IDEAS home Printed from https://ideas.repec.org/a/spr/cejnor/v31y2023i1d10.1007_s10100-022-00808-2.html
   My bibliography  Save this article

Portfolio optimization with asset preselection using data envelopment analysis

Author

Listed:
  • Mohammad Mehdi Hosseinzadeh

    (University of Bergamo
    University of Bergamo)

  • Sergio Ortobelli Lozza

    (University of Bergamo
    VSB Technical University of Ostrava)

  • Farhad Hosseinzadeh Lotfi

    (Islamic Azad University)

  • Vittorio Moriggia

    (University of Bergamo)

Abstract

This paper uses data envelopment analysis (DEA) approach as a nonparametric efficiency analysis tool to preselect efficient assets in large-scale portfolio problems. Thus, we reduce the dimensionality of portfolio problems, considering multiple asset performance criteria in a linear DEA model. We first introduce several reward/risk criteria that are typically used in portfolio literature to identify features of financial returns. Secondly, we suggest some DEA input/output sets for preselecting efficient assets in a large-scale portfolio framework. Then, we evaluate the impact of the preselected assets in different portfolio optimization strategies. In particular, we propose an ex-post empirical analysis based on two alternative datasets: the components of S &P500 and the Fama and French 100 portfolio formed on size and book to market. According to this empirical analysis we observe better performances of the DEA preselection than the classic PCA factor models for large scale portfolio selection problems. Moreover, the proposed model outperform the S &P500 index and the strategy based on the fully diversified portfolio.

