Asset/liability management under uncertainty
In this chapter, we present robust methods for solving Asset/Liability Managec ment (ALM) problems. Whereas Chapter 9 concentrates on assets-only optimization, this chapter explores the difficulty of simultaneously optimizing both the asset and the liability sides of a portfolio. Alternative minimax formulations with differing objective functions are presented, depending on the targets or objectives of the ALM portfolios. We illustrate the robustness property of the minimax formulation when the liability structure of an ALM portfolio is sensitive to shifts in yield curves. It can be shown that the minimax solution, as compared to standard immunization, provides the least deteriora ion in the value of the ALM portfolio.
We also present extended stochastic ALM models that deal with multiperiod objectives and varying performance horizons as well as varying investment, or benchmarking, horizons. The minimax formulations are based on scenarios describing evolutionary paths for both assets and liabilities. These stochastic ALM models are useful for making a comprehensive evaluation of an ALM strategy, whether it is based on minimax, where portfolios are designed to be robust, or on standard ALM techniques, where specific objec ives may have dominated the portfolio's construction.
In Chapter 9, we present applications of minimax to asset management while in this chapter we consider an application to asset/liability management (ALM). In both areas the objective of the decision maker is asset returns enhancement. However, whereas in asset management the concern is with the management of the volatility of returns, in ALM this is compounded by the management of liabilities to ensure payments are met as they fall due. This implies that the modeler providing a suite of tools to the decision maker has to consider a more complex measure of risk and devise strategies for managing this risk.
The problem of setting up an asset portfolio such that the cashflows from this portfolio are used for managing liabilities is complicated by a number of issues. These are asset return enhancement, volatility of asset returns, full or