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Portfolio Optimization Using Multivariate t-Copulas with Conditionally Skewed Margins

Author

Listed:
  • Chirag Shekhar

    (Birla Institute of Technology and Science, Pilani - K.K. Birla Goa Campus, INDIA)

  • Mark Trede

    (Department of Economics, Westfalische Wilhelms-Universitat Munster, Am Stadtgraben 9, 48161 M¨¹nster, GERMANY)

Abstract
Over the last few decades, copulas have consistently gained significance in finance research, due to their usefulness in risk modeling. However, the idea of implicitly representing dependencies between multiple assets in a single mathematical entity is extremely useful in portfolio allocation models as well. While Church (2012) and many others have exploited these benefits, the efficiency of such frameworks in capturing the most essential features of financial data can still be enhanced. An obvious improvement would be to incorporate the fact that financial returns are generally asymmetric and skewed in nature, and therefore asymmetric (or skewed) margins can be used to describe them in a suitable copula framework. In this paper, we consolidate this idea with a GARCH(1,1) pre-whitening method that takes into account inter-temporal dependencies of returns, and use a utility maximization approach to find optimal portfolio allocation schemes. We show that the gains of optimal weighting, in terms of certainty equivalent returns, can be substantial for utility functions with reasonable risk aversion.

Suggested Citation

  • Chirag Shekhar & Mark Trede, 2017. "Portfolio Optimization Using Multivariate t-Copulas with Conditionally Skewed Margins," Review of Economics & Finance, Better Advances Press, Canada, vol. 9, pages 29-41, August.
    • Handle: RePEc:bap:journl:170303
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    References listed on IDEAS

    as
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    Cited by:

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    2. Le, Tuan Anh & Dao, Thi Thanh Binh, 2021. "Portfolio optimization under mean-CVaR simulation with copulas on the Vietnamese stock exchange," MPRA Paper 111105, University Library of Munich, Germany.

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    More about this item

    Keywords

    Utility maximization; Portfolio management; GARCH process; Multivariate return distributions; Copula;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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