A STOCHASTIC-PROGRAMMING MODEL FOR MONEY MANAGEMENT

Portfolio managers in the new fixed-income securities have to cope wit h various forms of uncertainty, in addition to the usual interest rate changes. Uncertainy in the timing and amount of cashflows, changes in the default and other risk premia and so on, complicate the portfolio manager's problem. We develop here a multi-period, dynamic, portfolio optimization model to address this problem. The model specifies a seq uence of investment decisions over time that maximize the expected uti lity of return at the end of the planning horizon. The model is a two- stage stochastic program with recourse. The dynamics of interest rates , cashflow uncertainty, and liquidity, default and other risk premia, are explicitly modeled through postulated scenarios. Simulation proced ures are developed to generate these scenarios, The optimization model s are then integrated with the simulation procedures. Extensive valida tion experiments are carried out to establish the effectiveness of the model in dealing with uncertainty. In particular the model is compare d against the popular portfolio immunization strategy, and against a p ortfolio based on mean-absolute deviation optimization.