IDEAS home Printed from https://ideas.repec.org/p/arz/wpaper/eres2014_213.html
   My bibliography  Save this paper

Cross-sector fund performance comparison: the role of real estate mutual funds

Author

Listed:
  • Yuan Zhao

Abstract

We firstly examine the performance of active sector funds as a whole as equal- and value-weighted portfolios, against a stock market benchmark (Carhart four-factor model), an associated sector market benchmark, and the combined five-factor model benchmarks. We consider the gross and net returns to show the impact of expenses on performance. We also employ the residual bootstrap approach for portfolios to separate genuine skills from luck. We also look into individual sector fund managers, to examine the proportion of truly skilled sector fund managers after false discoveries have been controlled using false discovery rate (FDR) approach. Among all 13 sectors, most sector fund managers on average cannot add enough to cover expenses irrespective of benchmarks. We find mediocre performance on real estate mutual funds (REMFs), comparing with funds of other sectors. Weak evidence of outperformance relative to sector index is found in sectors of gold, and consumer services, even after deduction of expenses. Healthcare and technology sectors, as a whole, can marginally beat the stock market. When the combined sector and stock market benchmark is employed, funds of health care and technology oriented sectors overall can still outperform after costs. Finally, at each sector fund level, we implement joint test to control false discoveries from false positive-alpha funds, and find limited proportion of skilled sector fund managers, after costs.

Suggested Citation

  • Yuan Zhao, 2014. "Cross-sector fund performance comparison: the role of real estate mutual funds," ERES eres2014_213, European Real Estate Society (ERES).
  • Handle: RePEc:arz:wpaper:eres2014_213
    as

    Download full text from publisher

    File URL: https://eres.architexturez.net/doc/oai-eres-id-eres2014-213
    Download Restriction: no

    File URL: https://eres.architexturez.net/system/files/pdf/eres2014_213.content.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    3. Richard B. Evans, 2010. "Mutual Fund Incubation," Journal of Finance, American Finance Association, vol. 65(4), pages 1581-1611, August.
    4. 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.
    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. Jordan, Bradford D. & Riley, Timothy B., 2015. "Volatility and mutual fund manager skill," Journal of Financial Economics, Elsevier, vol. 118(2), pages 289-298.
    2. Wayne Ferson & Junbo L Wang, 2021. "A Panel Regression Approach to Holdings-Based Fund Performance Measures [Multiperiod performance persistence analysis of hedge funds]," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 11(4), pages 695-734.
    3. Christiansen, Charlotte & Grønborg, Niels S. & Nielsen, Ole L., 2020. "Mutual fund selection for realistically short samples," Journal of Empirical Finance, Elsevier, vol. 55(C), pages 218-240.
    4. 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.
    5. 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.
    6. Cuthbertson, Keith & Nitzsche, Dirk & O'Sullivan, Niall, 2016. "A review of behavioural and management effects in mutual fund performance," International Review of Financial Analysis, Elsevier, vol. 44(C), pages 162-176.
    7. DeMiguel, Victor & Gil-Bazo, Javier & Nogales, Francisco J. & Santos, André A.P., 2023. "Machine learning and fund characteristics help to select mutual funds with positive alpha," Journal of Financial Economics, Elsevier, vol. 150(3).
    8. 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.
    9. Cai, Biqing & Cheng, Tingting & Yan, Cheng, 2018. "Time-varying skills (versus luck) in U.S. active mutual funds and hedge funds," Journal of Empirical Finance, Elsevier, vol. 49(C), pages 81-106.
    10. 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.
    11. Yan, Cheng & Cheng, Tingting, 2019. "In search of the optimal number of fund subgroups," Journal of Empirical Finance, Elsevier, vol. 50(C), pages 78-92.
    12. Bredin, Don & Cuthbertson, Keith & Nitzsche, Dirk & Thomas, Dylan C., 2014. "Performance and performance persistence of UK closed-end equity funds," International Review of Financial Analysis, Elsevier, vol. 34(C), pages 189-199.
    13. Benoît Dewaele & Hugues Pirotte & N. Tuchschmid & E. Wallerstein, 2011. "Assessing the Performance of Funds of Hedge Funds," Working Papers CEB 11-041, ULB -- Universite Libre de Bruxelles.
    14. Ardia, David & Bluteau, Keven & Tran, Thien Duy, 2022. "How easy is it for investment managers to deploy their talent in green and brown stocks?," Finance Research Letters, Elsevier, vol. 48(C).
    15. Livingston, Miles & Yao, Ping & Zhou, Lei, 2019. "The volatility of mutual fund performance," Journal of Economics and Business, Elsevier, vol. 104(C), pages 1-1.
    16. Pástor, Ľuboš & Stambaugh, Robert F. & Taylor, Lucian A., 2015. "Scale and skill in active management," Journal of Financial Economics, Elsevier, vol. 116(1), pages 23-45.
    17. Nik Tuzov & Frederi Viens, 2011. "Mutual fund performance: false discoveries, bias, and power," Annals of Finance, Springer, vol. 7(2), pages 137-169, May.
    18. David Ardia & Kris Boudt, 2013. "The Peer Performance of Hedge Funds," Cahiers de recherche 1329, CIRPEE.
    19. Victor DeMiguel & Javier Gil-Bazo & Francisco J. Nogales & André A. P. Santos, 2021. "Can Machine Learning Help to Select Portfolios of Mutual Funds?," Working Papers 1245, Barcelona School of Economics.
    20. Ardia, David & Boudt, Kris, 2018. "The peer performance ratios of hedge funds," Journal of Banking & Finance, Elsevier, vol. 87(C), pages 351-368.

    More about this item

    JEL classification:

    • R3 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:arz:wpaper:eres2014_213. 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: Architexturez Imprints (email available below). General contact details of provider: https://edirc.repec.org/data/eressea.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.