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Large portfolio optimisation approaches

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Abstract

This paper makes an empirical comparison of prominent methods in portfolio optimisation, such as nodewise regression, the sample covariance matrix, observable factor model-based covariance matrices, linear and nonlinear shrinkage methods, and principal orthogonal complement thresholding (POET) estimators. Empirically, we find that the nodewise regression approach that uses a direct estimator of the sparse inverse covariance matrix improves portfolio performance among existing methods in mean-variance portfolio optimisation when the number of stocks is greater than the number of observations.

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Availability of data and materials

The data that support the findings of this study are available from the authors upon request.

Notes

  1. Proofs related to these theorems are presented in online supplementary material https://www.tandfonline.com/doi/suppl/10.1080/07350015.2019.1683018?scroll=top &role=tab.

  2. One-year t-bill rate is obtained from the website, https://datastore.borsaistanbul.com/.

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Acknowledgements

We are grateful to Ege University Planning and Monitoring Coordination of Organizational Development and Directorate of Library and Documentation for their support in editing and proofreading service of this study.

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The authors did not receive support from any organization for the submitted work

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Authors and Affiliations

  1. Department of Economics, Ege University, Izmir, Türkiye

    A. Özlem Önder

  2. Smart Capital, 35040, Izmir, Türkiye

    Esra Ulasan

Authors
  1. Esra Ulasan
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  2. A. Özlem Önder
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Contributions

All authors contributed to the study conception and design. Data collection and analysis were performed by EU. The first draft of the manuscript was written by all authors. All authors read and approved the final manuscript.

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Correspondence to A. Özlem Önder.

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Appendix

Appendix

Table 5 Monthly Portfolio performance of \(T=96\), \(n-T=36\)
Full size table
Table 6 Daily Period: Portfolio Performance of \(T=2002\), \(n-T=750\)
Full size table

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Ulasan, E., Önder, A.Ö. Large portfolio optimisation approaches. J Asset Manag 24, 485–497 (2023). https://doi.org/10.1057/s41260-023-00322-3

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