Dynamic Semiparametric Models for Expected Shortfall (and Value-At-Risk)

50 Pages Posted: 18 Jul 2017

See all articles by Andrew J. Patton

Andrew J. Patton

Duke University - Department of Economics

Johanna Ziegel

University of Bern

Rui Chen

Duke University

Date Written: July 11, 2017

Abstract

Expected Shortfall (ES) is the average return on a risky asset conditional on the return being below some quantile of its distribution, namely its Value-at-Risk (VaR). The Basel III Accord, which will be implemented in the years leading up to 2019, places new attention on ES, but unlike VaR, there is little existing work on modeling ES. We use recent results from statistical decision theory to overcome the problem of "elicitability" for ES by jointly modelling ES and VaR, and propose new dynamic models for these risk measures. We provide estimation and inference methods for the proposed models, and confirm via simulation studies that the methods have good finite-sample properties. We apply these models to daily returns on four international equity indices, and find the proposed new ES-VaR models outperform forecasts based on GARCH or rolling window models.

Keywords: Risk Management, Tails, Crashes, Forecasting, Generalized Autoregressive Score

JEL Classification: G17, C22, G32, C58

Suggested Citation

Patton, Andrew J. and Ziegel, Johanna and Chen, Rui, Dynamic Semiparametric Models for Expected Shortfall (and Value-At-Risk) (July 11, 2017). Economic Research Initiatives at Duke (ERID) Working Paper No. 250, Available at SSRN: https://ssrn.com/abstract=3000465 or http://dx.doi.org/10.2139/ssrn.3000465

Andrew J. Patton (Contact Author)

Duke University - Department of Economics ( email )

213 Social Sciences Building
Box 90097
Durham, NC 27708-0204
United States

HOME PAGE: http://econ.duke.edu/~ap172/

Johanna Ziegel

University of Bern

Rui Chen

Duke University ( email )

100 Fuqua Drive
Durham, NC 27708-0204
United States

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