Forecast Evaluation in Large Cross-Sections of Realized Volatility

Christis Katsouris

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arXiv · 2112.04887

Forecast Evaluation in Large Cross-Sections of Realized Volatility

Christis Katsouris

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Abstract

In this paper, we consider the forecast evaluation of realized volatility measures under cross-section dependence using equal predictive accuracy testing procedures. We evaluate the predictive accuracy of the model based on the augmented cross-section when forecasting Realized Volatility. Under the null hypothesis of equal predictive accuracy the benchmark model employed is a standard HAR model while under the alternative of non-equal predictive accuracy the forecast model is an augmented HAR model estimated via the LASSO shrinkage. We study the sensitivity of forecasts to the model specification by incorporating a measurement error correction as well as cross-sectional jump component measures. The out-of-sample forecast evaluation of the models is assessed with numerical implementations.

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Christis Katsouris. 2021-12-09. Forecast Evaluation in Large Cross-Sections of Realized Volatility. https://arxiv.org/abs/2112.04887

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