On the Evaluation Financial Risk using Conditional Value at Risk (CVaR).

Abstract

During review of the trading book in the year 2013, the Basel Committee on Banking and Supervision proposed movement from 99% Value at Risk to 97.5% Expected Shortfall with a horizon of one day in quantifying market risk for banks. However, the accord allowed financial institutions to use internal models in forecasting their risk levels. In this regard, most risk managers prefer Value at Risk due to its simplicity and intuitive interpretation. This is despite the many shortcomings of Value at Risk evidenced in literature. This study looks at estimation of Conditional Value at Risk using conditional extreme quantile autoregression and how the resulting estimator is applied in evaluating financial risk in banks and other financial institutions. Performance of the estimator is compared against two other values at risk estimators using Root Mean Squared Error. Results from the study indicate that the proposed Conditional Value at Risk estimator is consistent and leads to more accurate risk estimates.