Realized Extreme Quantile: A time-varying quantile model for financial extremes

3 November 2016
Versione stampabile

2 PM, Seminar room, Department of Economics and Management

Speaker: Luca Trapin, Scuola Normale Superiore


We propose a new framework exploiting realized measures of volatility to estimate and forecast extreme quantiles. Our Realized Extreme Quantile (REQ) combines quantile regression with extreme value theory and uses a measurement equation that relates the realized measure to the latent conditional quantile. Model estimation is performed by Quasi Maximum Likelihood and a simulation experiment validates this estimator infinite samples. An extensive empirical analysis shows that high-frequency measures are particularly informative of the dynamic quantiles. Finally, an out-of-sample forecast analysis of quantile-based risk measures confirms the merit of the REQ.