IDEAS home Printed from https://ideas.repec.org/a/sbe/breart/v31y2011i2a7173.html
   My bibliography  Save this article

Generalized Tests of Investment Fund Performance

Author

Listed:
  • Laurini, Márcio Poletti
  • Sanvicente, Antônio Zoratto
  • Monteiro, Rogério da Costa

Abstract

The paper discusses the use of statistical methods in the comparison ofinvestment fund peThe paper discusses the use of statistical methods in the comparison ofinvestment fund performance indicators. The analysis is based on the robuststatistics proposed by Ledoit and Wolf (2008), for the pairwise comparison offunds and two generalizations for sets of multiple investment funds. The multipleinvestment fund tests use the Wald and Distance Metric statistics, based onestimation by Generalized Method of Moments using HAC matrices. In orderto correct size limitations in the GMMestimation in the case of a large number ofmoment conditions, the test distributions are obtained through block-bootstrapprocedures. We applied the proposed procedures to daily return data for thelargest 97 actively managed equity funds in the Brazilian market, covering theperiod from July 2006 to July 2008. The results indicate that there are nosignificant differences in the performances of the 97 funds in the sample, bothin pairwise and joint comparisons, thus providing what is believed to be the firstBrazilian market evidence for the so-called herding hypothesis. rformance indicators. The analysis is based on the robust statistics proposed by Ledoit and Wolf (2008), for the pairwise comparison of funds and two generalizations for sets of multiple investment funds. The multiple investment fund tests use the Wald and Distance Metric statistics, based on estimation by Generalized Method of Moments using HAC matrices.In order to correct size limitations in the GMM estimation in the case of a large number of moment conditions, the test distributions are obtained through block-bootstrap procedures. We applied the proposed procedures to daily return data for the largest 97 actively managed equity funds in the Brazilian market, covering the period from July 2006 to July 2008. The results indicate that there are no significant differences in the performances of the 97 funds in the sample, both in pairwise and joint comparisons, thus providing what is believed to be the first Brazilian market evidence for the so-called herding hypothesis.

Suggested Citation

  • Laurini, Márcio Poletti & Sanvicente, Antônio Zoratto & Monteiro, Rogério da Costa, 2011. "Generalized Tests of Investment Fund Performance," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 31(2), December.
  • Handle: RePEc:sbe:breart:v:31:y:2011:i:2:a:7173
    as

