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A methodology to avoid over-diversification of funds of equity funds An implementation case study for equity funds of funds in bull markets

Author

Listed:
  • Nadège Ribau-Peltre

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

  • Pascal Damel

    (LGIPM - Laboratoire de Génie Informatique, de Production et de Maintenance - UL - Université de Lorraine)

  • An Lethi

    (LGIPM - Laboratoire de Génie Informatique, de Production et de Maintenance - UL - Université de Lorraine)

Abstract

Funds of funds are funds that invest primarily in units of other funds. They have developed in Europe since the end of the 1990s. They exist because no fund manager can be excellent in all fields (all sectors, all geographical areas ...) and because it can therefore be interesting to compose funds from shares of funds managed by different management companies. As there is a higher diversification in funds of funds, they can be attractive at first glance. But studies have pointed out that they have some disadvantages, the main one being over-diversification. In this paper, we will review the literature on the issue of over-diversification by showing the consequences this overdiversification may have on the management and performance of funds of funds. Using Markowitz's mean-variance optimization method, we will on the one hand show that by building funds of funds from a panel of 551 equity funds, the efficient frontier is made up of funds of funds comprising from 1 to 11 funds with an average of 7.44 funds. This empirical study thus shows that the efficient frontier is composed of portfolios comprising a number of funds significantly below the professional standard (20 to 30 funds). Over-diversification and the accumulation of the resulting costs are therefore not a necessity. On the other hand, we will show that the mean-variance optimization method can be improved by DCA clustering techniques. A prior clustering of the initial database makes it indeed possible to reduce (by almost 10 in our example) the size of the database on which the Markowitz's meanvariance optimization is applied. The efficient frontier deriving from this reduced database is almost equivalent in terms of risk-adjusted performance as the one deriving from the initial database, while avoiding computational problems generated during the optimization process on wide databases (especially when including regulatory constraints).

Suggested Citation

  • Nadège Ribau-Peltre & Pascal Damel & An Lethi, 2018. "A methodology to avoid over-diversification of funds of equity funds An implementation case study for equity funds of funds in bull markets," Post-Print hal-03027770, HAL.
    • Handle: RePEc:hal:journl:hal-03027770
    Note: View the original document on HAL open archive server: https://hal.science/hal-03027770
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    References listed on IDEAS

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    1. Francesco Cesarone & Andrea Scozzari & Fabio Tardella, 2011. "Portfolio selection problems in practice: a comparison between linear and quadratic optimization models," Papers 1105.3594, arXiv.org.
    2. Stephen J. Brown & William N. Goetzmann & Bing Liang, 2005. "Fees On Fees In Funds Of Funds," World Scientific Book Chapters, in: H Gifford Fong (ed.), The World Of Hedge Funds Characteristics and Analysis, chapter 7, pages 141-160, World Scientific Publishing Co. Pte. Ltd..
    3. Lwin, Khin T. & Qu, Rong & MacCarthy, Bart L., 2017. "Mean-VaR portfolio optimization: A nonparametric approach," European Journal of Operational Research, Elsevier, vol. 260(2), pages 751-766.
    4. Shaojun Guo & John Leigh Box & Wenyang Zhang, 2017. "A Dynamic Structure for High-Dimensional Covariance Matrices and Its Application in Portfolio Allocation," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(517), pages 235-253, January.
    5. Andrew Ang & Matthew Rhodes-Kropf & Rui Zhao, 2008. "Do Funds-of-Funds Deserve Their Fees-on-Fees?," NBER Working Papers 13944, National Bureau of Economic Research, Inc.
    6. Schwert, G William & Seguin, Paul J, 1990. "Heteroskedasticity in Stock Returns," Journal of Finance, American Finance Association, vol. 45(4), pages 1129-1155, September.
    7. Victor DeMiguel & Lorenzo Garlappi & Francisco J. Nogales & Raman Uppal, 2009. "A Generalized Approach to Portfolio Optimization: Improving Performance by Constraining Portfolio Norms," Management Science, INFORMS, vol. 55(5), pages 798-812, May.
    8. Marc Senneret & Yannick Malevergne & Patrice Abry & Gerald Perrin & Laurent Jaffres, 2016. "Covariance Versus Precision Matrix Estimation for Efficient Asset Allocation," Post-Print halshs-03590388, HAL.
    9. Vincent Guigues, 2011. "Sensitivity analysis and calibration of the covariance matrix for stable portfolio selection," Computational Optimization and Applications, Springer, vol. 48(3), pages 553-579, April.
    10. Elton, Edwin J & Gruber, Martin J, 1973. "Estimating the Dependence Structure of Share Prices-Implications for Portfolio Selection," Journal of Finance, American Finance Association, vol. 28(5), pages 1203-1232, December.
    11. Libin Yang & William Rea & Alethea Rea, 2015. "Stock Selection with Principal Component Analysis," Working Papers in Economics 15/03, University of Canterbury, Department of Economics and Finance.
    12. Alessandro Carretta & Gianluca Mattarocci, 2009. "Funds of Funds Portfolio Composition and its Impact on Performance: Evidence from the Italian Market," Palgrave Macmillan Studies in Banking and Financial Institutions, in: Alessandro Carretta & Franco Fiordelisi & Gianluca Mattarocci (ed.), New Drivers of Performance in a Changing Financial World, chapter 5, pages 69-88, Palgrave Macmillan.
    13. John L. Evans & Stephen H. Archer, 1968. "Diversification And The Reduction Of Dispersion: An Empirical Analysis," Journal of Finance, American Finance Association, vol. 23(5), pages 761-767, December.
    14. Klapper, Leora & Sulla, Victor & Vittas, Dimitri, 2004. "The development of mutual funds around the world," Emerging Markets Review, Elsevier, vol. 5(1), pages 1-38, March.
    15. Gregoriou, Greg N., 2006. "Funds of Hedge Funds," Elsevier Monographs, Elsevier, edition 1, number 9780750679848.
    16. MacKinlay, A. Craig, 1987. "On multivariate tests of the CAPM," Journal of Financial Economics, Elsevier, vol. 18(2), pages 341-371, June.
    17. Simone Brands & David R. Gallagher, 2005. "Portfolio selection, diversification and fund‐of‐funds: a note," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 45(2), pages 185-197, July.
    18. André A.P. Santos, 2015. "Beating the market with small portfolios: Evidence from Brazil," Economia, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics], vol. 16(1), pages 22-31.
    19. Ulf, Herold & Raimond, Maurer, 2006. "Portfolio Choice and Estimation Risk. A Comparison of Bayesian to Heuristic Approaches," ASTIN Bulletin, Cambridge University Press, vol. 36(1), pages 135-160, May.
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