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Monte Carlo Optimization and Path Dependent Nonstationary Laws of Large Numbers

Author

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  • Y.M. Ermoliev
  • V.I. Norkin

Abstract

New types of laws of large numbers are derived by using connections between estimation and stochastic optimization problems. They enable one to "track" time-and-path dependent functionals by using, in general, nonlinear estimators. Proofs are based on the new stochastic version of the Lyapunov's method. Applications to Monte Carlo optimization, stochastic branch and bounds method and minimization of risk functions are discussed.

Suggested Citation

  • Y.M. Ermoliev & V.I. Norkin, 1998. "Monte Carlo Optimization and Path Dependent Nonstationary Laws of Large Numbers," Working Papers ir98009, International Institute for Applied Systems Analysis.
    • Handle: RePEc:wop:iasawp:ir98009
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    References listed on IDEAS

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    1. T.Y. Ermolieva, 1997. "The Design of Optimal Insurance Decisions in the Presence of Catastrophic Risks," Working Papers ir97068, International Institute for Applied Systems Analysis.
    2. T.Y. Ermolieva & Y.M. Ermoliev & V.I. Norkin, 1997. "Spatial Stochastic Model for Optimization Capacity of Insurance Networks Under Dependent Catastrophic Risks: Numerical Experiments," Working Papers ir97028, International Institute for Applied Systems Analysis.
    3. V.I. Norkin & G.C. Pflug & A. Ruszczynski, 1996. "A Branch and Bound Method for Stochastic Global Optimization," Working Papers wp96065, International Institute for Applied Systems Analysis.
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    Cited by:

    1. Y.M. Ermoliev & T.Y. Ermolieva & G.J. MacDonald & V.I. Norkin, 1998. "On the Design of Catastrophic Risk Portfolios," Working Papers ir98056, International Institute for Applied Systems Analysis.
    2. Gritsevskyi, Andrii & Nakicenovi, Nebojsa, 2000. "Modeling uncertainty of induced technological change," Energy Policy, Elsevier, vol. 28(13), pages 907-921, November.

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