Realized extreme quantile: A joint model for conditional quantiles and measures of volatility with EVT refinements
Marco Bee,
Debbie J. Dupuis and
Luca Trapin
Journal of Applied Econometrics, 2018, vol. 33, issue 3, 398-415
Abstract:
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.
Date: 2018
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https://doi.org/10.1002/jae.2615
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Persistent link: https://EconPapers.repec.org/RePEc:wly:japmet:v:33:y:2018:i:3:p:398-415
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