Chapter 13 - Asset liability management: A review and some new results in the presence of heavy tails

Abstract

Managing assets and liabilities is a concern for banks, pension funds, and insurance companies. Asset and liability management is the simultaneous consideration of assets and liabilities in strategic investment planning. This chapter briefly reviews the asset and liability management models that use stochastic programming framework. Most of these models describe the financial uncertainty by a set of representative scenarios. This chapter proposes to replace the classical assumption of Gaussian returns in the scenario generation with the stable Paretian distribution, which can capture the leptokurtic nature of financial data. A multistage stochastic asset allocation model with decision rules is analyzed in the chapter. Optimal asset allocation under the Gaussian and stable Paretian returns are compared. Computational results suggest that asset allocation is up to 20% different depending on the utility function and the risk aversion level of the investor. Certainty equivalent return is increased up to 0.13% and utility can be improved up to 0.72% by switching to the stable Paretian model.