Realized extreme quantile: A joint model for conditional quantiles and measures of volatility with EVT refinements. (11th January 2018)

• Record Type: Journal Article
• Authors: Bee, Marco; Dupuis, Debbie J.; Trapin, Luca
• Is Part Of: Journal of applied econometrics. Volume 33:Number 3(2018)
• Page Start: 398
• Page End: 415
• Publication Date: 2018-01-11
• Subjects: Econometrics -- Periodicals; 330.015195
• DOI: 10.1002/jae.2615
• Languages: English
• ISSNs: 0883-7252

Abstract

Summary: 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 in finite 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.