Skip to main content

Mutual Fund Industry Performance: A Network Data Envelopment Analysis Approach

  • Chapter
  • First Online:
Data Envelopment Analysis

Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 238))

Abstract

The objective of this chapter is twofold. First, we present a comprehensive review of the DEA literature that has evaluated mutual fund performance. Second, we present a two-stage DEA model that decomposes the overall efficiency of a decision-making unit into two components and demonstrate its applicability by assessing the relative performance of 66 large mutual fund families in the US over the period 1993–2008. By decomposing the overall efficiency into operational management efficiency and portfolio management efficiency components, we reveal the best performers, the families that deteriorated in performance, and those that improved in their performance over the sample period. We also make frontier projections for poorly performing mutual fund families and highlight how the portfolio managers have managed their funds relative to the others during financial crisis periods.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 139.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 179.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 249.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Alexakis P, Tsolas I (2011) Appraisal of mutual equity fund performance using data envelopment analysis. Multinat Finance J 15:273–296

    Article  Google Scholar 

  • Ali AI, Seiford LM (1990) Translation invariance in data envelopment analysis. Oper Res Lett 9:403–405

    Article  Google Scholar 

  • Anderson R, Brockman C, Giannikos C, McLeod R (2004) A nonparametric examination of real-estate mutual fund efficiency. Int J Bus Econ 3:225–238

    Google Scholar 

  • Andersen P, Petersen, N (1993) A procedure for ranking efficient units in data envelopment analysis. Manag Sci 39:1261–1264

    Google Scholar 

  • Banker RD, Charnes A, Cooper WW (1984) Some models for the estimation of technical and scale inefficiencies in data envelopment analysis. Manag Sci 30:1078–1092

    Article  Google Scholar 

  • Banker R, Cooper W, Seiford L, Thrall R, Zhu J (2004) Returns to scale in different DEA models. Eur J Oper Res 154:345–362

    Article  Google Scholar 

  • Basso A, Funari S (2001) A data envelopment analysis approach to measure the mutual fund performance. CEJOR 135(3):477–492

    Article  Google Scholar 

  • Basso A, Funari S (2003) Measuring the performance of ethical mutual funds: a DEA approach. J Oper Res Soc 54(5):521–531

    Article  Google Scholar 

  • Basso A, Funari S (2005) A generalized performance attribution technique for mutual funds. CEJOR 13(1):65–84

    Google Scholar 

  • Benninga S (2008) Financial modeling, 3rd edn. The MIT Press, Cambridge, MA

    Google Scholar 

  • Bogle J (2004) Re-mutualizing the mutual fund industry—the alpha and the omega. Boston College Law Rev 45:391–422

    Google Scholar 

  • Brown S, Goetzmann W, Park J (2001) Careers and survival: competition and risk in the hedge fund and CTA industry. J Financ 56:1869–1886

    Article  Google Scholar 

  • Carhart M (1997) Persistence in mutual fund performance. J Financ 52:57–82

    Article  Google Scholar 

  • Chang K (2004) Evaluating mutual fund performance: an application of minimum convex input requirements set approach. Comput Oper Res 31:929–940

    Article  Google Scholar 

  • Charnes A, Cooper WW, Rhodes E (1978) Measuring the efficiency of decision-making units. Eur J Oper Res 2:429–444

    Article  Google Scholar 

  • Charnes A, Cooper W, Seiford L, Stutz J (1982) A multiplicative model for efficiency analysis. Socioecon Plann Sci 16:223–224

    Article  Google Scholar 

  • Chen CM (2009) A network-DEA model with new efficiency measures to incorporate the dynamic effect in production networks. Eur J Oper Res 194:687–699

    Article  Google Scholar 

  • Chen Z, Lin R (2006) Mutual fund performance evaluation using data envelopment analysis with new risk measures. OR Spectr 28:375–398

    Article  Google Scholar 

  • Chen Y, Cook WD, Li N, Zhu J (2009) Additive efficiency decomposition in two-stage DEA. Eur J Oper Res 196:1170–1176

