IDEAS home Printed from https://ideas.repec.org/a/kap/annfin/v7y2011i2p137-169.html
   My bibliography  Save this article

Mutual fund performance: false discoveries, bias, and power

Author

Listed:
  • Nik Tuzov
  • Frederi Viens

Abstract

No abstract is available for this item.

Suggested Citation

  • Nik Tuzov & Frederi Viens, 2011. "Mutual fund performance: false discoveries, bias, and power," Annals of Finance, Springer, vol. 7(2), pages 137-169, May.
    • Handle: RePEc:kap:annfin:v:7:y:2011:i:2:p:137-169
    DOI: 10.1007/s10436-010-0151-9
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10436-010-0151-9
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10436-010-0151-9?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. Yoav Benjamini & Abba M. Krieger & Daniel Yekutieli, 2006. "Adaptive linear step-up procedures that control the false discovery rate," Biometrika, Biometrika Trust, vol. 93(3), pages 491-507, September.
    2. Joseph P. Romano & Michael Wolf, 2005. "Stepwise Multiple Testing as Formalized Data Snooping," Econometrica, Econometric Society, vol. 73(4), pages 1237-1282, July.
    3. S. P. Kothari & Jerold B. Warner, 2001. "Evaluating Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 56(5), pages 1985-2010, October.
    4. Laurent Barras & Olivier Scaillet & Russ Wermers, 2010. "False Discoveries in Mutual Fund Performance: Measuring Luck in Estimated Alphas," Journal of Finance, American Finance Association, vol. 65(1), pages 179-216, February.
    5. Bradford Cornell & Jakša Cvitanić & Levon Goukasian, 2010. "Beliefs regarding fundamental value and optimal investing," Annals of Finance, Springer, vol. 6(1), pages 83-105, January.
    6. Harry Mamaysky & Matthew Spiegel & Hong Zhang, 2007. "Improved Forecasting of Mutual Fund Alphas and Betas," Review of Finance, European Finance Association, vol. 11(3), pages 359-400.
    7. Daniel, Kent, et al, 1997. "Measuring Mutual Fund Performance with Characteristic-Based Benchmarks," Journal of Finance, American Finance Association, vol. 52(3), pages 1035-1058, July.
    8. Romano, Joseph P. & Shaikh, Azeem M. & Wolf, Michael, 2008. "Formalized Data Snooping Based On Generalized Error Rates," Econometric Theory, Cambridge University Press, vol. 24(2), pages 404-447, April.
    9. Robert Kosowski & Allan Timmermann & Russ Wermers & Hal White, 2006. "Can Mutual Fund “Stars” Really Pick Stocks? New Evidence from a Bootstrap Analysis," Journal of Finance, American Finance Association, vol. 61(6), pages 2551-2595, December.
    10. Efron B. & Tibshirani R. & Storey J.D. & Tusher V., 2001. "Empirical Bayes Analysis of a Microarray Experiment," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1151-1160, December.
    11. Jones, Christopher S. & Shanken, Jay, 2005. "Mutual fund performance with learning across funds," Journal of Financial Economics, Elsevier, vol. 78(3), pages 507-552, December.
    12. Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
    13. John D. Storey, 2002. "A direct approach to false discovery rates," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(3), pages 479-498, August.
    14. Efron, Bradley, 2007. "Correlation and Large-Scale Simultaneous Significance Testing," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 93-103, March.
    15. Chen, Hsiu-Lang & Jegadeesh, Narasimhan & Wermers, Russ, 2000. "The Value of Active Mutual Fund Management: An Examination of the Stockholdings and Trades of Fund Managers," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 35(3), pages 343-368, September.
    16. Manuel Ammann & Michael Verhofen, 2009. "The impact of prior performance on the risk-taking of mutual fund managers," Annals of Finance, Springer, vol. 5(1), pages 69-90, January.
    17. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    18. John D. Storey & Jonathan E. Taylor & David Siegmund, 2004. "Strong control, conservative point estimation and simultaneous conservative consistency of false discovery rates: a unified approach," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 66(1), pages 187-205, February.
    19. repec:ebl:ecbull:v:7:y:2008:i:10:p:1-9 is not listed on IDEAS
    20. Jorge Sainz & Pilar Grau & Luis Miguel Doncel & Javier Otamendi, 2008. "An evaluation on the true statistical relevance of Jensen's alpha trough simulation: An application for Germany," Economics Bulletin, AccessEcon, vol. 7(10), pages 1-9.
    21. Fan, Jianqing & Fan, Yingying & Lv, Jinchi, 2008. "High dimensional covariance matrix estimation using a factor model," Journal of Econometrics, Elsevier, vol. 147(1), pages 186-197, November.
    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. Danny Yeung, 2012. "The Impact of Institutional Ownership: A Study of the Australian Equity Market," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 11, July-Dece.
    2. Thomas A. Severini, 2016. "A nonparametric approach to measuring the sensitivity of an asset’s return to the market," Annals of Finance, Springer, vol. 12(2), pages 179-199, May.

