Asset-Liability Management Under Time-Varying Investment Opportunities
33 Pages Posted: 8 May 2009 Last revised: 1 Jul 2017
Date Written: 2010
Stochastic linear programming is a suitable numerical approach for solving practical asset-liability management problems. In this paper, we consider a multi-stage setting under time-varying investment opportunities and propose a decomposition of the benefits in dynamic re-allocation and predictability effects. A first-order unrestricted vector autoregressive process is used to model asset returns and state variables where, in addition to equity returns and dividend-price ratios, Nelson/Siegel parameters are included to account for the evolution of the yield curve. The objective is to minimize the Conditional Value at Risk of shareholder value, i.e., the difference between the mark-to-market value of (financial) assets and the present value of future liabilities.
Keywords: asset-liability management, predictability, stochastic programming, scenario generation, VAR process
JEL Classification: C61, G11
Suggested Citation: Suggested Citation