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Cash Flow Matching

Author

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  • Garud Iyengar
  • Alfred Ma

Abstract

We propose a scenario-based optimization framework for solving the cash flow matching problem where the time horizon of the liabilities is longer than the maturities of available bonds and the interest rates are uncertain. Standard interest rate models can be used for scenario generation within this framework. The optimal portfolio is found by minimizing the cost at a specific level of shortfall risk measured by the conditional tail expectation (CTE), also known as conditional valueat-risk (CVaR) or Tail-VaR. The resulting optimization problem is still a linear program (LP) as in the classical cash flow matching approach. This framework can be employed in situations when the classical cash flow matching technique is not applicable.

Suggested Citation

  • Garud Iyengar & Alfred Ma, 2009. "Cash Flow Matching," North American Actuarial Journal, Taylor & Francis Journals, vol. 13(3), pages 370-378.
    • Handle: RePEc:taf:uaajxx:v:13:y:2009:i:3:p:370-378
    DOI: 10.1080/10920277.2009.10597562
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    Cited by:

    1. Danjue Shang & Victor Kuzmenko & Stan Uryasev, 2018. "Cash flow matching with risks controlled by buffered probability of exceedance and conditional value-at-risk," Annals of Operations Research, Springer, vol. 260(1), pages 501-514, January.
    2. Christopher Bayliss & Marti Serra & Armando Nieto & Angel A. Juan, 2020. "Combining a Matheuristic with Simulation for Risk Management of Stochastic Assets and Liabilities," Risks, MDPI, vol. 8(4), pages 1-14, December.

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