IDEAS home Printed from https://ideas.repec.org/a/spr/snopef/v1y2020i3d10.1007_s43069-020-00025-0.html
   My bibliography  Save this article

Fast Quadratic Programming for Mean-Variance Portfolio Optimisation

Author

Listed:
  • Vasileios E. Kontosakos

    (Monash University
    Group Risk, Allianz SE)

Abstract

In this paper, a vectorised quadratic convex optimisation algorithm based on Matlab’s quadprog built-in function is proposed. We target specifically a classic problem confronted by portfolio analysts, that of optimising asset allocation when choosing among several asset classes, in the context of Markowitz’s modern portfolio theory. Simulating return trajectories for several asset classes, we formulate the optimisation routine in such a way that is able to handle multiple scenarios at the same time, instead of on a one-by-one basis, reducing computational times significantly, without introducing observable estimation errors. A sensitivity analysis is offered with respect to the optimal batch size.

Suggested Citation

  • Vasileios E. Kontosakos, 2020. "Fast Quadratic Programming for Mean-Variance Portfolio Optimisation," SN Operations Research Forum, Springer, vol. 1(3), pages 1-15, September.
    • Handle: RePEc:spr:snopef:v:1:y:2020:i:3:d:10.1007_s43069-020-00025-0
    DOI: 10.1007/s43069-020-00025-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s43069-020-00025-0
    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/s43069-020-00025-0?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. Liu, Yong-Jun & Zhang, Wei-Guo, 2013. "Fuzzy portfolio optimization model under real constraints," Insurance: Mathematics and Economics, Elsevier, vol. 53(3), pages 704-711.
    2. Čermák, M. & Sysala, S. & Valdman, J., 2019. "Efficient and flexible MATLAB implementation of 2D and 3D elastoplastic problems," Applied Mathematics and Computation, Elsevier, vol. 355(C), pages 595-614.
    3. Shinji Mizuno & Michael J. Todd & Yinyu Ye, 1993. "On Adaptive-Step Primal-Dual Interior-Point Algorithms for Linear Programming," Mathematics of Operations Research, INFORMS, vol. 18(4), pages 964-981, November.
    4. Alexander, Gordon J. & Baptista, Alexandre M., 2002. "Economic implications of using a mean-VaR model for portfolio selection: A comparison with mean-variance analysis," Journal of Economic Dynamics and Control, Elsevier, vol. 26(7-8), pages 1159-1193, July.
    5. Margarida Abreu & Victor Mendes, 2010. "Financial literacy and portfolio diversification," Quantitative Finance, Taylor & Francis Journals, vol. 10(5), pages 515-528.
    6. Lin, Chang-Chun & Liu, Yi-Ting, 2008. "Genetic algorithms for portfolio selection problems with minimum transaction lots," European Journal of Operational Research, Elsevier, vol. 185(1), pages 393-404, February.
    7. Gârleanu, Nicolae & Pedersen, Lasse Heje, 2016. "Dynamic portfolio choice with frictions," Journal of Economic Theory, Elsevier, vol. 165(C), pages 487-516.
    8. Quaranta, Anna Grazia & Zaffaroni, Alberto, 2008. "Robust optimization of conditional value at risk and portfolio selection," Journal of Banking & Finance, Elsevier, vol. 32(10), pages 2046-2056, October.
    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. Liu, Yong-Jun & Zhang, Wei-Guo, 2015. "A multi-period fuzzy portfolio optimization model with minimum transaction lots," European Journal of Operational Research, Elsevier, vol. 242(3), pages 933-941.
    2. Chun-Hao Chen & Jonathan Coupe & Tzung-Pei Hong, 2023. "An Accelerated Optimization Approach for Finding Diversified Industrial Group Stock Portfolios with Natural Group Detection," Mathematics, MDPI, vol. 11(14), pages 1-25, July.
    3. Xu, Qifa & Zhou, Yingying & Jiang, Cuixia & Yu, Keming & Niu, Xufeng, 2016. "A large CVaR-based portfolio selection model with weight constraints," Economic Modelling, Elsevier, vol. 59(C), pages 436-447.
