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Risk of investing in volatility products: A regime-switching approach
Investment Analysts Journal ( IF 0.925 ) Pub Date : 2020-10-12 , DOI: 10.1080/10293523.2020.1814047
Leon Li 1
Affiliation  

ABSTRACT

Volatility indexes provide a tool for investors to speculate and trade on market sentiment regarding future volatility. The risk of trading on volatility indexes can be measured by their second moments, namely, variance and correlation. This study considers the four representative volatility indexes published by the CBOE: stock market volatility index (VIX), crude oil volatility index (OVX), foreign exchange rate volatility index (EVZ), and gold price volatility index (GVZ). To examine their risk, we develop an extended multivariate Markov switching ARCH (MSARCH) model in which regime-switching variances, correlations, and variance-correlation relations are designed. Our empirical sample consists of the four volatility indexes from June 2008 to April 2020 for 612 weekly observations (Wednesday to Wednesday). For the conditional variances, we find evidence of regime-switching processes (switching between low and high volatility regimes) for the individual volatility index returns, with the exception of the GVZ. The estimated probability of the high volatility regime may be used to track economic distress and uncertainty shocks. These results provide evidence for volatility-of-volatility risk. For the conditional correlations, we find a regime-switching relation between variances and correlations. That is, the highest correlation appears when the paired volatility markets are simultaneously experiencing a state of high volatility. By contrast, when the paired volatility markets are encountering different volatility states, the correlation is weaker. These results indicate that the volatility-of-volatility risk is a factor affecting the dynamics of correlations between volatility indexes.



中文翻译:

投资波动性产品的风险:一种制度转换方法

抽象的

波动率指数为投资者提供了一种工具,可以就未来的波动性进行市场情绪的推测和交易。波动率指数的交易风险可以通过其第二时刻来衡量,即方差和相关性。本研究考虑了芝加哥期权交易所发布的四个代表性波动率指数:股市波动率指数(VIX),原油波动率指数(OVX),汇率波动率指数(EVZ)和黄金价格波动率指数(GVZ)。为了检查其风险,我们开发了扩展的多元马尔可夫切换ARCH(MSARCH)模型,其中设计了制度切换方差,相关性和方差相关关系。我们的经验样本包括2008年6月至2020年4月的612个每周观测值(周三至周三)的四个波动率指数。对于条件方差,我们发现,除了GVZ以外,各个波动率指数收益都存在着政权转换过程(在低波动率制度和高波动率制度之间进行转换)的证据。高波动率制度的估计概率可用于跟踪经济困境和不确定性冲击。这些结果提供了波动率-波动率风险的证据。对于条件相关性,我们发现方差和相关性之间有一种政权转换关系。也就是说,当成对的波动性市场同时处于高波动性状态时,出现最高的相关性。相反,当成对的波动性市场遇到不同的波动性状态时,相关性较弱。

更新日期:2020-10-12
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