Unravelling crash risk transmission: Cryptocurrency impact on stock markets in G-7 and China

Abstract

In this paper, we use the Empirical Bayes estimation and multiple linear regression approach to examine the impact of the top 5 cryptocurrencies’ crash risks on the G-7 and China equity markets’ crash risks. MATLAB was used to calculate the crash risks, while Stata software was employed for the econometric analysis. Three crash risk measures are used to validate the robustness of the results: (i) the relative frequency of the number of crash days in the market, (ii) the monthly returns’ skewness, and (iii) the down-to-up volatility. Our findings indicate that overall crash risks of the top 5 cryptocurrencies are positively related with G-7 and Chinese stock markets’ crash risk. This suggests that the crash risk transmits from the crypto to the equity markets and the crashes in crypto can serve as a predictor in the stock markets. Furthermore, there is a negative correlation between the historical crash risks of the G-7 stock market and the present crash risks of the same stock market. This suggests that past stock market crashes can serve as a predictive factor for assessing the current risk of a stock market crash.