    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. Laurent Barras & Olivier Scaillet & Russ Wermers, 2010. "False Discoveries in Mutual Fund Performance: Measuring Luck in Estimated Alphas," Journal of Finance, American Finance Association, vol. 65(1), pages 179-216, February.
    2. Cuthbertson, Keith & Nitzsche, Dirk & O'Sullivan, Niall, 2008. "UK mutual fund performance: Skill or luck?," Journal of Empirical Finance, Elsevier, vol. 15(4), pages 613-634, September.
    3. Bajgrowicz, Pierre & Scaillet, Olivier, 2012. "Technical trading revisited: False discoveries, persistence tests, and transaction costs," Journal of Financial Economics, Elsevier, vol. 106(3), pages 473-491.
    4. Grønborg, Niels S. & Lunde, Asger & Timmermann, Allan & Wermers, Russ, 2021. "Picking funds with confidence," Journal of Financial Economics, Elsevier, vol. 139(1), pages 1-28.
    5. Stephen A. Gorman & Frank J. Fabozzi, 2021. "The ABC’s of the alternative risk premium: academic roots," Journal of Asset Management, Palgrave Macmillan, vol. 22(6), pages 405-436, October.
    6. Psaradellis, Ioannis & Laws, Jason & Pantelous, Athanasios A. & Sermpinis, Georgios, 2023. "Technical analysis, spread trading, and data snooping control," International Journal of Forecasting, Elsevier, vol. 39(1), pages 178-191.
    7. Huang, Rong & Pilbeam, Keith & Pouliot, William, 2021. "Do actively managed US mutual funds produce positive alpha?," Journal of Economic Behavior & Organization, Elsevier, vol. 182(C), pages 472-492.
    8. Georgios Sermpinis & Arman Hassanniakalager & Charalampos Stasinakis & Ioannis Psaradellis, 2018. "Technical Analysis and Discrete False Discovery Rate: Evidence from MSCI Indices," Papers 1811.06766, arXiv.org, revised Jun 2019.
    9. Russ Wermers & Tong Yao & Jane Zhao, 2012. "Forecasting Stock Returns Through an Efficient Aggregation of Mutual Fund Holdings," The Review of Financial Studies, Society for Financial Studies, vol. 25(12), pages 3490-3529.
    10. Andrew Y. Chen, 2022. "Do t-Statistic Hurdles Need to be Raised?," Papers 2204.10275, arXiv.org, revised Apr 2024.
    11. Campbell R. Harvey & Yan Liu, 2020. "False (and Missed) Discoveries in Financial Economics," Papers 2006.04269, arXiv.org.
    12. Mason, Andrew & Agyei-Ampomah, Sam & Skinner, Frank, 2016. "Realism, skill, and incentives: Current and future trends in investment management and investment performance," International Review of Financial Analysis, Elsevier, vol. 43(C), pages 31-40.
    13. Fisher, Mark & Jensen, Mark J., 2022. "Bayesian nonparametric learning of how skill is distributed across the mutual fund industry," Journal of Econometrics, Elsevier, vol. 230(1), pages 131-153.
    14. Sermpinis, Georgios & Hassanniakalager, Arman & Stasinakis, Charalampos & Psaradellis, Ioannis, 2021. "Technical analysis profitability and Persistence: A discrete false discovery approach on MSCI indices," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 73(C).
    15. Hunter, David & Kandel, Eugene & Kandel, Shmuel & Wermers, Russ, 2014. "Mutual fund performance evaluation with active peer benchmarks," Journal of Financial Economics, Elsevier, vol. 112(1), pages 1-29.
    16. Chen, Li-Wen & Adams, Andrew & Taffler, Richard, 2013. "What style-timing skills do mutual fund “stars” possess?," Journal of Empirical Finance, Elsevier, vol. 21(C), pages 156-173.
    17. Francesco Lisi, 2011. "Dicing with the market: randomized procedures for evaluation of mutual funds," Quantitative Finance, Taylor & Francis Journals, vol. 11(2), pages 163-172.
    18. Ekholm, Anders G., 2012. "Portfolio returns and manager activity: How to decompose tracking error into security selection and market timing," Journal of Empirical Finance, Elsevier, vol. 19(3), pages 349-358.
    19. Harvey, Campbell R. & Liu, Yan, 2021. "Lucky factors," Journal of Financial Economics, Elsevier, vol. 141(2), pages 413-435.
    20. Miguel, António F. & Chen, Yihao, 2021. "Do machines beat humans? Evidence from mutual fund performance persistence," International Review of Financial Analysis, Elsevier, vol. 78(C).

    More about this item

    Keywords

    Mutual fund; Performance evaluation; False discovery; Multiple inference; Statistical power; C10; G10; G20;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G20 - Financial Economics - - Financial Institutions and Services - - - General

    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:annfin:v:7:y:2011:i:2:p:137-169. 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.