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An Economic Evaluation of Model Risk in Long-term Asset Allocations

Author

Listed:
  • Christophe Boucher

    (CEREFIGE - Centre Européen de Recherche en Economie Financière et Gestion des Entreprises - UL - Université de Lorraine, EconomiX - EconomiX - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique)

  • Gregory Jannin

    (PRISM Sorbonne - Pôle de recherche interdisciplinaire en sciences du management - UP1 - Université Paris 1 Panthéon-Sorbonne)

  • Patrick Kouontchou

    (CEREFIGE - Centre Européen de Recherche en Economie Financière et Gestion des Entreprises - UL - Université de Lorraine)

  • Bertrand Maillet

    (A.A.Advisors-QCG - ABN AMRO, EIF - Europlace Institute of Finance, LEO - Laboratoire d'Économie d'Orleans [UMR7322] - UO - Université d'Orléans - UT - Université de Tours - CNRS - Centre National de la Recherche Scientifique)

Abstract

Following the recent crisis and the revealed weakness of risk management practices, regulators of developed markets have recommended that financial institutions assess model risk. Standard risk measures, such as the value-at-risk ( VaR), emerged during the 1990s as the industry standard for risk management and become today a key tool for asset allocation. This paper illustrates and estimates model risk, and focuses on the evaluation of its impact on optimal portfolios at various time horizons. Based on a long sample of US data, the paper finds a non-linear relation between VaR model errors and the horizon that impacts optimal asset allocations.

Suggested Citation

  • Christophe Boucher & Gregory Jannin & Patrick Kouontchou & Bertrand Maillet, 2013. "An Economic Evaluation of Model Risk in Long-term Asset Allocations," Post-Print hal-01369201, HAL.
    • Handle: RePEc:hal:journl:hal-01369201
    DOI: 10.1111/roie.12049
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    Cited by:

    1. Salah Mohamed Eladly, 2024. "Asset Quality, Firm Size and Volatility of Returns of Insurance Companies in Egypt," International Journal of Business and Management, Canadian Center of Science and Education, vol. 19(6), pages 308-308, December.
    2. Roberto Casarin & Bertrand B. Maillet & Anthony Osuntuyi, 2024. "Monte carlo within simulated annealing for integral constrained optimizations," Annals of Operations Research, Springer, vol. 334(1), pages 205-240, March.

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