Bayesian Value at Risk Metrics for Equity Portfolios

17 Pages Posted: 5 Sep 2014 Last revised: 10 Mar 2017

See all articles by Eric Hendries

Eric Hendries

Independent

Jun Huang

Independent

Rachel Li

Independent

Xiao Li

Independent

Yiyang Qi

CME Group

Helene Sajer

Independent

Stephen Michael Taylor

New Jersey Institute of Technology

John Zerolis

Independent

Date Written: September 1, 2014

Abstract

We develop a Bayesian framework for estimating high quantiles of the relative return loss distribution of equity portfolios. This framework allows for the incorporation of both quantitative data via a parametric model for the loss distribution as well as qualitative information, specified independent of the data, by the choice of a prior distribution over the model parameters. We apply these methods in the case of one and two dimensional models to estimate distribution parameters and associated error bounds from which 99% VaR values are estimated. Finally, we systematically apply our framework to four test portfolios, compute summary statistics related to model performance, and report the results.

Keywords: Bayesian Inference, Value at Risk, Burr Distribution

JEL Classification: C11

Suggested Citation

Hendries, Eric and Huang, Jun and Li, Rachel and Li, Xiao and Qi, Yiyang and Sajer, Helene and Taylor, Stephen Michael and Zerolis, John, Bayesian Value at Risk Metrics for Equity Portfolios (September 1, 2014). Available at SSRN: https://ssrn.com/abstract=2490240 or http://dx.doi.org/10.2139/ssrn.2490240

Eric Hendries

Independent ( email )

Jun Huang

Independent ( email )

Rachel Li

Independent ( email )

Xiao Li

Independent ( email )

Yiyang Qi

CME Group ( email )

20 S Wacker Dr
Chicago, IL 60606
United States

Helene Sajer

Independent ( email )

Stephen Michael Taylor (Contact Author)

New Jersey Institute of Technology ( email )

University Heights
Newark, NJ 07102
United States

John Zerolis

Independent ( email )

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