IDEAS home Printed from https://ideas.repec.org/a/spr/eurase/v10y2020i4d10.1007_s40822-020-00141-6.html
   My bibliography  Save this article

Is size an input in the mutual fund performance evaluation with DEA?

Author

Listed:
  • Sevgi Eda Tuzcu

    (Ankara Üniversitesi, Siyasal Bilgiler Fakültesi, Cebeci Kampüsü)

  • Emrah Ertugay

    (Ankara Üniversitesi, Siyasal Bilgiler Fakültesi, Cebeci Kampüsü)

Abstract

It has been a common practice to evaluate the performance of mutual funds with data envelopment analysis (DEA). However, DEA itself is a “black box”, since there are no pre-determined inputs or outputs. This paper aims to add clarification to the “black box” nature of DEA by investigating whether fund size has to be included among DEA inputs in the Turkish mutual fund performance evaluation. Fund managers receive a proportion of fund size as compensation. Therefore, besides the traditional risk and expense inputs, economies or diseconomies of scale may also be effective in the fund’s performance. For these reasons, the evaluation of fund performance by using DEA may require fund size as an input. Yet, few international study adds size as an input to the DEA. The evidence is even scarcer for developing country fund markets. To the extent of our knowledge, size has not been utilized in the Turkish mutual fund performance evaluations. This paper aims to contribute to the literature by examining the linear and nonlinear relations between DEA scores and fund size for the Turkish mutual fund industry. For this aim, linear correlation, and Kendall and Spearman rank correlation coefficients are employed as well as a regression specification. The correlations and the regression results reveal a linear relationship between the efficiency scores and fund size. In general, this study presents stronger evidence for the fund size and fund efficiency relation than Basso and Funari (Eur J Finance 23:457–473, 2017) for the Turkish mutual fund market.

