Value-at-Risk for Fixed Income portfolios A comparison of alternative models

Abstract


The paper presents a new method for computing the VaR for a set of fixed income securities based on extreme value theory that models the tall probabilities directly without making any assumption about the distribution of entire return process. It compares the estimates of VaR for a portfolio of fixed income securities across three methods: Variance-Covariance method, Historical Simulation method and Extreme Value method and finds that extreme value method provides the best VaR estimator in terms of correct failure ratio and the size of VaR.