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Impact of a Bitcoin Network Factors and Financial Markets on Bitcoin Pricing

Student: Matveev Maxim

Supervisor: Oleg Shibanov

Faculty: Faculty of Economic Sciences

Educational Programme: Joint HSE-NES Undergraduate Program in Economics (Bachelor)

Year of Graduation: 2017

This paper presents an empirical study on pricing of cryptocurrency Bitcoin on the daily level. The paper uses factor analysis of Bitcoin network and financial markets for the time period between the end of 2013 to the beginning of 2017. In the study I use the following tools: Dickey-Fuller test, Granger Causality test, correlation matrix and ordinary least square regression with time series lags. The results of this research identified some factors, which could influence the future price of the Bitcoin cryptocurrency. I was able to check how strongly the total amount of unique addresses and total volume of transactions in the Bitcoin network could influence future pricing. I created a strategy, based on the found factors, which show when it is necessary to buy bitcoins and when to sell them. This model has been checked in simulated situations and shows about 30% revenue per year without transaction costs. Also I detected a weak correlation between Bitcoin prices and future S&P500 index. It is possible that the Bitcoin network contains some information which could help to predict S&P500.

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