IDEAS home Printed from https://ideas.repec.org/a/kap/theord/v79y2015i1p107-132.html
   My bibliography  Save this article

A theoretical foundation of portfolio resampling

Author

Listed:
  • Gabriel Frahm

Abstract

A portfolio-resampling procedure invented by Richard and Robert Michaud is a subject of highly controversial discussion and big scientific dispute. It has been evaluated in many empirical studies and Monte Carlo experiments. Apart from the contradictory findings, the Michaud approach still lacks a theoretical foundation. I prove that portfolio resampling has a strong foundation in the classic theory of rational behavior. Every noise trader could do better by applying the Michaud procedure. By contrast, a signal trader who has enough prediction power and risk-management skills should refrain from portfolio resampling. The key note is that in most simulation studies, investors are considered as noise traders. This explains why portfolio resampling performs well in simulation studies, but could be mediocre in real life. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • Gabriel Frahm, 2015. "A theoretical foundation of portfolio resampling," Theory and Decision, Springer, vol. 79(1), pages 107-132, July.
    • Handle: RePEc:kap:theord:v:79:y:2015:i:1:p:107-132
    DOI: 10.1007/s11238-014-9453-0
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11238-014-9453-0
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11238-014-9453-0?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. Gabriel Frahm & Tobias Wickern & Christof Wiechers, 2012. "Multiple tests for the performance of different investment strategies," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 96(3), pages 343-383, July.
    2. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    3. Kan, Raymond & Zhou, Guofu, 2007. "Optimal Portfolio Choice with Parameter Uncertainty," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 42(3), pages 621-656, September.
    4. Victor DeMiguel & Lorenzo Garlappi & Francisco J. Nogales & Raman Uppal, 2009. "A Generalized Approach to Portfolio Optimization: Improving Performance by Constraining Portfolio Norms," Management Science, INFORMS, vol. 55(5), pages 798-812, May.
    5. Bernd Scherer, 2006. "A note on the out-of-sample performance of resampled efficiency," Journal of Asset Management, Palgrave Macmillan, vol. 7(3), pages 170-178, September.
    6. Frahm, Gabriel & Memmel, Christoph, 2010. "Dominating estimators for minimum-variance portfolios," Journal of Econometrics, Elsevier, vol. 159(2), pages 289-302, December.
    7. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Working Papers 111, Princeton University, Department of Economics, Center for Economic Policy Studies..
    8. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Working Papers 111, Princeton University, Department of Economics, Center for Economic Policy Studies..
    9. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    10. Bernd Scherer, 2004. "Resampled efficiency and portfolio choice," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 18(4), pages 382-398, December.
    11. Timmermann, Allan & Granger, Clive W. J., 2004. "Efficient market hypothesis and forecasting," International Journal of Forecasting, Elsevier, vol. 20(1), pages 15-27.
    12. repec:pri:cepsud:91malkiel is not listed on IDEAS
    13. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    14. LeRoy, Stephen F, 1973. "Risk Aversion and the Martingale Property of Stock Prices," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 14(2), pages 436-446, June.
    15. repec:hal:journl:peer-00741629 is not listed on IDEAS
    16. Richard Bradley, 2007. "A Unified Bayesian Decision Theory," Theory and Decision, Springer, vol. 63(3), pages 233-263, November.
    17. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Journal of Economic Perspectives, American Economic Association, vol. 17(1), pages 59-82, Winter.
    18. Lucas, Robert E, Jr, 1978. "Asset Prices in an Exchange Economy," Econometrica, Econometric Society, vol. 46(6), pages 1429-1445, November.
    19. Pulley, Lawrence B., 1981. "A General Mean-Variance Approximation to Expected Utility for Short Holding Periods," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 16(3), pages 361-373, September.
    20. MOSSIN, Jan, 1968. "Optimal multiperiod portfolio policies," LIDAM Reprints CORE 19, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    21. Kerry Back, 2010. "Martingale Pricing," Annual Review of Financial Economics, Annual Reviews, vol. 2(1), pages 235-250, December.
    22. Kroll, Yoram & Levy, Haim & Markowitz, Harry M, 1984. "Mean-Variance versus Direct Utility Maximization," Journal of Finance, American Finance Association, vol. 39(1), pages 47-61, March.
    23. Bernd Scherer, 2007. "Can robust portfolio optimisation help to build better portfolios?," Journal of Asset Management, Palgrave Macmillan, vol. 7(6), pages 374-387, March.
    24. Ramsey, Frank P., 1926. "Truth and Probability," Histoy of Economic Thought Chapters, in: Braithwaite, R. B. (ed.),The Foundations of Mathematics and other Logical Essays, chapter 7, pages 156-198, McMaster University Archive for the History of Economic Thought.
    25. Bade, Alexander & Frahm, Gabriel & Jaekel, Uwe, 2008. "A general approach to Bayesian portfolio optimization," Discussion Papers in Econometrics and Statistics 1/08, University of Cologne, Institute of Econometrics and Statistics.
    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. Gabriel Frahm, 2016. "Pricing And Valuation Under The Real-World Measure," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 19(01), pages 1-39, February.
    2. Gabriel Frahm, 2020. "Statistical properties of estimators for the log-optimal portfolio," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 92(1), pages 1-32, August.
    3. Mynbayeva, Elmira & Lamb, John D. & Zhao, Yuan, 2022. "Why estimation alone causes Markowitz portfolio selection to fail and what we might do about it," European Journal of Operational Research, Elsevier, vol. 301(2), pages 694-707.

