Stock Volatility Predictability in Bull and Bear Markets

35 Pages Posted: 8 May 2019

See all articles by Xingyi Li

Xingyi Li

School of Business and Law, University of Agder

Valeriy Zakamulin

University of Agder - School of Business and Law

Date Written: April 12, 2019

Abstract

Recent literature on stock return predictability suggests that it varies substantially across economic states being strongest during bad economic times. In line with this evidence, we document that stock volatility predictability is also state dependent. In particular, using a large data set of high-frequency data on individual stocks and a few popular time-series volatility models, in this paper we comprehensively examine how volatility forecastability varies across bull and bear states of the stock market. We find that the volatility forecast horizon is substantially longer when the market is in a bear state than when it is in a bull state. In addition, the volatility forecast accuracy is higher and forecast bias is lower when the market is in a bear state. Our study concludes that the stock volatility predictability is strongest during bad economic times proxied by bear market states.

Keywords: stock markets, volatility forecasting, state dependence, high-frequency data, meta-analysis

JEL Classification: C22, C53, G17

Suggested Citation

Li, Xingyi and Zakamulin, Valeriy, Stock Volatility Predictability in Bull and Bear Markets (April 12, 2019). Available at SSRN: https://ssrn.com/abstract=3370828 or http://dx.doi.org/10.2139/ssrn.3370828

Xingyi Li

School of Business and Law, University of Agder ( email )

Serviceboks 422
N-4604 Kristiansand, VEST AGDER 4604
Norway
38141338 (Phone)

Valeriy Zakamulin (Contact Author)

University of Agder - School of Business and Law ( email )

Service Box 422
Kristiansand, N-4604
Norway
+47 38141039 (Phone)

HOME PAGE: http://vzakamulin.weebly.com/

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