Suggested Citation

  • Sevgi Eda Tuzcu & Emrah Ertugay, 2020. "Is size an input in the mutual fund performance evaluation with DEA?," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 10(4), pages 635-659, December.
    • Handle: RePEc:spr:eurase:v:10:y:2020:i:4:d:10.1007_s40822-020-00141-6
    DOI: 10.1007/s40822-020-00141-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s40822-020-00141-6
    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/s40822-020-00141-6?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. Babalos, Vassilios & Caporale, Guglielmo Maria & Philippas, Nikolaos, 2012. "Efficiency evaluation of Greek equity funds," Research in International Business and Finance, Elsevier, vol. 26(2), pages 317-333.
    2. Antonella Basso & Stefania Funari, 2017. "The role of fund size in the performance of mutual funds assessed with DEA models," The European Journal of Finance, Taylor & Francis Journals, vol. 23(6), pages 457-473, May.
    3. Mohammad Reza TAVAKOLI BAGHDADABAD & Afsaneh NOORI HOUSHYAR, 2014. "Productivity and Efficiency Evaluation of US Mutual Funds," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 64(2), pages 120-143, March.
    4. Jin-Li Hu & Hsueh-E. Yu & Yi-Ting Wang, 2012. "Manager Attributes and Fund Performance: Evidence from Taiwan," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 2(4), pages 1-6.
    5. Panayotis Alexakis & Ioannis Tsolas, 2011. "Appraisal of Mutual Equity Fund Performance Using Data Envelopment Analysis," Multinational Finance Journal, Multinational Finance Journal, vol. 15(3-4), pages 273-296, September.
    6. Galagedera, Don U.A. & Roshdi, Israfil & Fukuyama, Hirofumi & Zhu, Joe, 2018. "A new network DEA model for mutual fund performance appraisal: An application to U.S. equity mutual funds," Omega, Elsevier, vol. 77(C), pages 168-179.
    7. Premachandra, I.M. & Zhu, Joe & Watson, John & Galagedera, Don U.A., 2012. "Best-performing US mutual fund families from 1993 to 2008: Evidence from a novel two-stage DEA model for efficiency decomposition," Journal of Banking & Finance, Elsevier, vol. 36(12), pages 3302-3317.
    8. Md. Abul Kalam Azad & Susila Munisamy & Abdul Kadar Muhammad Masum & Paolo Saona & Peter Wanke, 2017. "Bank efficiency in Malaysia: a use of malmquist meta-frontier analysis," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 7(2), pages 287-311, August.
    9. Yoon K. Choi & B.P.S. Murthi, 2001. "Relative Performance Evaluation of Mutual Funds: A Non-Parametric Approach," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 28(7&8), pages 853-876.
    10. Ferreira, Miguel A. & Keswani, Aneel & Miguel, Antonio F. & Ramos, Sofia B., 2012. "The flow-performance relationship around the world," Journal of Banking & Finance, Elsevier, vol. 36(6), pages 1759-1780.
    11. Chevalier, Judith & Ellison, Glenn, 1997. "Risk Taking by Mutual Funds as a Response to Incentives," Journal of Political Economy, University of Chicago Press, vol. 105(6), pages 1167-1200, December.
    12. Erik R. Sirri & Peter Tufano, 1998. "Costly Search and Mutual Fund Flows," Journal of Finance, American Finance Association, vol. 53(5), pages 1589-1622, October.
    13. Alexander Kempf & Stefan Ruenzi, 2008. "Tournaments in Mutual-Fund Families," The Review of Financial Studies, Society for Financial Studies, vol. 21(2), pages 1013-1036, April.
    14. Daraio, Cinzia & Simar, Leopold, 2006. "A robust nonparametric approach to evaluate and explain the performance of mutual funds," European Journal of Operational Research, Elsevier, vol. 175(1), pages 516-542, November.
    15. Sánchez-González, Carlos & Sarto, José Luis & Vicente, Luis, 2017. "The efficiency of mutual fund companies: Evidence from an innovative network SBM approach," Omega, Elsevier, vol. 71(C), pages 114-128.
    16. Grinblatt, Mark & Titman, Sheridan D, 1989. "Mutual Fund Performance: An Analysis of Quarterly Portfolio Holdings," The Journal of Business, University of Chicago Press, vol. 62(3), pages 393-416, July.
    17. Thorsten Lehnert, 2019. "Big moves of mutual funds," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 9(1), pages 1-27, March.
    18. Murthi, B. P. S. & Choi, Yoon K. & Desai, Preyas, 1997. "Efficiency of mutual funds and portfolio performance measurement: A non-parametric approach," European Journal of Operational Research, Elsevier, vol. 98(2), pages 408-418, April.
    19. Manuel Ammann & Patrick Moerth, 2005. "Impact of fund size on hedge fund performance," Journal of Asset Management, Palgrave Macmillan, vol. 6(3), pages 219-238, October.
    20. repec:mfj:journl:v:16:y:2012:i:3-4:p:273-296 is not listed on IDEAS
    21. Yoon K. Choi & B.P.S. Murthi, 2001. "Relative Performance Evaluation of Mutual Funds: A Non‐Parametric Approach," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 28(7‐8), pages 853-876, September.
    22. Andreu, Laura & Serrano, Miguel & Vicente, Luis, 2019. "Efficiency of mutual fund managers: A slacks-based manager efficiency index," European Journal of Operational Research, Elsevier, vol. 273(3), pages 1180-1193.
    23. Alexis Derviz & JiÅí Podpiera, 2008. "Predicting Bank CAMELS and S&P Ratings: The Case of the Czech Republic," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 44(1), pages 117-130, January.
    24. Brown, Keith C & Harlow, W V & Starks, Laura T, 1996. "Of Tournaments and Temptations: An Analysis of Managerial Incentives in the Mutual Fund Industry," Journal of Finance, American Finance Association, vol. 51(1), pages 85-110, March.
    25. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2006. "Introduction to Data Envelopment Analysis and Its Uses," Springer Books, Springer, number 978-0-387-29122-2, December.
    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. Yangxue Ning & Yan Zhang & Guoqiang Wang, 2023. "An Improved DEA Prospect Cross-Efficiency Evaluation Method and Its Application in Fund Performance Analysis," Mathematics, MDPI, vol. 11(3), pages 1-15, January.
    2. Ioannis E. Tsolas, 2020. "Precious Metal Mutual Fund Performance Evaluation: A Series Two-Stage DEA Modeling Approach," JRFM, MDPI, vol. 13(5), pages 1-13, April.
    3. Davide Lanfranchi & Laura Grassi, 2021. "Translating technological innovation into efficiency: the case of US public P&C insurance companies," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 11(4), pages 565-585, December.

