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Diversified minimum-variance portfolios

Author

Listed:
  • Guillaume Coqueret

    (EDHEC - EDHEC Business School - UCL - Université catholique de Lille)

Abstract

We build on a one parameter family of weighting schemes arising from L2 -constrained portfolio optimization problems. The parameter allows to fine tune the trade-off between the volatility and the diversification of the portfolio. We propose two criteria in order to determine two unique portfolios: the first criterion requires that no weights be negative while the second one imposes a target diversification which is median between full concentration and full diversification. Both portfolios are empirically compared to classical benchmarks. The first one behaves very much like other popular Long-Only weighting schemes while the second displays a more aggressive profile, while generating moderate turnover. We also discuss implementation issues, as well as estimation related problems.

Suggested Citation

  • Guillaume Coqueret, 2015. "Diversified minimum-variance portfolios," Post-Print hal-02312223, HAL.
    • Handle: RePEc:hal:journl:hal-02312223
    DOI: 10.1007/s10436-014-0253-x
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    Citations

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    Cited by:

    1. Guillaume Coqueret, 2017. "Empirical properties of a heterogeneous agent model in large dimensions," Post-Print hal-02312186, HAL.
    2. Francisco Fernández-Navarro & Luisa Martínez-Nieto & Mariano Carbonero-Ruz & Teresa Montero-Romero, 2021. "Mean Squared Variance Portfolio: A Mixed-Integer Linear Programming Formulation," Mathematics, MDPI, vol. 9(3), pages 1-13, January.
    3. Bessler, Wolfgang & Taushanov, Georgi & Wolff, Dominik, 2021. "Optimal asset allocation strategies for international equity portfolios: A comparison of country versus industry optimization," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 72(C).
    4. Ammann, Manuel & Coqueret, Guillaume & Schade, Jan-Philip, 2016. "Characteristics-based portfolio choice with leverage constraints," Journal of Banking & Finance, Elsevier, vol. 70(C), pages 23-37.
    5. Vigo Pereira, Caio, 2021. "Portfolio efficiency with high-dimensional data as conditioning information," International Review of Financial Analysis, Elsevier, vol. 77(C).
    6. Wolfgang Bessler & Georgi Taushanov & Dominik Wolff, 2021. "Factor investing and asset allocation strategies: a comparison of factor versus sector optimization," Journal of Asset Management, Palgrave Macmillan, vol. 22(6), pages 488-506, October.
    7. Guillaume Coqueret, 2017. "Empirical properties of a heterogeneous agent model in large dimensions," Post-Print hal-02000726, HAL.
    8. Dian Zhu & Andrew J. Heunis, 2017. "Quadratic minimization with portfolio and intertemporal wealth constraints," Annals of Finance, Springer, vol. 13(3), pages 299-340, August.
    9. Gilles Boevi Koumou, 2020. "Diversification and portfolio theory: a review," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(3), pages 267-312, September.
    10. Coqueret, Guillaume, 2017. "Empirical properties of a heterogeneous agent model in large dimensions," Journal of Economic Dynamics and Control, Elsevier, vol. 77(C), pages 180-201.
    11. Guillaume Coqueret, 2016. "Empirical properties of a heterogeneous agent model in large dimensions," Post-Print hal-02088097, HAL.
    12. Guillaume Chevalier & Guillaume Coqueret & Thomas Raffinot, 2022. "Supervised portfolios," Post-Print hal-04144588, HAL.

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