    4. Gordon J. Alexander & Alexandre M. Baptista, 2004. "A Comparison of VaR and CVaR Constraints on Portfolio Selection with the Mean-Variance Model," Management Science, INFORMS, vol. 50(9), pages 1261-1273, September.
    5. Giovanni Bonaccolto & Massimiliano Caporin & Sandra Paterlini, 2018. "Asset allocation strategies based on penalized quantile regression," Computational Management Science, Springer, vol. 15(1), pages 1-32, January.
    6. Chiang, Thomas C., 2019. "Empirical analysis of intertemporal relations between downside risks and expected returns—Evidence from Asian markets," Research in International Business and Finance, Elsevier, vol. 47(C), pages 264-278.
    7. TAVARES Fernando Oliveira & ALMEIDA Luís Gomes & SOARES Vasco Jorge & TAVARES Vasco Capela, 2022. "Financial literacy: an exploratory analysis in Portugal," Studies in Business and Economics, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 17(2), pages 252-269, August.
    8. Dirk Schoenmaker, 2017. "A macro approach to international bank resolution," Policy Contributions 21231, Bruegel.
    9. Migliavacca, Milena & Goodell, John W. & Paltrinieri, Andrea, 2023. "A bibliometric review of portfolio diversification literature," International Review of Financial Analysis, Elsevier, vol. 90(C).
    10. Christoph Belak & Lukas Mich & Frank T. Seifried, 2019. "Optimal Investment for Retail Investors with Flooredand Capped Costs," Working Paper Series 2019-06, University of Trier, Research Group Quantitative Finance and Risk Analysis.
    11. Elisa Darriet & Marianne Guille & Jean-Christophe Vergnaud, 2021. "Financial Literacy and Numeracy," Documents de travail du Centre d'Economie de la Sorbonne 21031, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    12. Jeroen Rombouts & Marno Verbeek, 2009. "Evaluating portfolio Value-at-Risk using semi-parametric GARCH models," Quantitative Finance, Taylor & Francis Journals, vol. 9(6), pages 737-745.
    13. Pak, Tae-Young, 2023. "Relative deprivation and financial risk taking✰," Finance Research Letters, Elsevier, vol. 55(PA).
    14. Bo Zhang & Jin Peng & Shengguo Li, 2015. "Uncertain programming models for portfolio selection with uncertain returns," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(14), pages 2510-2519, October.
    15. Nikitopoulos, Christina Sklibosios & Thomas, Alice Carole & Wang, Jianxin, 2023. "The economic impact of daily volatility persistence on energy markets," Journal of Commodity Markets, Elsevier, vol. 30(C).
    16. Lars Hornuf & Matthias Schmitt & Eliza Stenzhorn, 2020. "Does a Local Bias Exist in Equity Crowdfunding?," CESifo Working Paper Series 8154, CESifo.
    17. Nonthachote Chatsanga & Andrew J. Parkes, 2016. "International Portfolio Optimisation with Integrated Currency Overlay Costs and Constraints," Papers 1611.01463, arXiv.org.
    18. Kim, Hohyun & Kim, Kyoung Tae & Hanna, Sherman D., 2022. "The Effect of Investment Literacy on the Likelihood of Retail Investor Margin Trading and Having a Margin Call," Finance Research Letters, Elsevier, vol. 45(C).
    19. Gangwar, Rachna & Singh, Ritvik, 2018. "Analyzing Factors Affecting Financial Literacy and its Impact on Investment Behavior among Adults in India," MPRA Paper 89452, University Library of Munich, Germany.
    20. Illes, Tibor & Nagy, Marianna, 2007. "A Mizuno-Todd-Ye type predictor-corrector algorithm for sufficient linear complementarity problems," European Journal of Operational Research, Elsevier, vol. 181(3), pages 1097-1111, September.

    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:snopef:v:1:y:2020:i:3:d:10.1007_s43069-020-00025-0. 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.