Dynamic semiparametric models for expected shortfall (and Value-at-Risk)

Andrew Patton, Johanna F. Ziegel and Rui Chen

Journal of Econometrics, 2019, vol. 211, issue 2, 388-413

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 modeling 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 (search for similar items in EconPapers)
JEL-codes: C22 C58 G17 G32 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (132)

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Working Paper: Dynamic Semiparametric Models for Expected Shortfall (and Value-at-Risk) (2017)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:211:y:2019:i:2:p:388-413

DOI: 10.1016/j.jeconom.2018.10.008

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