Backtesting Expected Shortfall via Multi-Quantile Regression

By Couperier Ophélie and Leymarie Jérémy
Working Paper (2021)

  • Jérémy Leymarie

    EDHEC Business School


  • Ophélie Couperier




November 9, 2018

Last update

June 11, 2021










These Matlab codes compute the four regression-based backtests for ES of the article "Backtesting Expected Shortfall via Multi-Quantile Regression". The test statistics are devised to assess the coefficients of a multi-quantile regression model which satisfy specific properties when the ES forecasts are valid. The folder contains two main scripts that implement a GARCH(1,1) model and a AR(1)-GARCH(1,1) model, respectively. To compute the backtests, the user must choose the number p of risk levels, and the coverage level tau of ES. The scripts are applied to the daily returns of the S&P500 index over the period 1997-2012 and allow to reproduce most of the figures and tables of the empirical application of this article.

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