    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. Ashok Chanabasangouda Patil & Shailesh Rastogi, 2019. "Time-Varying Price–Volume Relationship and Adaptive Market Efficiency: A Survey of the Empirical Literature," JRFM, MDPI, vol. 12(2), pages 1-18, June.
    2. Murizah Osman Salleh & Aziz Jaafar & M. Shahid Ebrahim, 2011. "The Inhibition of Usury (Riba An-Nasi'ah) and the Economic Underdevelopment of the Muslim World," Working Papers 11002, Bangor Business School, Prifysgol Bangor University (Cymru / Wales).
    3. Taufiq Choudhry & Ranadeva Jayasekera, 2015. "Level of efficiency in the UK equity market: empirical study of the effects of the global financial crisis," Review of Quantitative Finance and Accounting, Springer, vol. 44(2), pages 213-242, February.
    4. Kin-Boon Tang & Shao-Jye Wong & Shih-Kuei Lin & Szu-Lang Liao, 2020. "Excess volatility and market efficiency in government bond markets: the ASEAN-5 context," Journal of Asset Management, Palgrave Macmillan, vol. 21(2), pages 154-165, March.
    5. Kofi A. Amoateng, 2019. "Did Tom Brady Save the US stock market? Market Anomaly or Market Efficiency?," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 11(5), pages 128-128, May.
    6. Stefanescu, Razvan & Dumitriu, Ramona, 2016. "Particularitǎţi ale evoluţiei variabilelor financiare [Some particularities of the financial variables evolution]," MPRA Paper 73481, University Library of Munich, Germany, revised 02 Sep 2016.
    7. Kwan, Yum K. & Leung, Charles Ka Yui & Dong, Jinyue, 2015. "Comparing consumption-based asset pricing models: The case of an Asian city," Journal of Housing Economics, Elsevier, vol. 28(C), pages 18-41.
    8. Felicia Ramona Birau, 2011. "An Analysis Of Weak-Form Efficiency On The Bucharest Stock Exchange," Annals of University of Craiova - Economic Sciences Series, University of Craiova, Faculty of Economics and Business Administration, vol. 3(39), pages 194-205.
    9. Roland Rothenstein, 2018. "Quantification of market efficiency based on informational-entropy," Papers 1812.02371, arXiv.org.
    10. Kristoufek, Ladislav, 2018. "Fractality in market risk structure: Dow Jones Industrial components case," Chaos, Solitons & Fractals, Elsevier, vol. 110(C), pages 69-75.
    11. Park, Cheol-Ho & Irwin, Scott H., 2004. "The Profitability Of Technical Trading Rules In Us Futures Markets: A Data Snooping Free Test," 2004 Conference, April 19-20, 2004, St. Louis, Missouri 19011, NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    12. Bennett, Donyetta & Mekelburg, Erik & Williams, T.H., 2023. "BeFi meets DeFi: A behavioral finance approach to decentralized finance asset pricing," Research in International Business and Finance, Elsevier, vol. 65(C).
    13. Bernard Njindan Iyke, 2019. "A Test Of The Efficiency Of The Foreign Exchange Market In Indonesia," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 0(12th BMEB), pages 1-26, January.
    14. Anastasios KONSTANTINIDIS & Androniki KATARACHIA & George BOROVAS & Maria Eleni VOUTSA, 2012. "From Efficient Market Hypothesis To Behavioural Finance: Can Behavioural Finance Be The New Dominant Model For Investing?," Scientific Bulletin - Economic Sciences, University of Pitesti, vol. 11(2), pages 16-26.
    15. Daniel Traian Pele & Miruna Mazurencu-Marinescu & Peter Nijkamp, 2013. "Herding Behaviour, Bubbles and Log Periodic Power Laws in Illiquid Stock Markets. A Case Study on the Bucharest Stock Exchange," Tinbergen Institute Discussion Papers 13-109/VIII, Tinbergen Institute.
    16. Romain Bocher, 2023. "Causal Entropic Forces, Narratives and Self-organisation of Capital Markets," Journal of Interdisciplinary Economics, , vol. 35(2), pages 172-190, July.
    17. Charron Jacques-Olivier, 2017. "Inefficient Debate. The EMH, the “Remarkable Error” and a Question of Point of View," Accounting, Economics, and Law: A Convivium, De Gruyter, vol. 7(3), pages 1-24, December.
    18. Thomas Delcey & Francesco Sergi, 2019. "The Efficient Market Hypothesis and Rational Expectations. How Did They Meet and Live (Happily?) Ever After," Working Papers hal-02187362, HAL.
    19. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.
    20. Felicia Ramona Birău, 2012. "The Impact Of Behavioral Finance On Stock Markets," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 3, pages 45-50, September.

    More about this item

    Keywords

    Asset allocation; Mean–variance analysis; Noise trader; Out-of-sample performance; Portfolio resampling; Resampled efficiency; Signal trader; Primary G11; Secondary D81;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

    Statistics

    Access and download statistics

    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:theord:v:79:y:2015:i:1:p:107-132. 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.