Forecasting Expected Shortfall and Value-at-Risk with the FZ Loss and Realized Variance Measures

54 Pages Posted: 23 Sep 2019 Last revised: 28 Nov 2020

See all articles by Ray Y. Chou

Ray Y. Chou

Academia Sinica; Jinhe center of economic research ; National Chiao Tung university

Tso-Jung Yen

Academia Sinica - Institute of Statistical Science

Yu-Min Yen

Department of International Business, National Chengchi University

Date Written: August 28, 2019

Abstract

Value at risk (VaR) and expected shortfall (ES) are two of the most widely used risk measures in economics and finance. In this paper, we use a semiparametric method, together with realized variance measures, to jointly estimate structural models for the two risk measures. The semiparametric estimations rely on using a class of consistent loss functions recently proposed by Fissler and Ziegel (2016). We develop an efficient and stable two-stage method to implement the estimations. We then compare out-of-sample forecast performances from the estimated structural models with other existing methods. Through comprehensive evaluations with different performance measures, we find the proposed models featuring with the realized variance measures as exogenous variables can deliver comparable or even better performances on forecasting VaR and ES of major stock indices around the world than the existing methods.

Keywords: Expected shortfall, Forecast, Realized variance measure, Semiparametric estimation, Value-at-risk

JEL Classification: C22, C53, C58, G17

Suggested Citation

Chou, Ray Y. and Yen, Tso-Jung and Yen, Yu-Min, Forecasting Expected Shortfall and Value-at-Risk with the FZ Loss and Realized Variance Measures (August 28, 2019). Available at SSRN: https://ssrn.com/abstract=3448882 or http://dx.doi.org/10.2139/ssrn.3448882

Ray Y. Chou

Academia Sinica ( email )

128 Academia Road, Section 2
Nankang
Taipei, 11529
Taiwan

Jinhe center of economic research ( email )

No 28, Xianning West Road
Xi’an, Shaanxi
China

National Chiao Tung university ( email )

1001 University Road
Hsinchu, 300
Taiwan

Tso-Jung Yen

Academia Sinica - Institute of Statistical Science ( email )

Nankang
Taipei, 11529
Taiwan

Yu-Min Yen (Contact Author)

Department of International Business, National Chengchi University ( email )

64, Section 2, Zhi-nan Road
Wenshan
Taipei, 116
Taiwan

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