Predictive Models for Disaggregate Stock Market Volatility

Chong, Terence Tai Leung and Lin, Shiyu (2015): Predictive Models for Disaggregate Stock Market Volatility.

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.

• Item Type: MPRA Paper
• Language: English
• Keywords: Industry level stock return volatility; Out-of-sample forecast; Granger Causality.
• Subjects: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C12 - Hypothesis Testing: General; G - Financial Economics > G1 - General Financial Markets > G12 - Asset Pricing ; Trading Volume ; Bond Interest Rates

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