The Effect Of Volume On Bitcoin Price Variation

Open Access
Zavaleta, Nicolas Xavier
Area of Honors:
Interdisciplinary in Economics and Finance
Bachelor of Science
Document Type:
Thesis Supervisors:
  • Shouyong Shi, Thesis Supervisor
  • Russell Paul Chuderewicz, Honors Advisor
  • Brian Spangler Davis, Honors Advisor
  • Bitcoin
  • volatility
This paper aims to investigate how Bitcoin price behaves relative to change in volume. Bitcoin has been a fascination in recent years because of beliefs that it can replace gold or even become a global currency. Cryptocurrencies as a whole present a unique opportunity to change the payment method network. Part of Bitcoin’s success has been how it is created and the platform it works off of, much like the beginnings of the Internet. Whether or not Bitcoin stabilizes around a set price or proportion in relation to national currencies, the price movements of Bitcoin have been captivating and correlated with an increase in interest ranging from regulators to speculators. Since debate continues about Bitcoin either as a currency, property, or payment method, the price is important in understanding investor sentiment. With the decrease in price fluctuations, policymakers, consumers, and businesses will better be able to integrate Bitcoin into the transaction market. In order to find out when or how Bitcoin will stabilize, it is useful to see what factors effect price movements in Bitcoin. This paper will look at a common comparison to price, “daily volume”. Understanding volume’s impact on price will help to gain a foundation for which other variables can be examined to explain price change. I examine six Bitcoin exchanges and use those as examples of how to track price changes over time with different volume levels. I create an Artificial Index to act as a way to link all the exchanges together on a total volume weighted average to create a new price and volume. I find that volume is statistically significant or that I cannot reject the null hypothesis, but believe other variables may have a greater impact. The paper concludes with my findings and offers some suggestions on how to model additional variables that may be able to prove better to model price change in the market.