Date of Award

Summer 8-25-2022

Degree Type

Thesis

Degree Name

Master of Arts in Economics

Department

Economics

First Advisor

Ngo, Phuong

Second Advisor

Isakin, Maksim

Third Advisor

Wang, Wei

Subject Headings

Economics

Abstract

I study whether news and the sentiment of the news regarding cryptocurrency regulation affects the volatility of Bitcoin, Binance, and Ethereum, measured as the standard deviation of the 1st difference of the log of the price with a right sided overlapping window of 7 days. I utilise a modified dynamic causal model with Newey-West heteroskedastic autocorrelation standard errors to estimate both the impact and cumulative effects that regulation news has on the three cryptocurrencies included in the study. My results show the volatility of all three cryptocurrencies react most strongly to negative regulatory news, with Binance being affected the most with an increase of 16.329% after 9 periods following an event, followed by Ethereum with an increase of 8.240% and Bitcoin with an increase of 8.180%. Positive news is also found to affect the volatilities; however, it is a much smaller effect and is only significant for Bitcoin, which experienced an increase of 4.597% in volatility 9 periods following an event. The results are robust to controlling potential omitted variable bias including the volatility of the S&P500 index, consumer confidence, inflation, and federal funds rates.

Included in

Economics Commons

COinS