Do Bitcoin Shocks Dominate Other Cryptocurrencies? An Examination Through GARCH Based Dynamic Models

In this paper, we examine the effects of return and volatility shocks captured from Bitcoin to other seven types of major cryptocurrencies by employing the daily data spanning from June 2011 to June 2020. We examine return and volatility transmission from Bitcoin to other cryptocurrencies using ARMA-GARCH model and extension of the asymmetric model of ARMA-TGARCH and ARMA-EGARCH. Moreover, we apply Dynamic Conditional Correlation and Asymmetric Dynamic Conditional Correlation (DCC and ADCC) models to measure the time-varying nature of conditional correlation. The results of the study show strong evidence of shocks transmission from Bitcoin to other cryptocurrencies in terms of both returns and volatility spillover, except for some less inefficient cryptocurrencies. In addition, the majority of the cryptocurrencies also reflect strong evidence about time-varying dynamic conditional correlation with asymmetric effects that adds ups the significant novelty in the existing literature from the methodological perspective as well.