A0463
Title: Forecasting value-at-risk and expected shortfall: A comparison study
Authors: Helena Veiga - Universidad Carlos III de Madrid (Spain) [presenting]
J Miguel Marin - University Carlos III (Spain)
Abstract: Data cloning is used to forecast two risk measures, value-at-risk and expected shortfall, for five volatility models, including conditional heteroscedastic and stochastic volatility models, which may or may not allow for an asymmetric response of the volatility. These risk measures are forecasted for five international stock market indexes and show that models that include the asymmetric response of the volatility often provide more accurate forecasts of the value-at-risk and expected shortfall.