    Download full text from publisher

    File URL: https://periodicos.fgv.br/bre/article/view/7173
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    2. Lakonishok, Josef & Shleifer, Andrei & Vishny, Robert W., 1992. "The impact of institutional trading on stock prices," Journal of Financial Economics, Elsevier, vol. 32(1), pages 23-43, August.
    3. Burnside, Craig & Eichenbaum, Martin S, 1996. "Small-Sample Properties of GMM-Based Wald Tests," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 294-308, July.
    4. Berndt, Ernst R & Savin, N Eugene, 1977. "Conflict among Criteria for Testing Hypotheses in the Multivariate Linear Regression Model," Econometrica, Econometric Society, vol. 45(5), pages 1263-1277, July.
    5. 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.
    6. Newey, Whitney K & West, Kenneth D, 1987. "Hypothesis Testing with Efficient Method of Moments Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 28(3), pages 777-787, October.
    7. Anatolyev, Stanislav, 2012. "Inference in regression models with many regressors," Journal of Econometrics, Elsevier, vol. 170(2), pages 368-382.
    8. Joseph Romano & Azeem Shaikh & Michael Wolf, 2008. "Control of the false discovery rate under dependence using the bootstrap and subsampling," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 17(3), pages 417-442, November.
    9. Inoue, Atsushi & Shintani, Mototsugu, 2006. "Bootstrapping GMM estimators for time series," Journal of Econometrics, Elsevier, vol. 133(2), pages 531-555, August.
    10. 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.
    11. Ledoit, Oliver & Wolf, Michael, 2008. "Robust performance hypothesis testing with the Sharpe ratio," Journal of Empirical Finance, Elsevier, vol. 15(5), pages 850-859, December.
    12. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    13. Joseph Romano & Azeem Shaikh & Michael Wolf, 2008. "Rejoinder on: Control of the false discovery rate under dependence using the bootstrap and subsampling," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 17(3), pages 461-471, November.
    14. LeRoy, Stephen F, 1989. "Efficient Capital Markets and Martingales," Journal of Economic Literature, American Economic Association, vol. 27(4), pages 1583-1621, December.
    15. Jobson, J D & Korkie, Bob M, 1981. "Performance Hypothesis Testing with the Sharpe and Treynor Measures," Journal of Finance, American Finance Association, vol. 36(4), pages 889-908, September.
    16. Eugene F. Fama & Kenneth R. French, 2010. "Luck versus Skill in the Cross‐Section of Mutual Fund Returns," Journal of Finance, American Finance Association, vol. 65(5), pages 1915-1947, October.
    17. Andrews, Donald W K, 1991. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Econometrica, Econometric Society, vol. 59(3), pages 817-858, May.
    18. Grinblatt, Mark & Titman, Sheridan & Wermers, Russ, 1995. "Momentum Investment Strategies, Portfolio Performance, and Herding: A Study of Mutual Fund Behavior," American Economic Review, American Economic Association, vol. 85(5), pages 1088-1105, December.
    19. repec:cdl:ucsbec:13-89 is not listed on IDEAS
    20. Gregory, Allan W & Veall, Michael R, 1985. "Formulating Wald Tests of Nonlinear Restrictions," Econometrica, Econometric Society, vol. 53(6), pages 1465-1468, November.
    21. Hall, Peter & Horowitz, Joel L, 1996. "Bootstrap Critical Values for Tests Based on Generalized-Method-of-Moments Estimators," Econometrica, Econometric Society, vol. 64(4), pages 891-916, July.
    22. Hansen, Lars Peter & Heaton, John & Yaron, Amir, 1996. "Finite-Sample Properties of Some Alternative GMM Estimators," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 262-280, July.
    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. La Vecchia, Davide & Moor, Alban & Scaillet, Olivier, 2023. "A higher-order correct fast moving-average bootstrap for dependent data," Journal of Econometrics, Elsevier, vol. 235(1), pages 65-81.
    2. 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.
    3. Frank Kleibergen, 2004. "Expansions of GMM statistics that indicate their properties under weak and/or many instruments and the bootstrap," Econometric Society 2004 North American Summer Meetings 408, Econometric Society.
    4. Paulo M. D. C. Parente & Richard J. Smith, 2021. "Quasi‐maximum likelihood and the kernel block bootstrap for nonlinear dynamic models," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(4), pages 377-405, July.
    5. Härdle, Wolfgang & Horowitz, Joel L. & Kreiss, Jens-Peter, 2001. "Bootstrap methods for time series," SFB 373 Discussion Papers 2001,59, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    6. Bravo, Francesco & Crudu, Federico, 2012. "Efficient bootstrap with weakly dependent processes," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3444-3458.
    7. Hall, Alastair R. & Inoue, Atsushi, 2003. "The large sample behaviour of the generalized method of moments estimator in misspecified models," Journal of Econometrics, Elsevier, vol. 114(2), pages 361-394, June.
    8. Alastair R. Hall, 2015. "Econometricians Have Their Moments: GMM at 32," The Economic Record, The Economic Society of Australia, vol. 91(S1), pages 1-24, June.
    9. Alastair R. Hall, 2013. "Generalized Method of Moments," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 14, pages 313-333, Edward Elgar Publishing.
    10. Ayadi, Mohamed A. & Kryzanowski, Lawrence, 2011. "Fixed-income fund performance: Role of luck and ability in tail membership," Journal of Empirical Finance, Elsevier, vol. 18(3), pages 379-392, June.
    11. Yuichi Kitamura, 2006. "Empirical Likelihood Methods in Econometrics: Theory and Practice," CIRJE F-Series CIRJE-F-430, CIRJE, Faculty of Economics, University of Tokyo.
    12. Smith, Richard J., 2005. "Automatic Positive Semidefinite Hac Covariance Matrix And Gmm Estimation," Econometric Theory, Cambridge University Press, vol. 21(1), pages 158-170, February.
    13. repec:wyi:journl:002162 is not listed on IDEAS
    14. Campbell R. Harvey & Yan Liu, 2020. "False (and Missed) Discoveries in Financial Economics," Papers 2006.04269, arXiv.org.
    15. Faff, Robert & Gray, Philip, 2006. "On the estimation and comparison of short-rate models using the generalised method of moments," Journal of Banking & Finance, Elsevier, vol. 30(11), pages 3131-3146, November.
    16. Javed Iqbal & Robert Brooks & Don Galagedera, 2010. "Multivariate tests of asset pricing: simulation evidence from an emerging market," Applied Financial Economics, Taylor & Francis Journals, vol. 20(5), pages 381-395.
    17. Qihui Chen & Yu Ren, 2013. "Improvement in finite-sample properties of GMM-based Wald tests," Computational Statistics, Springer, vol. 28(2), pages 735-749, April.
    18. Mardi Dungey & Vitali Alexeev & Jing Tian & Alastair R. Hall, 2015. "Econometricians Have Their Moments: GMM at 32," The Economic Record, The Economic Society of Australia, vol. 91, pages 1-24, June.
    19. Paulo M.D.C. Parente & Richard J. Smith, 2018. "Generalised Empirical Likelihood Kernel Block Bootstrapping," Working Papers REM 2018/55, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    20. Jiang, Hao & Verardo, Michela, 2013. "Does herding behavior reveal skill? An analysis of mutual fund performance," LSE Research Online Documents on Economics 119034, London School of Economics and Political Science, LSE Library.
    21. Bryan D. MacGregor & Rainer Schulz & Yuan Zhao, 2021. "Performance and Market Maturity in Mutual Funds: Is Real Estate Different?," The Journal of Real Estate Finance and Economics, Springer, vol. 63(3), pages 437-492, October.

    More about this item

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

    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:sbe:breart:v:31:y:2011:i:2:a:7173. 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: Núcleo de Computação da FGV EPGE (email available below). General contact details of provider: https://edirc.repec.org/data/sbeeeea.html .

    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.