IDEAS home Printed from https://ideas.repec.org/a/kap/compec/v64y2024i3d10.1007_s10614-023-10485-1.html
   My bibliography  Save this article

How to Keep Your Portfolio Close in Risk and Diversification to a Desired Benchmark

Author

Listed:
  • Argimiro Arratia

    (Universitat Politécnica de Catalunya)

  • Henryk Gzyl

    (IESA)

  • Silvia Mayoral

    (Universidad Carlos III de Madrid)

Abstract

The standard approach to portfolio management consists of determining the best trade-off between risk and return. This usually results in portfolios concentrated in a small collection of the available assets. To offset this one can start with a well-diversified portfolio, to be regarded as a benchmark, then search for a portfolio that improves upon its return. The main issue is that the search has to be carried out in a neighborhood in which diversification is maintained and the risk is under control. Here we examine three ways of defining the neighborhood of the well-diversified portfolio, and see that the nature of the optimal portfolio within that neighborhood changes considerably. As there is no universal choice for the distance between portfolios, this poses an interesting and hard problem for the portfolio manager.

Suggested Citation

  • Argimiro Arratia & Henryk Gzyl & Silvia Mayoral, 2024. "How to Keep Your Portfolio Close in Risk and Diversification to a Desired Benchmark," Computational Economics, Springer;Society for Computational Economics, vol. 64(3), pages 1489-1505, September.
    • Handle: RePEc:kap:compec:v:64:y:2024:i:3:d:10.1007_s10614-023-10485-1
    DOI: 10.1007/s10614-023-10485-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10614-023-10485-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10614-023-10485-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. SE Satchell & S Hwang, 2001. "Tracking error: Ex ante versus ex post measures," Journal of Asset Management, Palgrave Macmillan, vol. 2(3), pages 241-246, December.
    2. Gaivoronski, Alexei A. & Krylov, Sergiy & van der Wijst, Nico, 2005. "Optimal portfolio selection and dynamic benchmark tracking," European Journal of Operational Research, Elsevier, vol. 163(1), pages 115-131, May.
    3. Paskalis Glabadanidis, 2020. "Portfolio Strategies to Track and Outperform a Benchmark," JRFM, MDPI, vol. 13(8), pages 1-26, August.
    4. Navya Jayesh Mehta & Fan Yang, 2022. "Portfolio Optimization for Extreme Risks with Maximum Diversification: An Empirical Analysis," Risks, MDPI, vol. 10(5), pages 1-26, May.
    5. Rustam Ibragimov, 2009. "Portfolio diversification and value at risk under thick-tailedness," Quantitative Finance, Taylor & Francis Journals, vol. 9(5), pages 565-580.
    6. Li, Qian & Bao, Liang, 2014. "Enhanced index tracking with multiple time-scale analysis," Economic Modelling, Elsevier, vol. 39(C), pages 282-292.
    7. Cui, Hengxin & Tan, Ken Seng & Yang, Fan & Zhou, Chen, 2022. "Asymptotic analysis of portfolio diversification," Insurance: Mathematics and Economics, Elsevier, vol. 106(C), pages 302-325.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Héctor Jasso-Fuentes & Gladys D. Salgado-Suárez, 2024. "A discrete-time benchmark tracking problem in two markets subject to random environments," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 46(4), pages 1265-1294, December.
    2. Julio Cezar Soares Silva & Adiel Teixeira de Almeida Filho, 2023. "A systematic literature review on solution approaches for the index tracking problem in the last decade," Papers 2306.01660, arXiv.org, revised Jun 2023.
    3. Sant’Anna, Leonardo R. & Filomena, Tiago P. & Caldeira, João F., 2017. "Index tracking and enhanced indexing using cointegration and correlation with endogenous portfolio selection," The Quarterly Review of Economics and Finance, Elsevier, vol. 65(C), pages 146-157.
