Dynamic models for fixed-income portfolio management under uncertainty

Abstract

Abstract We develop multi-period dynamic models for fixed-income portfolio management under uncertainty, using multi-stage stochastic programming with recourse. The models integrate the prescriptive stochastic programs with descriptive Monte Carlo simulation models of the term structure of interest rates. Extensive validation experiments are carried out to establish the effectiveness of the models in hedging against uncertainty, and to assess their performance vis-a-vis single-period models. An application to tracking the Salomon Brothers Mortgage Index is reported, with very encouraging results. Results that establish the efficacy of the models in hedging against out-of-sample scenarios are also reported for an application from money management. The multi-period models outperform classical models based on portfolio immunization and single-period models.