A Novel Robust Method for Estimating the Covariance Matrix of Financial Returns with Applications to Risk Management

Arturo Leccadito (), Alessandro Staino and Pietro Toscano
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Arturo Leccadito: Université catholique de Louvain, LIDAM/LFIN, Belgium

No 2022011, LIDAM Discussion Papers LFIN from Université catholique de Louvain, Louvain Finance (LFIN)

Abstract: In this paper we introduce the dynamic Gerber model (DGC) and compare its performance in the prediction of VaR and ES compared to alternative parametric, nonparametric and semiparametric methods to estimate the variance-covariance matrix of returns. Based on ES backtests, the DGC method produces, overall, accurate ES forecasts. Furthermore, we use the Model Confidence Set (MCS) procedure to identify the superior set of models (SSM). For all the portfolios and VaR/ES confidence levels we consider, the DGC is found to belong to the SSM.

Keywords: VaR; ES; Gerber statistic; parametric methods; nonparametric methods; semiparametric methods (search for similar items in EconPapers)
Pages: 38
Date: 2022-11-29
New Economics Papers: this item is included in nep-ecm and nep-rmg
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Persistent link: https://EconPapers.repec.org/RePEc:ajf:louvlf:2022011

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