Forecasting the volatility of the German stock market: New evidence

C-Tier
Journal: Applied Economics
Year: 2022
Volume: 54
Issue: 9
Pages: 1055-1070

Score contribution per author:

0.335 = (α=2.01 / 3 authors) × 0.5x C-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

This study mainly explores whether the implied volatility indices of international stock markets and crude oil contain useful information in predicting the realized volatility (RV) of the German stock market. We use the standard predictive regression model, principal component analysis, five combination methods, and two shrinkage models to generate forecasts of DAX index volatility. First, the in-sample results indicate that almost all of the implied volatility indices considered have significant predictive power for the RV of the German DAX index. Second, the out-of-sample predictions suggest that the two shrinkage models exhibit the best out-of-sample predictions. Furthermore, a mean-variance investor can allocate portfolios through volatility predictions based on shrinkage models to achieve considerable economic gains. Finally, our conclusions are supported by numerous robustness checks.

Technical Details

RePEc Handle
repec:taf:applec:v:54:y:2022:i:9:p:1055-1070
Journal Field
General
Author Count
3
Added to Database
2026-01-29