Factors Affecting the Return and Volatility of Major Cryptocurrencies

The goal of this study is to analyze the predictive power of selected financial variables over principal cryptocurrencies (Bitcoin, Ethereum, and Ripple) by applying the PGARCH, EGARCH, TGARCH, and GARCH models. The studied variables include daily Google trend values of the selected cryptocurrencies' names considered as search terms; the daily log-returns of the exchange rate of major currencies per SDRs; and the daily log-returns of the S&P500 index, gold, and oil prices. Our results provide evidence that the log-returns of each studied cryptocurrency have significant explanatory over each other. We also find significant results for the daily Google trend values of the search terms “Bitcoin” and “Ripple,” but not for “Ethereum.” Likewise, we find significant results for the log-returns of the exchange rate of the Chinese Yuan per SDRs for the three cryptocurrencies. Similarly, the log-returns of oil prices have a significant relationship with Bitcoin and Ethereum, but not with Ripple. Correspondingly, we find that the daily log-returns of the S&P500 index has explanatory power for all selected cryptocurrencies; however, the daily log-returns of gold have no significant relationship with any of them. Finally, we find that the log-returns of oil have a significant relationship with Bitcoin only. Regarding the volatility of the studied cryptocurrencies, our results provide mixed evidence about the presence of leverage effects.