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A provisioning problem with stochastic payments

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Listed author(s):
  • Pagnoncelli, Bernardo K.
  • Vanduffel, Steven

Abstract

We consider the problem of determining the minimal requirement one must establish in order to meet a series of future random payments. It is shown in a very general setting that this problem can be recast as a chance constrained model and how the technique of Sample Average Approximation can be employed to find solutions. We also use comonotonic theory to analyze analytical approximations in a restricted Gaussian setting. Our numerical illustrations demonstrate that the Sample Average Approximation is a viable and efficient way to solve the stated problem generally and outperforms the analytical approximations. In passing we present a result that is related to Stein’s famous lemma (Stein, 1981) and is of interest in itself.

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Article provided by Elsevier in its journal European Journal of Operational Research.

Volume (Year): 221 (2012)
Issue (Month): 2 ()
Pages: 445-453

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Handle: RePEc:eee:ejores:v:221:y:2012:i:2:p:445-453
DOI: 10.1016/j.ejor.2012.01.065
Contact details of provider: Web page: http://www.elsevier.com/locate/eor

Keywords: Risk management; Solvency; Comonotonicity; Sample Average Approximation;

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  1. Harrison, J. Michael & Kreps, David M., 1979. "Martingales and arbitrage in multiperiod securities markets," Journal of Economic Theory, Elsevier, vol. 20(3), pages 381-408, June.
  2. Dilip B. Madan & Frank Milne, 1991. "Option Pricing With V. G. Martingale Components," Mathematical Finance, Wiley Blackwell, vol. 1(4), pages 39-55.
  3. Dupacova, Jitka & Gaivoronski, Alexei & Kos, Zdenek & Szantai, Tamas, 1991. "Stochastic programming in water management: A case study and a comparison of solution techniques," European Journal of Operational Research, Elsevier, vol. 52(1), pages 28-44, May.
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  7. J. Dhaene & S. Vanduffel & M. J. Goovaerts & R. Kaas & D. Vyncke, 2005. "Comonotonic Approximations for Optimal Portfolio Selection Problems," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 72(2), pages 253-300.
  8. A. Charnes & W. W. Cooper & G. H. Symonds, 1958. "Cost Horizons and Certainty Equivalents: An Approach to Stochastic Programming of Heating Oil," Management Science, INFORMS, vol. 4(3), pages 235-263, April.
  9. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters,in: THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78 World Scientific Publishing Co. Pte. Ltd..
  10. Abdelaziz, Fouad Ben & Aouni, Belaid & Fayedh, Rimeh El, 2007. "Multi-objective stochastic programming for portfolio selection," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1811-1823, March.
  11. Hürlimann, Werner, 2010. "Analytical Pricing of the Unit-Linked Endowment with Guarantees and Periodic Premiums," ASTIN Bulletin: The Journal of the International Actuarial Association, Cambridge University Press, vol. 40(02), pages 631-653, November.
  12. Cesari, Riccardo & Cremonini, David, 2003. "Benchmarking, portfolio insurance and technical analysis: a Monte Carlo comparison of dynamic strategies of asset allocation," Journal of Economic Dynamics and Control, Elsevier, vol. 27(6), pages 987-1011, April.
  13. Kampas, Athanasios & White, Ben, 2003. "Probabilistic programming for nitrate pollution control: Comparing different probabilistic constraint approximations," European Journal of Operational Research, Elsevier, vol. 147(1), pages 217-228, May.
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Cited by:

  1. Tsai, Shing Chih & Zheng, Ya-Xin, 2013. "A simulation optimization approach for a two-echelon inventory system with service level constraints," European Journal of Operational Research, Elsevier, vol. 229(2), pages 364-374.
  2. repec:eee:ejores:v:262:y:2017:i:1:p:251-261 is not listed on IDEAS

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