Predictive models for disaggregate stock market volatility

被引:3
|
作者
Chong T.T.-L. [1 ]
Lin S. [2 ]
机构
[1] Department of Economics and Lau Chor Tak Institute of Global Economics and Finance, The Chinese University of Hong Kong, Shatin, N.T.
[2] Department of Economics, The Chinese University of Hong Kong, Shatin, N.T.
关键词
Granger causality; Industry-level stock return volatility; Out-of-sample forecast;
D O I
10.1007/s11408-017-0291-2
中图分类号
学科分类号
摘要
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. © 2017, Swiss Society for Financial Market Research.
引用
收藏
页码:261 / 288
页数:27
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