Measuring Risk in Fixed Income Portfolios Using Yield Curve Models

28 Pages Posted: 18 Aug 2013

See all articles by João Caldeira

João Caldeira

Universidade Federal do Rio Grande do Sul (UFRGS)

Guilherme V. Moura

Universidade Federal de Santa Catarina (UFSC) - Department of Economics

Andre A. P. Santos

Universidade Federal de Santa Catarina (UFSC) - Department of Economics

Date Written: June 3, 2013

Abstract

We propose a novel approach to measure risk in fixed income portfolios in terms of value-at-risk (VaR). We use closed-form expressions for the vector of expected bond returns and for the covariance matrix of bond returns based on a general class of well established term structure factor models, including the dynamic versions of the Nelson-Siegel and Svensson models, to compute the parametric VaR of a portfolio composed of fixed income securities. The proposed approach is very flexible as it can accommodate alternative specifications to model the yield curve and also alternative specifications to model the conditional heteroskedasticity in bond returns. An empirical application involving a data set with 15 fixed income securities with different maturities indicate that the proposed approach delivers very accurate VaR estimates.

Keywords: backtesting, dynamic conditional correlation (DCC), forecast, maximum likelihood, value-at-risk

JEL Classification: C53, E43, G17

Suggested Citation

Caldeira, João and Moura, Guilherme Valle and A. P. Santos, Andre, Measuring Risk in Fixed Income Portfolios Using Yield Curve Models (June 3, 2013). Available at SSRN: https://ssrn.com/abstract=2311721 or http://dx.doi.org/10.2139/ssrn.2311721

João Caldeira

Universidade Federal do Rio Grande do Sul (UFRGS) ( email )

Av. Carlos Gomes 1111
Porto Alegre, Rio Grande do Sul 90480-004
Brazil

Guilherme Valle Moura

Universidade Federal de Santa Catarina (UFSC) - Department of Economics ( email )

PO Box 476
Florianopolis, SC 88010-970
Brazil

Andre A. P. Santos (Contact Author)

Universidade Federal de Santa Catarina (UFSC) - Department of Economics ( email )

PO Box 476
Florianopolis, SC 88010-970
Brazil

HOME PAGE: http://sites.google.com/site/andreportela

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