Publikation: Dynamic Modelling of Large Dimensional Covariance Matrices
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2007
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Voev, Valeri
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Modelling and forecasting the covariance of financial return series has always been a challenge due to the so-called "curse of dimensionality". This paper proposes a methodology that is applicable in large dimensional cases and is based on a time series of realized covariance matrices. Some solutions are also presented to the problem of non-positive definite forecasts. This methodology is then compared to some traditional models on the basis of its forecasting performance employing Diebold-Mariano tests. We show that our approach is better suited to capture the dynamic features of volatilities and covolatilities compared to the sample covariance based models.
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VOEV, Valeri, 2007. Dynamic Modelling of Large Dimensional Covariance MatricesBibTex
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author={Voev, Valeri}
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