IDEAS home Printed from https://ideas.repec.org/a/spr/operea/v20y2020i2d10.1007_s12351-017-0361-2.html
   My bibliography  Save this article

Discrete fuzzy system orbits as a portfolio selection method

Author

Listed:
  • Sergio Pérez-Gonzaga

    (Universitat Politècnica de València)

  • Jorge Jordán-Núñez

    (Universitat Politècnica de València)

  • Pau Miro-Martinez

    (Universitat Politècnica de València)

Abstract

The purpose of this work is to approach the portfolio selection problem from a particular System Theory framework. The System will be formed by the set of public companies in the portfolio and a set of fuzzy relations on those companies. Starting with an equally split portfolio represented by a fuzzy set B, the orbit of B is computed for a particular period obtaining a portfolio to invest in the next period. We present an example finding nine portfolios to invest in 9 months and we compare them with some optimal portfolios in the efficient frontier given by the Modern Portfolio Theory and with some random generated portfolios. We find a better performance in returns for the portfolio based on the systemic method.

Suggested Citation

  • Sergio Pérez-Gonzaga & Jorge Jordán-Núñez & Pau Miro-Martinez, 2020. "Discrete fuzzy system orbits as a portfolio selection method," Operational Research, Springer, vol. 20(2), pages 1047-1053, June.
    • Handle: RePEc:spr:operea:v:20:y:2020:i:2:d:10.1007_s12351-017-0361-2
    DOI: 10.1007/s12351-017-0361-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12351-017-0361-2
    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/s12351-017-0361-2?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. 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.
    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. Harrison Hong & Terence Lim & Jeremy C. Stein, 2000. "Bad News Travels Slowly: Size, Analyst Coverage, and the Profitability of Momentum Strategies," Journal of Finance, American Finance Association, vol. 55(1), pages 265-295, February.
    2. Shi, Huai-Long & Zhou, Wei-Xing, 2022. "Factor volatility spillover and its implications on factor premia," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    3. David A. Volkman, 1999. "Market Volatility And Perverse Timing Performance Of Mutual Fund Managers," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 22(4), pages 449-470, December.
    4. Pastor, Lubos & Stambaugh, Robert F., 2003. "Liquidity Risk and Expected Stock Returns," Journal of Political Economy, University of Chicago Press, vol. 111(3), pages 642-685, June.
    5. Klaus Grobys & James W. Kolari & Jere Rutanen, 2022. "Factor momentum, option-implied volatility scaling, and investor sentiment," Journal of Asset Management, Palgrave Macmillan, vol. 23(2), pages 138-155, March.
    6. Agarwal, Vikas & Gay, Gerald D. & Ling, Leng, 2011. "Window dressing in mutual funds," CFR Working Papers 11-07, University of Cologne, Centre for Financial Research (CFR).
    7. Dimitrios D. Thomakos & Michail S. Koubouros, 2011. "The Role of Realised Volatility in the Athens Stock Exchange," Multinational Finance Journal, Multinational Finance Journal, vol. 15(1-2), pages 87-124, March - J.
    8. John H. Cochrane, 1999. "New facts in finance," Economic Perspectives, Federal Reserve Bank of Chicago, vol. 23(Q III), pages 36-58.
    9. Turan G. Bali & Robert F. Engle & Yi Tang, 2017. "Dynamic Conditional Beta Is Alive and Well in the Cross Section of Daily Stock Returns," Management Science, INFORMS, vol. 63(11), pages 3760-3779, November.
    10. David Peón & Anxo Calvo, 2012. "Using Behavioral Economics to Analyze Credit Policies in the Banking Industry," European Research Studies Journal, European Research Studies Journal, vol. 0(3), pages 145-160.
    11. Cakici, Nusret & Zaremba, Adam, 2022. "Salience theory and the cross-section of stock returns: International and further evidence," Journal of Financial Economics, Elsevier, vol. 146(2), pages 689-725.
    12. Hou, Yang & Meng, Jiayin, 2018. "The momentum effect in the Chinese market and its relationship with the simultaneous and the lagged investor sentiment," MPRA Paper 94838, University Library of Munich, Germany.
    13. Horowitz, Joel L. & Loughran, Tim & Savin, N. E., 2000. "The disappearing size effect," Research in Economics, Elsevier, vol. 54(1), pages 83-100, March.
    14. Clemens Sialm, 2009. "Tax Changes and Asset Pricing," American Economic Review, American Economic Association, vol. 99(4), pages 1356-1383, September.
    15. Brown, Stephen & Hillegeist, Stephen A. & Lo, Kin, 2009. "The effect of earnings surprises on information asymmetry," Journal of Accounting and Economics, Elsevier, vol. 47(3), pages 208-225, June.
    16. Luo, Bing, 2019. "Effects of auditor-provided tax services on book-tax differences and on investors' mispricing of book-tax differences," Advances in accounting, Elsevier, vol. 47(C).
    17. Drakos, Anastassios A., 2016. "Does the relationship between small and large portfolios’ returns confirm the lead–lag effect? Evidence from the Athens Stock Exchange," Research in International Business and Finance, Elsevier, vol. 36(C), pages 546-561.
    18. Francesco Busato & Cuono Massimo Coletta & Maria Manganiello, 2019. "Estimating the Cost of Equity Capital: Forecasting Accuracy for U.S. REIT Sector," International Real Estate Review, Asian Real Estate Society, vol. 22(3), pages 401-432.
    19. Ciciretti, Rocco & Dalò, Ambrogio & Dam, Lammertjan, 2023. "The contributions of betas versus characteristics to the ESG premium," Journal of Empirical Finance, Elsevier, vol. 71(C), pages 104-124.
    20. Chen, Zhuo & Lu, Andrea, 2017. "Slow diffusion of information and price momentum in stocks: Evidence from options markets," Journal of Banking & Finance, Elsevier, vol. 75(C), pages 98-108.

    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:operea:v:20:y:2020:i:2:d:10.1007_s12351-017-0361-2. 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.