    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. Galagedera, Don U.A. & Fukuyama, Hirofumi & Watson, John & Tan, Eric K.M., 2020. "Do mutual fund managers earn their fees? New measures for performance appraisal," European Journal of Operational Research, Elsevier, vol. 287(2), pages 653-667.
    2. Antonella Basso & Stefania Funari, 2017. "The role of fund size in the performance of mutual funds assessed with DEA models," The European Journal of Finance, Taylor & Francis Journals, vol. 23(6), pages 457-473, May.
    3. Babalos, Vassilios & Mamatzakis, Emmanuel C. & Matousek, Roman, 2015. "The performance of US equity mutual funds," Journal of Banking & Finance, Elsevier, vol. 52(C), pages 217-229.
    4. Vassilios Babalos & Michael Doumpos & Nikolaos Philippas & Constantin Zopounidis, 2015. "Towards a Holistic Approach for Mutual Fund Performance Appraisal," Computational Economics, Springer;Society for Computational Economics, vol. 46(1), pages 35-53, June.
    5. Andreu, Laura & Serrano, Miguel & Vicente, Luis, 2019. "Efficiency of mutual fund managers: A slacks-based manager efficiency index," European Journal of Operational Research, Elsevier, vol. 273(3), pages 1180-1193.
    6. Ioannis E. Tsolas, 2020. "Precious Metal Mutual Fund Performance Evaluation: A Series Two-Stage DEA Modeling Approach," JRFM, MDPI, vol. 13(5), pages 1-13, April.
    7. Babalos, Vassilios & Caporale, Guglielmo Maria & Philippas, Nikolaos, 2012. "Efficiency evaluation of Greek equity funds," Research in International Business and Finance, Elsevier, vol. 26(2), pages 317-333.
    8. Hallahan, Terrence & Faff, Robert, 2009. "Tournament behavior in Australian superannuation funds: A non-parametric analysis," Global Finance Journal, Elsevier, vol. 19(3), pages 307-322.
    9. Mohammad Reza TAVAKOLI BAGHDADABAD & Afsaneh NOORI HOUSHYAR, 2014. "Productivity and Efficiency Evaluation of US Mutual Funds," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 64(2), pages 120-143, March.
    10. Mazur, Mieszko & Salganik-Shoshan, Galla & Zagonov, Maxim, 2017. "Comparing performance sensitivity of retail and institutional mutual funds’ investment flows," Finance Research Letters, Elsevier, vol. 22(C), pages 66-73.
    11. Amporn SOONGSWANG & Yosawee SANOHDONTREE, 2011. "Equity Mutual Fund: Performances, Persistence and Fund Rankings," Journal of Knowledge Management, Economics and Information Technology, ScientificPapers.org, vol. 1(6), pages 1-27, October.
    12. Solórzano-Taborga, Pablo & Alonso-Conde, Ana Belén & Rojo-Suárez, Javier, 2018. "Efficiency and Persistence of Spanish Absolute Return Funds || Eficiencia y persistencia de los fondos de retorno absolutos españoles," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 25(1), pages 186-214, Junio.
    13. Hendriock, Mario, 2020. "Implied cost of capital and mutual fund performance," CFR Working Papers 20-11, University of Cologne, Centre for Financial Research (CFR).
    14. Emmanuel Mamatzakis & Mike Tsionas, 2018. "A Bayesian dynamic model to test persistence in funds' performance," Working Paper series 18-23, Rimini Centre for Economic Analysis.
    15. Ha, Yeonjeong & Ko, Kwangsoo, 2017. "Why do fund managers increase risk?," Journal of Banking & Finance, Elsevier, vol. 78(C), pages 108-116.
    16. Galán, Jorge & Ramos, Sofía B. & Veiga, Helena, 2015. "An analysis of the dynamics of efficiency of mutual funds," DES - Working Papers. Statistics and Econometrics. WS ws1517, Universidad Carlos III de Madrid. Departamento de Estadística.
    17. Wen-Min Lu & Qian Long Kweh & Chung-Wei Wang, 2021. "Integration and application of rough sets and data envelopment analysis for assessments of the investment trusts industry," Annals of Operations Research, Springer, vol. 296(1), pages 163-194, January.
    18. Raphaëlle Bellando & Sébastien Ringuedé, 2007. "Compétition entre fonds et prise de risque excessive : une application empirique au cas des OPCVM actions de droit français," Post-Print halshs-00226341, HAL.
    19. Martin Eling, 2006. "Performance measurement of hedge funds using data envelopment analysis," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 20(4), pages 442-471, December.
    20. Gennaro Bernile & Vineet Bhagwat & Ambrus Kecskés & Phuong‐Anh Nguyen, 2021. "Are the risk attitudes of professional investors affected by personal catastrophic experiences?," Financial Management, Financial Management Association International, vol. 50(2), pages 455-486, June.

    More about this item

    Keywords

    Data envelopment analysis (DEA); DEA inputs and outputs selection; Mutual fund performance; Size;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models

    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:spr:eurase:v:10:y:2020:i:4:d:10.1007_s40822-020-00141-6. 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.