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Financial Markets and Portfolio Management

, Volume 31, Issue 3, pp 261–288 | Cite as

Predictive models for disaggregate stock market volatility

  • Terence Tai-Leung ChongEmail author
  • Shiyu Lin
Article
  • 273 Downloads

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 

JEL Classification

C12 G12 

Notes

Acknowledgements

We thank the editor and anonymous referees for their constructive comments, which greatly improved the quality of the paper. We owe much to Liugang Sheng and Julan Du, and seminar participants at The Chinese University of Hong Kong, for their helpful comments. We are also very much indebted to Min Chen, Margaret Loo, Yingshi Chen, Junjie Guo, and Mandy Cheung, for their assistance with the research. Any remaining errors are ours.

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Copyright information

© Swiss Society for Financial Market Research 2017

Authors and Affiliations

  1. 1.Department of Economics and Lau Chor Tak Institute of Global Economics and FinanceThe Chinese University of Hong KongShatinHong Kong
  2. 2.Department of EconomicsThe Chinese University of Hong KongShatinHong Kong

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