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Estimation frequency of GARCH-type models: Impact on Value-at-Risk and Expected Shortfall forecasts?

David Ardia & Lennart Hoogerheide

Résumé We analyze the impact of the estimation frequency - updating parameter estimates on a daily, weekly, monthly or quarterly basis - for commonly used GARCH models in a large-scale study, using more than twelve years (2000-2012) of daily returns for constituents of the S&P 500 index. We assess the implication for one-day ahead 95% and 99% Value-at-Risk (VaR) forecasts with the test for correct conditional coverage of Christoffersen (1998) and for Expected Shortfall (ES) forecasts with the block-bootstrap test of ES violations of Jalal and Rockinger (2008). Using the false discovery rate methodology of Storey (2002) to estimate the percentage of stocks for which the model yields correct VaR and ES forecasts, we conclude that there is no difference in performance between updating the parameter estimates of the GARCH equation at a daily or weekly frequency, whereas monthly or even quarterly updates are only marginally outperformed.
   
Mots-clés GARCH; Value-at-Risk; Expected Shortfall; Equity; Frequency; False discovery rate
   
Citation Ardia, D., & Hoogerheide, L. (2014). Estimation frequency of GARCH-type models: Impact on Value-at-Risk and Expected Shortfall forecasts?. Economics Letters, 123, 187-190.
   
Type Article de périodique (Anglais)
Date de publication 2014
Nom du périodique Economics Letters
Volume 123
Pages 187-190
URL http://www.sciencedirect.com/science/article/pii/S0165176...