Suggested Citation

  • Mohammad Mehdi Hosseinzadeh & Sergio Ortobelli Lozza & Farhad Hosseinzadeh Lotfi & Vittorio Moriggia, 2023. "Portfolio optimization with asset preselection using data envelopment analysis," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 31(1), pages 287-310, March.
    • Handle: RePEc:spr:cejnor:v:31:y:2023:i:1:d:10.1007_s10100-022-00808-2
    DOI: 10.1007/s10100-022-00808-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10100-022-00808-2
    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/s10100-022-00808-2?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. Sergio Ortobelli Lozza & Enrico Angelelli & Daniele Toninelli, 2011. "Set-Portfolio Selection with the Use of Market Stochastic Bounds," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 47(0), pages 5-24, November.
    2. R. Mantegna, 1999. "Hierarchical structure in financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 11(1), pages 193-197, September.
    3. Sergio Ortobelli Lozza & Haim Shalit & Frank J. Fabozzi, 2013. "Portfolio Selection Problems Consistent With Given Preference Orderings," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 16(05), pages 1-38.
    4. N Adler & B Golany, 2002. "Including principal component weights to improve discrimination in data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(9), pages 985-991, September.
    5. Sergio Ortobelli & Tomáš Tichý, 2015. "On the impact of semidefinite positive correlation measures in portfolio theory," Annals of Operations Research, Springer, vol. 235(1), pages 625-652, December.
    6. Murthi, B. P. S. & Choi, Yoon K. & Desai, Preyas, 1997. "Efficiency of mutual funds and portfolio performance measurement: A non-parametric approach," European Journal of Operational Research, Elsevier, vol. 98(2), pages 408-418, April.
    7. Stephen A. Ross, 2005. "Mutual Fund Separation in Financial Theory—The Separating Distributions," World Scientific Book Chapters, in: Sudipto Bhattacharya & George M Constantinides (ed.), Theory Of Valuation, chapter 10, pages 309-356, World Scientific Publishing Co. Pte. Ltd..
    8. Varga-Haszonits, I. & Kondor, I., 2007. "Noise sensitivity of portfolio selection in constant conditional correlation GARCH models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 385(1), pages 307-318.
    9. Lim, Sungmook & Oh, Kwang Wuk & Zhu, Joe, 2014. "Use of DEA cross-efficiency evaluation in portfolio selection: An application to Korean stock market," European Journal of Operational Research, Elsevier, vol. 236(1), pages 361-368.
    10. Banihashemi, Shokoofeh & Navidi, Sarah, 2017. "Portfolio performance evaluation in Mean-CVaR framework: A comparison with non-parametric methods value at risk in Mean-VaR analysis," Operations Research Perspectives, Elsevier, vol. 4(C), pages 21-28.
    11. Jiahan Li, 2015. "Sparse and Stable Portfolio Selection With Parameter Uncertainty," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(3), pages 381-392, July.
    12. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    13. Merton, Robert C, 1981. "On Market Timing and Investment Performance. I. An Equilibrium Theory of Value for Market Forecasts," The Journal of Business, University of Chicago Press, vol. 54(3), pages 363-406, July.
    14. Jiaqin Chen & Ming Yuan, 2016. "Efficient Portfolio Selection in a Large Market," Journal of Financial Econometrics, Oxford University Press, vol. 14(3), pages 496-524.
    15. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    16. Huyen Nguyen-Thi-Thanh, 2006. "On the Use of Data Envelopment Analysis in Hedge Fund Performance Appraisal," Working Papers halshs-00120292, HAL.
    17. Jegadeesh, Narasimhan & Titman, Sheridan, 1995. "Overreaction, Delayed Reaction, and Contrarian Profits," The Review of Financial Studies, Society for Financial Studies, vol. 8(4), pages 973-993.
    18. Pflug, Georg Ch. & Pichler, Alois & Wozabal, David, 2012. "The 1/N investment strategy is optimal under high model ambiguity," Journal of Banking & Finance, Elsevier, vol. 36(2), pages 410-417.
    19. Martin Eling, 2006. "Performance measurement of hedge funds using data envelopment analysis," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 20(4), pages 442-471, December.
    20. Joro, Tarja & Na, Paul, 2006. "Portfolio performance evaluation in a mean-variance-skewness framework," European Journal of Operational Research, Elsevier, vol. 175(1), pages 446-461, November.
    21. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    22. Joe Zhu, 2014. "DEA Cross Efficiency," International Series in Operations Research & Management Science, in: Quantitative Models for Performance Evaluation and Benchmarking, edition 3, chapter 4, pages 61-92, Springer.
    23. Morey, Matthew R. & Morey, Richard C., 1999. "Mutual fund performance appraisals: a multi-horizon perspective with endogenous benchmarking," Omega, Elsevier, vol. 27(2), pages 241-258, April.
    24. Jegadeesh, Narasimhan & Titman, Sheridan, 1993. "Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency," Journal of Finance, American Finance Association, vol. 48(1), pages 65-91, March.
    25. Kondor, Imre & Pafka, Szilard & Nagy, Gabor, 2007. "Noise sensitivity of portfolio selection under various risk measures," Journal of Banking & Finance, Elsevier, vol. 31(5), pages 1545-1573, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ghaemi Asl, Mahdi & Rashidi, Muhammad Mahdi & Tavakkoli, Hamid Raza & Rezgui, Hichem, 2024. "Does Islamic investing modify portfolio performance? Time-varying optimization strategies for conventional and Shariah energy-ESG-utilities portfolio," The Quarterly Review of Economics and Finance, Elsevier, vol. 94(C), pages 37-57.

