Market volatility in cryptocurrencies: A comparative study using GARCH and TGARCH models

Price volatility has a negative connotation, as it is associated with market instability, uncertainty, and loss. When markets swing, investors and traders tend to place additional bets anticipating further swings, resulting in increased price volatility. There are no indices to assess crypto price volatility, but investigating historical price fluctuations provides insights into the rising peaks and depressive troughs that occur at a faster and more extreme rate in crypto prices compared to asset values in mainstream markets. This study employed generalized autoregressive conditional heteroskedasticity (GARCH) as a comparison tool to measure the leverage effect and price volatility among two major cryptocurrencies, Bitcoin and Ethereum, for the period from 2017 to 2021. A unit root test was conducted to determine whether the data should be differenced or regressed, and an autoregressive conditional heteroskedasticity (ARCH) effect test was used to measure the relationships within heteroskedasticity. The study revealed that the prices increased astonishingly over these periods, despite drastic decreases, indicating negative correlations between cryptocurrencies and their volatility.