Article ID Journal Published Year Pages File Type
5088673 Journal of Banking & Finance 2015 29 Pages PDF
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
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