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On the robustness of portfolio allocation under copula misspecification

Author

Listed:
  • Abdallah Ben Saida
  • Jean-Luc Prigent

    (THEMA - Théorie économique, modélisation et applications - CNRS - Centre National de la Recherche Scientifique - CY - CY Cergy Paris Université)

Abstract

The copula theory allows to easily model the probability distributions of random vectors by separately estimating the marginal distributions and the dependence structure of the components represented by the copula itself. Copula functions generally provide significant improvements to the financial portfolio allocation problem. However, being given the large spectrum of available copulas, the choice of the best model is rather complex. This paper investigates the copula misspecification impact on the portfolio allocation problem, which is an important risk model issue. We address this issue from the perspective of the behavioral portfolio theory through the Zakamouline (Quant Finance 14(4):699–710, 2014) approach by considering an investor allocating his wealth between a risk-free asset and a risky asset. Our main objective is to assess investors’ sensitivities to the choice of the probability of the random vector, namely both the marginal distributions and the copula function. This analysis is conducted with respect to their degrees of risk and loss aversions, for different compositions of the risky asset, and for different investment horizons.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Abdallah Ben Saida & Jean-Luc Prigent, 2018. "On the robustness of portfolio allocation under copula misspecification," Post-Print hal-03679698, HAL.
    • Handle: RePEc:hal:journl:hal-03679698
    DOI: 10.1007/s10479-016-2137-0
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    Cited by:

    1. Henryk Zähle, 2022. "A concept of copula robustness and its applications in quantitative risk management," Finance and Stochastics, Springer, vol. 26(4), pages 825-875, October.
    2. Su, Xiaoshan & Li, Yuhan, 2024. "Robust portfolio selection with subjective risk aversion under dependence uncertainty," Economic Modelling, Elsevier, vol. 132(C).
    3. Sabri Boubaker & Zhenya Liu & Yaosong Zhan, 2022. "Risk management for crude oil futures: an optimal stopping-timing approach," Annals of Operations Research, Springer, vol. 313(1), pages 9-27, June.
    4. Erdinc Akyildirim & Frank J. Fabozzi & Ahmet Goncu & Ahmet Sensoy, 2022. "Statistical arbitrage in jump-diffusion models with compound Poisson processes," Annals of Operations Research, Springer, vol. 313(2), pages 1357-1371, June.
    5. E. Allevi & L. Boffino & M. E. Giuli & G. Oggioni, 2019. "Analysis of long-term natural gas contracts with vine copulas in optimization portfolio problems," Annals of Operations Research, Springer, vol. 274(1), pages 1-37, March.

    More about this item

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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