Predictive models for disaggregate stock market volatility

Terence Tai Leung Chong and Shiyu Lin
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Shiyu Lin: The Chinese University of Hong Kong

Financial Markets and Portfolio Management, 2017, vol. 31, issue 3, No 1, 288 pages

Abstract: Abstract This paper incorporates macroeconomic determinants into the forecasting model of industry-level stock return volatility in order to detect whether different macroeconomic factors can forecast the volatility of various industries. To explain different fluctuation characteristics among industries, we identified a set of macroeconomic determinants to examine their effects. The Clark and West (J Econom 138(1):291–311, 2007) test is employed to verify whether the new forecasting models, which vary among industries based on the in-sample results, make better predictions than the two benchmark models. Our results show that default return and default yield have a significant impact on stock return volatility.

Keywords: Industry-level stock return volatility; Out-of-sample forecast; Granger causality (search for similar items in EconPapers)
JEL-codes: C12 G12 (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (3)

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Working Paper: Predictive Models for Disaggregate Stock Market Volatility (2015)
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DOI: 10.1007/s11408-017-0291-2

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