Predictive Models for Disaggregate Stock Market Volatility
Terence Tai Leung Chong and
Shiyu Lin
MPRA Paper from University Library of Munich, Germany
Abstract:
This paper incorporates the 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 (2007) test is employed to verify whether the new forecasting models, which vary among industries based on the in-sample results, can have better predictions than the two benchmark models. Our results show that default return and default yield have significant impacts 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: 2015-11-08
New Economics Papers: this item is included in nep-fmk, nep-for and nep-rmg
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https://mpra.ub.uni-muenchen.de/68460/1/MPRA_paper_68460.pdf original version (application/pdf)
Related works:
Journal Article: Predictive models for disaggregate stock market volatility (2017)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:68460
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