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Which fear index matters for predicting US stock market volatilities: Text-counts or option based measurement?

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  • Zhu, Sha
  • Liu, Qiuhong
  • Wang, Yan
  • Wei, Yu
  • Wei, Guiwu

Abstract

Although VIX has long been recognized as an index to measure fear sentiment in US stock markets, a set of similar measurements called Equity Market Volatility (EMV) trackers are newly created based on the text-counts of newspaper articles including several keywords related to US economy or stock market volatility. In this paper, we use GARCH-MIDAS method to quantify the in-sample explanatory and out-of-sample predictive powers of these two kinds of fear indices in US stock markets. Our empirical results show that VIX has larger in-sample impacts on US stock market volatility than EMV trackers. However, the out-of-sample volatility predictive performances of EMV trackers are generally superior to VIX across different US stock indices and prediction time horizons. In addition, policy-related EMV tracker acts better than VIX and other EMV trackers in predicting volatilities of US stock markets.

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  • Zhu, Sha & Liu, Qiuhong & Wang, Yan & Wei, Yu & Wei, Guiwu, 2019. "Which fear index matters for predicting US stock market volatilities: Text-counts or option based measurement?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    • Handle: RePEc:eee:phsmap:v:536:y:2019:i:c:s0378437119314645
    DOI: 10.1016/j.physa.2019.122567
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