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Confronting Model Misspecification In Finance: Tractable Collections Of Scenario Probability Measures For Robust Financial Optimization Problems

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  • CRAIG FRIEDMAN

    (Risk Solutions, Standard & Poor's, 55 Water Street, 46th floor, New York, NY 10041, USA)

Abstract

Despite the widespread realization that financial models for contingent claim pricing, asset allocation and risk management depend critically on their underlying assumptions, the vast majority of financial models are based onsingle probability measures. In such models, asset prices are assumed to be random, but asset price probabilities are assumed to be known with certainty, an obviously false assumption.We explore practical methods to specify collections of probability measures for an assortment of important financial problems; we provide practical methods to solve the robust financial optimization problems that arise and, in the process, discover "dangerous" measures.

Suggested Citation

  • Craig Friedman, 2002. "Confronting Model Misspecification In Finance: Tractable Collections Of Scenario Probability Measures For Robust Financial Optimization Problems," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 5(01), pages 33-54.
    • Handle: RePEc:wsi:ijtafx:v:05:y:2002:i:01:n:s0219024902001353
    DOI: 10.1142/S0219024902001353
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    Cited by:

    1. Breuer, Thomas & Csiszár, Imre, 2013. "Systematic stress tests with entropic plausibility constraints," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1552-1559.
    2. Li, Jing, 2018. "Essays on model uncertainty in financial models," Other publications TiSEM 202cd910-7ef1-4db4-94ae-d, Tilburg University, School of Economics and Management.

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