LP Modeling for Asset-Liability Management: A Survey of Choices and Simplifications

Abstract

Dynamic linear programming (LP) models for asset-liability management (ALM) are quite powerful and flexible but face two challenges: (1) many modeling choices, not all consistent with one another or with finance theory, and (2) solution difficulties due to the large number of scenarios obtained from standard interest-rate models. We first survey these modeling choices with a view to help researchers make self-consistent choices. Next, we review how the dynamic LP model for ALM and the representation of uncertainty therein have been simplified in the past to motivate new or hybrid models emphasizing tractability. To this end, we review existing static LP models as extreme modeling simplifications and aggregation as a simplification of uncertainty.

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No-arbitrage bounds for financial scenarios

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Determining supply requirement in the sales-and-operations-planning (S&OP) process under demand uncertainty: a stochastic programming formulation and a spreadsheet implementation

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