Financial Asset-Pricing Theory and Stochastic Programming Models for Asset/Liability Management: A Synthesis
Posted: 8 May 1997
Date Written: April 1996
Practical portfolio investment problems under uncertainty can be modeled well as multi-period stochastic programs. However, the numerical optimization methods which need to be used to solve such models seriously limit the level of detail in the uncertainty about future asset prices and returns which can be incorporated. Somewhat surprisingly, the question how this necessarily approximate description of the uncertainty should be constructed has received relatively little attention in the stochastic programming literature. Moreover, many of the descriptions which have been used are not arbitrage-free, and therefore inconsistent with modern nancial asset-pricing theory. In this paper we will present aggregation methods which can be used in combination with nancial asset-pricing models to obtain a description of the uncertainty that is arbitrage-free, consistent with observed market prices as well as concise enough for a stochastic programming model. Furthermore, we will discuss how these aggregation methods can form the basis of an iterative solution approach.
JEL Classification: G12, C61
Suggested Citation: Suggested Citation