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Are Smart Beta strategies suitable for hedge fund portfolios?

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  • Asmerilda Hitaj
  • Giovanni Zambruno

Abstract

In the equity context different Smart Beta strategies (such as the equally weighted, global minimum variance, equal risk contribution and maximum diversified ratio) have been proposed as alternatives to the cap‐weighted index. These new approaches have attracted the attention of equity managers as different empirical analyses demonstrate the superiority of these strategies with respect to cap‐weighted and to strategies that consider only mean and variance. In this paper we focus our attention to hedge fund index portfolios and analyze if the results reported in the equity framework are still valid. We consider hedge fund index and equity portfolios, the approaches used for portfolio selection are the four ‘Smart Beta’ strategies, mean–variance and mean–variance–skewness. In the two latter approaches the Taylor approximation of a CARA expected utility function and the Polynomial Goal Programing (PGP) have been used. The obtained portfolios are analyzed in the in‐sample as well as in the out‐of‐sample perspectives.

Suggested Citation

  • Asmerilda Hitaj & Giovanni Zambruno, 2016. "Are Smart Beta strategies suitable for hedge fund portfolios?," Review of Financial Economics, John Wiley & Sons, vol. 29(1), pages 37-51, April.
  • Handle: RePEc:wly:revfec:v:29:y:2016:i:1:p:37-51
    DOI: 10.1016/j.rfe.2016.03.001
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    Cited by:

    1. Zeynep Cipiloglu Yildiz & Selim Baha Yildiz, 2022. "A portfolio construction framework using LSTM‐based stock markets forecasting," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 2356-2366, April.
    2. Asmerilda Hitaj & Lorenzo Mercuri & Edit Rroji, 2019. "Sensitivity analysis of Mixed Tempered Stable parameters with implications in portfolio optimization," Computational Management Science, Springer, vol. 16(1), pages 71-95, February.
    3. Massimiliano Kaucic & Filippo Piccotto & Gabriele Sbaiz, 2024. "A constrained swarm optimization algorithm for large-scale long-run investments using Sharpe ratio-based performance measures," Computational Management Science, Springer, vol. 21(1), pages 1-29, June.
    4. Gian Paolo Clemente & Rosanna Grassi & Asmerilda Hitaj, 2022. "Smart network based portfolios," Annals of Operations Research, Springer, vol. 316(2), pages 1519-1541, September.
    5. Gian Paolo Clemente & Rosanna Grassi & Asmerilda Hitaj, 2018. "Asset allocation: new evidence through network approaches," Papers 1810.09825, arXiv.org.
    6. Gian Paolo Clemente & Rosanna Grassi & Asmerilda Hitaj, 2019. "Smart network based portfolios," Papers 1907.01274, arXiv.org.
    7. Fabio Vanni & Asmerilda Hitaj & Elisa Mastrogiacomo, 2024. "Enhancing Portfolio Allocation: A Random Matrix Theory Perspective," Mathematics, MDPI, vol. 12(9), pages 1-16, May.
    8. Giorgio Consigli & Asmerilda Hitaj & Elisa Mastrogiacomo, 2019. "Portfolio choice under cumulative prospect theory: sensitivity analysis and an empirical study," Computational Management Science, Springer, vol. 16(1), pages 129-154, February.
    9. Gian Paolo Clemente & Rosanna Grassi & Asmerilda Hitaj, 2021. "Asset allocation: new evidence through network approaches," Annals of Operations Research, Springer, vol. 299(1), pages 61-80, April.

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