    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. J. Francisco Rubio & Neal Maroney & M. Kabir Hassan, 2018. "Can Efficiency of Returns Be Considered as a Pricing Factor?," Computational Economics, Springer;Society for Computational Economics, vol. 52(1), pages 25-54, June.
    2. Martin Eling, 2006. "Performance measurement of hedge funds using data envelopment analysis," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 20(4), pages 442-471, December.
    3. Tarnaud, Albane Christine & Leleu, Hervé, 2018. "Portfolio analysis with DEA: Prior to choosing a model," Omega, Elsevier, vol. 75(C), pages 57-76.
    4. Liu, Wenbin & Zhou, Zhongbao & Liu, Debin & Xiao, Helu, 2015. "Estimation of portfolio efficiency via DEA," Omega, Elsevier, vol. 52(C), pages 107-118.
    5. Sergio Ortobelli & Noureddine Kouaissah & Tomáš Tichý, 2017. "On the impact of conditional expectation estimators in portfolio theory," Computational Management Science, Springer, vol. 14(4), pages 535-557, October.
    6. Solórzano-Taborga, Pablo & Alonso-Conde, Ana Belén & Rojo-Suárez, Javier, 2018. "Efficiency and Persistence of Spanish Absolute Return Funds || Eficiencia y persistencia de los fondos de retorno absolutos españoles," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 25(1), pages 186-214, Junio.
    7. Glawischnig, Markus & Sommersguter-Reichmann, Margit, 2010. "Assessing the performance of alternative investments using non-parametric efficiency measurement approaches: Is it convincing?," Journal of Banking & Finance, Elsevier, vol. 34(2), pages 295-303, February.
    8. Lamb, John D. & Tee, Kai-Hong, 2012. "Data envelopment analysis models of investment funds," European Journal of Operational Research, Elsevier, vol. 216(3), pages 687-696.
    9. Mousavi, Mohammad M. & Ouenniche, Jamal & Xu, Bing, 2015. "Performance evaluation of bankruptcy prediction models: An orientation-free super-efficiency DEA-based framework," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 64-75.
    10. Ruiyue Lin & Zhiping Chen & Qianhui Hu & Zongxin Li, 2017. "Dynamic network DEA approach with diversification to multi-period performance evaluation of funds," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(3), pages 821-860, July.
    11. Banker, Rajiv & Chen, Janice Y.S. & Klumpes, Paul, 2016. "A trade-level DEA model to evaluate relative performance of investment fund managers," European Journal of Operational Research, Elsevier, vol. 255(3), pages 903-910.
    12. Lin, Ruiyue & Liu, Qian, 2021. "Multiplier dynamic data envelopment analysis based on directional distance function: An application to mutual funds," European Journal of Operational Research, Elsevier, vol. 293(3), pages 1043-1057.
    13. Panayotis Alexakis & Ioannis Tsolas, 2011. "Appraisal of Mutual Equity Fund Performance Using Data Envelopment Analysis," Multinational Finance Journal, Multinational Finance Journal, vol. 15(3-4), pages 273-296, September.
    14. U D Kumar & A B Roy & H Saranga & K Singal, 2010. "Analysis of hedge fund strategies using slack-based DEA models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(12), pages 1746-1760, December.
    15. Tsolas, Ioannis E., 2014. "Precious metal mutual fund performance appraisal using DEA modeling," Resources Policy, Elsevier, vol. 39(C), pages 54-60.
    16. Pablo Solórzano-Taborga & Ana Belén Alonso-Conde & Javier Rojo-Suárez, 2020. "Data Envelopment Analysis and Multifactor Asset Pricing Models," IJFS, MDPI, vol. 8(2), pages 1-18, April.
    17. Andreu, Laura & Serrano, Miguel & Vicente, Luis, 2019. "Efficiency of mutual fund managers: A slacks-based manager efficiency index," European Journal of Operational Research, Elsevier, vol. 273(3), pages 1180-1193.
    18. Martin Branda, 2016. "Mean-value at risk portfolio efficiency: approaches based on data envelopment analysis models with negative data and their empirical behaviour," 4OR, Springer, vol. 14(1), pages 77-99, March.
    19. Sweksha Srivastava & Abha Aggarwal & Pooja Bansal, 2024. "Efficiency Evaluation of Assets and Optimal Portfolio Generation by Cross Efficiency and Cumulative Prospect Theory," Computational Economics, Springer;Society for Computational Economics, vol. 63(1), pages 129-158, January.
    20. Sergio Ortobelli & Tomáš Tichý, 2015. "On the impact of semidefinite positive correlation measures in portfolio theory," Annals of Operations Research, Springer, vol. 235(1), pages 625-652, December.

    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:spr:cejnor:v:31:y:2023:i:1:d:10.1007_s10100-022-00808-2. 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.