A Parametric Model to Estimate Risk in a Fixed Income Portfolio

Resumen

In this paper we propose a methodology that let us to calculate the variance and covariance matrix of a very large set of interest rate changes at a very low computational cost. The proposal uses the parametization of interest rates that underlies the model of Nelson and Siegel (1987) to estimate the yield curve. Starting with that model, we are able to obtain the variance-covariance matrix of a vector of k interest rates by estimating the variance of the principal components of the four parameters of the model. We used the methodology we propose to calculate risk in a fixed income portfolio, in particular to calculate Value at Risk (VaR). The results of the paper indicate that the application of our method to calculate VaR provides a precise measure of risk when compared to other parametric methods