Forecasting VaR and Expected Shortfall using Dynamical Systems: A Risk Management Strategy

Cyril Caillault (1) , Dominique Guegan (2, 3)

1 Fortis Investments
2 CES - Centre d'économie de la Sorbonne
3 PSE - Paris School of Economics

Using non-parametric and parametric models, we show that the bivariate distribution of an Asian portfolio is not stable along all the period under study. We suggest several dynamic models to compute two market risk measures, the Value at Risk and the Expected Shortfall: the RiskMetrics methodology, the Multivariate GARCH models, the Multivariate Markov-Switching models, the empirical histogram and the dynamic copulas. We discuss the choice of the best method with respect to the policy management of bank supervisors. The copula approach seems to be a good compromise between all these models. It permits taking financial crises into account and obtaining a low capital requirement during the most important crises.

Mots clés: Value at Risk; Expected Shortfall; Copulas; Risk management; GARCH models; Markov switching models

Domaines: Economies et finances; Probabilités [math.PR]; Statistiques [math.ST]; Théorie [stat.TH]

Cyril Caillault, Dominique Guegan. Forecasting VaR and Expected Shortfall using Dynamical Systems: A Risk Management Strategy. Frontiers in finance and economics, 2009, 6 (1), pp.26-50. ⟨halshs-00375765⟩