This paper studies asymmetric contagion effects between stock and cryptocurrency markets. We implement the time-varying symmetrized Joe-Clayton copula GARCH model and Bai-Perron breakpoint test to explore dynamic correlations between the daily log-returns of the two markets in each time range. The asymmetric contagion effects between the two markets are studied using the non-linear Granger causality test. We also find that the lower tail dependences are more significant than the upper ones. Our findings can be used as a reference for supervisory authorities, and also provide insights on risk hedging for rational investors to avoid underestimating risk when building their portfolios.

本文研究了股票和加密货币市场之间的非对称传染效应。我们实施了时变对称的 Joe-Clayton copula GARCH 模型和 Bai-Perron 断点测试，以探索两个市场在每个时间范围内的每日对数回报之间的动态相关性。使用非线性格兰杰因果检验来研究两个市场之间的不对称传染效应。我们还发现，较低的尾部依赖性比较高的尾部依赖性更显着。我们的研究结果可以作为监管部门的参考，也可以为理性投资者提供风险对冲的见解，以避免在建立投资组合时低估风险。