Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5088673 | Journal of Banking & Finance | 2015 | 29 Pages |
Abstract
Considering a wide range of potential risk drivers, we apply boosting to derive monthly volatility predictions for the equity market represented by S&P 500 index. Comparisons with commonly-used GARCH and EGARCH benchmark models show that our approach substantially improves out-of-sample volatility forecasts for short- and longer-run horizons. The results indicate that risk drivers affect future volatility in a nonlinear fashion.
Related Topics
Social Sciences and Humanities
Economics, Econometrics and Finance
Economics and Econometrics
Authors
Stefan Mittnik, Nikolay Robinzonov, Martin Spindler,