Robust Value at Risk Prediction

51 Pages Posted: 17 Aug 2005 Last revised: 13 Sep 2010

See all articles by Loriano Mancini

Loriano Mancini

USI Lugano - Institute of Finance; Swiss Finance Institute

Fabio Trojani

Swiss Finance Institute; University of Geneva

Date Written: September 10, 2010

Abstract

This paper proposes a robust semiparametric bootstrap method to estimate predictive distributions of GARCH-type models. The method is based on a robust estimation of parametric GARCH models and a robustified resampling scheme for GARCH residuals that controls bootstrap instability due to outlying observations. A Monte Carlo simulation shows that our robust method provides more accurate VaR forecasts than classical methods, often by a large extent, especially for several days ahead horizons and/or in presence of outlying observations. An empirical application confirms the simulation results. The robust procedure outperforms in backtesting several other VaR prediction methods, such as RiskMetrics, CAViaR, Historical Simulation, and classical Filtered Historical Simulation methods. We show empirically that robust estimation reduces tail estimation risk, providing more accurate and more stable VaR prediction intervals over time.

Keywords: M-estimator, Extreme Value Theory, Breakdown Point, Backtesting

JEL Classification: C14, C15, C23, C59

Suggested Citation

Mancini, Loriano and Trojani, Fabio, Robust Value at Risk Prediction (September 10, 2010). Swiss Finance Institute Research Paper No. 07-31. Available at SSRN: https://ssrn.com/abstract=776124 or http://dx.doi.org/10.2139/ssrn.776124

Loriano Mancini (Contact Author)

USI Lugano - Institute of Finance ( email )

Via Giuseppe Buffi 6
6904 Lugano, CH-6904
Switzerland
+41 (0)91 912 46 47 (Fax)

HOME PAGE: http://www.people.usi.ch/mancil/

Swiss Finance Institute ( email )

c/o University of Geneva
40, Bd du Pont-d'Arve
CH-1211 Geneva 4
Switzerland

Fabio Trojani

Swiss Finance Institute ( email )

c/o University of Geneva
40, Bd du Pont-d'Arve
CH-1211 Geneva 4
Switzerland

University of Geneva ( email )

Geneva
Switzerland

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