Predictive Models for Disaggregate Stock Market Volatility
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- Terence Tai-Leung Chong & Shiyu Lin, 2017. "Predictive models for disaggregate stock market volatility," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 31(3), pages 261-288, August.
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Citations
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Cited by:
- Conrad, Christian & Glas, Alexander, 2018. "‘Déjà vol’ revisited: Survey forecasts of macroeconomic variables predict volatility in the cross-section of industry portfolios," Working Papers 0655, University of Heidelberg, Department of Economics.
- Yu Wei & Lan Bai & Kun Yang & Guiwu Wei, 2021. "Are industry‐level indicators more helpful to forecast industrial stock volatility? Evidence from Chinese manufacturing purchasing managers index," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 17-39, January.
- Zhang Wu & Terence Tai-Leung Chong, 2021. "Does the macroeconomy matter to market volatility? Evidence from US industries," Empirical Economics, Springer, vol. 61(6), pages 2931-2962, December.
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More about this item
Keywords
Industry level stock return volatility; Out-of-sample forecast; Granger Causality.;All these keywords.
JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
NEP fields
This paper has been announced in the following NEP Reports:- NEP-FMK-2015-12-28 (Financial Markets)
- NEP-FOR-2015-12-28 (Forecasting)
- NEP-RMG-2015-12-28 (Risk Management)
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