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Term Structure Models in Multistage Stochastic Programming: Estimation and Approximation

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  • Karl Frauendorfer
  • Michael Schürle

Abstract

This paper investigates some common interest rate models for scenario generation in financial applications of stochastic optimization. We discuss conditions for the underlying distributions of state variables which preserve convexity of value functions in a multistage stochastic program. One- and multi-factor term structure models are estimated based on historical data for the Swiss Franc. An analysis of the dynamic behavior of interest rates generated with these models reveals several deficiencies which have an impact on the performance of investment policies derived from the stochastic program. While barycentric approximation is used here for the generation of scenario trees, these insights may be generalized to other discretization techniques as well. Copyright Kluwer Academic Publishers 2000

Suggested Citation

  • Karl Frauendorfer & Michael Schürle, 2000. "Term Structure Models in Multistage Stochastic Programming: Estimation and Approximation," Annals of Operations Research, Springer, vol. 100(1), pages 189-209, December.
    • Handle: RePEc:spr:annopr:v:100:y:2000:i:1:p:189-209:10.1023/a:1019223318808
    DOI: 10.1023/A:1019223318808
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    Cited by:

    1. Vlasta Kaňková, 2007. "Multistage Stochastic Programming via Autoregressive Sequences [Autoregresní posloupnosti v úlohách vícestupňového stochastického programování]," Acta Oeconomica Pragensia, Prague University of Economics and Business, vol. 2007(4), pages 99-110.
    2. Frauendorfer, Karl & Schurle, Michael, 2003. "Management of non-maturing deposits by multistage stochastic programming," European Journal of Operational Research, Elsevier, vol. 151(3), pages 602-616, December.

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