    4. Carol Alexander & Anca Dimitriu, 2003. "Equity Indexing: Conitegration and Stock Price Dispersion: A Regime Switiching Approach to market Efficiency," ICMA Centre Discussion Papers in Finance icma-dp2003-02, Henley Business School, University of Reading.
    5. Lijun Bo & Huafu Liao & Xiang Yu, 2020. "Optimal Tracking Portfolio with A Ratcheting Capital Benchmark," Papers 2006.13661, arXiv.org, revised Apr 2021.
    6. Di Giacinto, Marina & Federico, Salvatore & Gozzi, Fausto & Vigna, Elena, 2014. "Income drawdown option with minimum guarantee," European Journal of Operational Research, Elsevier, vol. 234(3), pages 610-624.
    7. Füss, Roland & Miebs, Felix & Trübenbach, Fabian, 2014. "A jackknife-type estimator for portfolio revision," Journal of Banking & Finance, Elsevier, vol. 43(C), pages 14-28.
    8. Spiridon Penev & Pavel Shevchenko & Wei Wu, 2019. "Myopic robust index tracking with Bregman divergence," Papers 1908.07659, arXiv.org, revised Jul 2021.
    9. Palomba, Giulio & Riccetti, Luca, 2012. "Portfolio frontiers with restrictions to tracking error volatility and value at risk," Journal of Banking & Finance, Elsevier, vol. 36(9), pages 2604-2615.
    10. Steven Kou & Xianhua Peng, 2016. "On the Measurement of Economic Tail Risk," Operations Research, INFORMS, vol. 64(5), pages 1056-1072, October.
    11. Sun, Chuting & Wu, Qi & Yan, Xing, 2024. "Dynamic CVaR portfolio construction with attention-powered generative factor learning," Journal of Economic Dynamics and Control, Elsevier, vol. 160(C).
    12. Christopher Dance & Alexei Gaivoronski, 2012. "Stochastic optimization for real time service capacity allocation under random service demand," Annals of Operations Research, Springer, vol. 193(1), pages 221-253, March.
    13. James Primbs & Chang Sung, 2008. "A Stochastic Receding Horizon Control Approach to Constrained Index Tracking," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 15(1), pages 3-24, March.
    14. Oliver Kley & Claudia Kluppelberg & Gesine Reinert, 2014. "Risk in a large claims insurance market with bipartite graph structure," Papers 1410.8671, arXiv.org, revised Nov 2015.
    15. Hill, Jonathan B. & Prokhorov, Artem, 2016. "GEL estimation for heavy-tailed GARCH models with robust empirical likelihood inference," Journal of Econometrics, Elsevier, vol. 190(1), pages 18-45.
    16. Lassance, Nathan & Vrins, Frédéric, 2023. "Portfolio selection: A target-distribution approach," European Journal of Operational Research, Elsevier, vol. 310(1), pages 302-314.
    17. Leonardo Riegel Sant’Anna & Tiago Pascoal Filomena & Pablo Cristini Guedes & Denis Borenstein, 2017. "Index tracking with controlled number of assets using a hybrid heuristic combining genetic algorithm and non-linear programming," Annals of Operations Research, Springer, vol. 258(2), pages 849-867, November.
    18. Di Lascio, F. Marta L. & Giammusso, Davide & Puccetti, Giovanni, 2018. "A clustering approach and a rule of thumb for risk aggregation," Journal of Banking & Finance, Elsevier, vol. 96(C), pages 236-248.
    19. Ankudinov, Andrei & Ibragimov, Rustam & Lebedev, Oleg, 2017. "Sanctions and the Russian stock market," Research in International Business and Finance, Elsevier, vol. 40(C), pages 150-162.
    20. Lijun Bo & Yijie Huang & Kaixin Yan & Xiang Yu, 2024. "Optimal consumption under relaxed benchmark tracking and consumption drawdown constraint," Papers 2410.16611, arXiv.org.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:compec:v:64:y:2024:i:3:d:10.1007_s10614-023-10485-1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.