Single-Index Expectile Models for Estimating Conditional Value at Risk and Expected Shortfall. (4th August 2020)

• Record Type: Journal Article
• Authors: Jiang, Rong; Hu, Xueping; Yu, Keming
• Is Part Of: Journal of financial econometrics. Volume 20:Number 2(2022)
• Page Start: 345
• Page End: 366
• Publication Date: 2020-08-04
• Subjects: single-index model -- expectile regression -- value at risk; C13 -- C14 -- C22; Capital market -- Law and legislation -- Periodicals; Financial institutions -- Law and legislation -- Periodicals; 338.544205
• DOI: 10.1093/jjfinec/nbaa016
• Languages: English
• ISSNs: 1479-8409

Abstract

Abstract: This article develops a single-index approach for modeling the expectile-based value at risk (EVaR). EVaR has an advantage over the conventional quantile-based VaR (QVaR) of being more sensitive to the magnitude of extreme losses. EVaR can also be used for calculating QVaR and expected shortfall (ES) by exploiting the one-to-one mapping from expectiles to quantiles and the relationship between VaR and ES. We develop an asymmetric least squares technique for estimating the unknown regression parameter and link function in a single-index model, and establish the asymptotic normality of the resultant estimators. Simulation studies and real data applications are conducted to illustrate the finite sample performance of the proposed methods.