore it can be concluded that the closing price of bitcoin helps in predicting volume of transaction.

Table 5: Regression analysis between the price and volume of bitcoin transaction

Dependent variable : Close

Methjod : Least Squares

Date : 08/19/17 Time 1625

Sample (adjusted) : 12164

Induced Observations : 2143 after adjustments

Variable

Coefficient

Std. Error

t-Statistic

Prob.

VOLUME_BTC

368.5903

0.008461

15.90160

0.001062

23.17945

7.968764

0.0000

R-squared

Adjusted R-squred

S.E. of regression

Sum squared resid

Log. likelihood

F-statistic

Pro(F-statistic)

0.028805

0.028352

562.4452

6.77E+08

-16609.89

63.50120

0.000000

Mean dependent var

S.D. dependent var

Akaike info criterion

Schwarz criterion

Hannan-Quinn Criter.

Durbin-Watson stat

450.3403

570.5920

15.50340

15.50869

15.50533

0.024298

After analysing that there is causal relationship between the closing price of bitcoin and the volume of transaction. There is need to identify the impact of the closing price on the volume of transaction. It can be concluded that when the price increases by 0.008461 dollars there is 1 unit increase in the volume of transaction. The probability is less than 0.05 which implies that there is a significant relationship between the variables.R squared is 2.8%, It implies that 2.8% of the price variation is effected through the volume of transaction.

Table 6: Variance Analysis of the price of commodities

Variance calculation of the price of commodities
Bitcoin price	514798.2
Copper price	0.276974
Gold price	36661.48
Natural oil	0.54788
Silver price	35.22817

Table 7: Variance analysis of exchange rates

Variance calculation of the exchange rates
Euro	0.012319
British Pound	0.001543
Japanese Yen	189.1340
Renminbi	0.02293
Bitcoin	514798.2

From the above table it can be observed that the volatility of bitcoin is very high compared to the commodity price and Exchange rates. The huge price fluctuation in in the price of bitcoin provides a big opportunity and risk to the investors.

CONCLUSION:

From the study, it can be concluded that there is no causal relationship between the price of bitcoin and the price of commodities and exchange rates. The past data of the price of bitcoin and exchange rates cannot be used to predict the future price of bitcoin but the past data of the bitcoin price helps in predicting the future price of copper and the exchange rate of British pound. From the regression analysis it can be concluded when the price increases by 0.008461 dollars there is 1 unit increase in the volume of transaction. The volatility of the price of bitcoin is very high compared to the commodity price and the exchange rates. The investors can use this study in determining the future price of copper and the exchange rate of British pound using the past data of bitcoin price.

REFERENCES:

1. Bibliography Foreste, P. (2007). Testing for a Granger causality between stock price and economic growth. Munich Personal RePEC archive, 2962.

2. Hill, K. (2016). The future of money. 1-7.

3. Li, M. (2016). Emperical study on finance and labour economics. Pro Quest , 1- 130.

4. Lio, H. (2016). essay on digital currency. Pro Quest, 1-107.

5. Marse, v. Y. (2015). what is in store for bitcoin and crypto currency regulation . U.S international editions .

6. Negurita, O. (2014). Bitcoin- between legal and financial performance . Addleton Academic publisher, 242-248.

7. Patterson, C. c. (2017). Native Copper, Silver, and Gold Accessible to Early Metallurgists. American Antiquity, 286-321.

8. Turpin, J. B. (2014). Bitcoin- The economic case for a global virtual currency operating in unexplored legal framework. Indian Journal of Global Legal Studies.

9. Woo, D., Gordon, L., and laralov, v. (2013). Bitcoin: A first assement. Bank of america merril Lynch, 13 - 14.

Received on 10.11.2017 Modified on 15.12.2017

Asian Journal of Management. 2018; 9(1):427-431.

DOI: 10.5958/2321-5763.2018.00065.3