The role of stock market volatility in predicting macroeconomic quantities.

• Main Authors: Leong, Florence Mei Hua., Wirawan, Sulistiyana., Kevin, Yohanes.
• Other Authors: Nanyang Business School
• Format: Final Year Project
• Language: English
• Published: 2013
• Subjects: DRNTU::Business::Finance
• Online Access: http://hdl.handle.net/10356/51380
• Institution: Nanyang Technological University

This paper explores predictability of stock market volatility over macroeconomic quantities. We measure stock market volatility with the variance of stock prices while the macroeconomic quantities are represented by the growth rates of macroeconomic variables. This paper performs correlation analyses and multivariate linear regressions of four different volatility measures – average systematic volatility, average idiosyncratic volatility, average total volatility and aggregate market volatility, on five chosen United States macroeconomic variables. The five variables are real gross domestic product, employment rate, industrial production index, real personal consumption expenditure and nondurables goods & services consumption. We find that stock market volatility, in particular average systematic volatility, is significant in predicting macroeconomic quantities while average idiosyncratic and average total volatility do not have significant predictive power. In addition, we find that average systematic volatility behaves similarly to aggregate market volatility, leading macroeconomic quantities, on the average, up to three quarters. We also find that average idiosyncratic volatility may have significant positive association with macroeconomic quantities. When idiosyncratic volatility increases, macroeconomic quantities generally increase as well. We link this finding to the growth option theory, which suggests that idiosyncratic volatility estimates real options value possessed by firms. When average idiosyncratic volatility increases, firms’ value increases and this contributes positively to economic growth.