Abstract
This article develops multivariate factor models for forecasting volatility in Australian stocks. We suggest estimation procedures for approximate factor models that are robust to jumps when the cross-sectional dimension is not very large, and also work with volatility measures that have been constructed so that they contain no jump components. Out-of-sample forecast analysis shows that multivariate factor models of volatility outperform univariate models, but there is little difference between simple and sophisticated factor models.
Original language | English |
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Pages (from-to) | 76-90 |
Number of pages | 15 |
Journal | Journal of Business and Economic Statistics |
Volume | 25 |
Issue number | 1 |
DOIs | |
Publication status | Published - Jan 2007 |