Repercussion of Covid 19 Upsurge: An Analysis on the Efficaciousness of Autoregressive Models in Volatility and Return Estimation of Bitcoin

Cryptocurrencies, especially Bitcoin, is a hot commodity today. High volatility is a common feature of almost all the cryptocurrencies in the world. A systematic exploration and examination of the volatility of cryptos enables the investor to earn more on their investments. After the outbreak of the COVID-19 pandemic, the crypto market witnessed a highly volatile situation with a huge increase in price. The pandemic also affected the volatility and return of Bitcoin. This research aims to analyse and compare the risk and volatility characteristics of Bitcoin after the outbreak of the COVID-19 pandemic. The study further tests the capacity of several autoregressive models, such as ARMA, GARCH, EGARCH, and TARCH in estimating and evaluating the return and volatility associated with Bitcoin. Identified models were tested and compared with the help of Akaike information criteria (AIC) and Schwarz information criteria (SIC). For this article, the data of daily adjusted closing price of Bitcoin INR (BTC-INR) were collected from Yahoo Finance during the period January, 2017 to December, 2021. We witnessed a huge change in the daily average return of Bitcoin after the COVID-19 outbreak. Also, we identified TARCH (1, 1) as the best model in the ARCH family for evaluating and estimating volatility and ARMA (10, 10) as the best model for predicting the return of Bitcoin.