David Ardia

finance seminar

David Ardia

University of Neuchatel, Laval University
Forecasting risk with Markov–switching GARCH models: A large–scale performance study
Co-écrit avec
Keven Bluteaua, Kris Boudt, Leopoldo Catania
Lieu

Château Lafarge

Château Lafarge - Salle de séminaires
Château Lafarge
Route des Milles
13290 Les Milles
Date(s)
Mardi 10 avril 2018| 14:30
Contact(s)

Eric Girardin : eric.girardin[at]univ-amu.fr
Christelle Lecourt : christelle.lecourt[at]univ-amu.fr
Jean-François Carpantier : jean-francois.carpantier[at]univ-amu.fr

Résumé

We perform a large–scale empirical study to compare the forecasting performance of single–regime and Markov–switching GARCH (MSGARCH) models from a risk management perspective. We find that MSGARCH models yield more accurate Value–at–Risk and left–tail distribution forecasts than their single–regime counterpart. Also, our results indicate that accounting for parameter uncertainty improves left–tail predictions, independently of the inclusion of the Markov–switching mechanism.