    Article  Google Scholar 

  • Chen Y, Cook WD, Zhu J (2010) Deriving the DEA frontier for two-stage processes. Eur J Oper Res 202:138–142

    Article  Google Scholar 

  • Chen Y, Chis Y, Li M (2011) Mutual fund performance evaluation—application of system BCC model. S Afr J Econ 79:1–16

    Article  Google Scholar 

  • Chilingerian J, Sherman HD (2004) Health care applications: from hospitals to physician, from productive efficiency to quality frontiers. In: Cooper WW, Seiford LM, Zhu J (eds) Handbook on data envelopment analysis. Springer, Boston

    Google Scholar 

  • Choi YK, Murthi BPS (2001) Relative performance evaluation of mutual funds: a non-parametric approach. J Bus Finance Acc 28:853–876

    Article  Google Scholar 

  • Cook WD, Zhu J (2014) Data envelopment analysis—a handbook of modeling internal structures and networks. Springer, New York

    Google Scholar 

  • Cook WD, Liang L, Zhu J (2010) Measuring performance of two-stage network structures by DEA: a review and future perspective. Omega 38:423–430

    Article  Google Scholar 

  • Cook WD, Tone K, Zhu J (2014) Data envelopment analysis: prior to choosing a model. Omega 44:1–4

    Article  Google Scholar 

  • Cooper WW, Seiford LM, Zhu J (2004) Handbook on data envelopment analysis. Kluwer Academic, Boston

    Book  Google Scholar 

  • Cooper WW, Seiford LM, Tone K (2006) Introduction to data envelopment analysis and its uses. Springer, New York

    Google Scholar 

  • Daraio C, Simar L (2006) A robust nonparametric approach to evaluate and explain the performance of mutual funds. Eur J Oper Res 175:516–542

    Article  Google Scholar 

  • Drake L, Weyman-Jones T (1996) Productive and allocative inefficiencies in UK Building societies: a comparison of non-parametric and stochastic frontier techniques. Manch Sch 64(1):22–37

    Article  Google Scholar 

  • Dunstan B (2012, February 15) Price customers into the market. The Australian Financial Review, p 32

    Google Scholar 

  • Eling M (2006) Performance measurement of hedge funds using data envelopment analysis. Fin Mkts Portfolio Mgmt 20(4):442–471

    Article  Google Scholar 

  • Elton E, Gruber M, Blake C (2006) The adequacy of investment choices offered by 401 K plans. J Public Econ 90:303–318

    Google Scholar 

  • Elton E, Gruber MJ, Green TC (2007) The impact of mutual fund family membership on investor risk. J Financ Quant Anal 42:257–278

    Article  Google Scholar 

  • Färe R, Grosskopf S (1996) Productivity and intermediate products: a frontier approach. Econ Lett 50:65–70

    Article  Google Scholar 

  • Färe R, Whittaker G (1995) An intermediate input model of dairy production using complex survey data. J Agric Econ 46:201–213

    Article  Google Scholar 

  • Fare R, Grosskopf S, Grifell-Tatje E, Knox-Lovell C (1997) Biased technical change and the Malmquist productivity index. Scand J Econ 99(1):119–127

    Article  Google Scholar 

  • Farrell MJ (1957) The management of productive efficiency. J R Stat Soc Ser A 120:253–290

    Article  Google Scholar 

  • Favero C, Papi L (1995) Technical efficiency and scale efficiency in the Italian banking sector: a non-parametric approach. Appl Econ 27(4):385–395

    Article  Google Scholar 

  • Ferris S, Chance D (1987) The effects of 12b-1 plans on mutual fund expense ratios: a note. J Financ 42:1077–1082

    Article  Google Scholar 

  • Fiduciary Insight 360 (2009) Fund family fiduciary rankings. Data as of December 31, 2008. Document retrieved July 12, 2010. http://www.fi360.com/press/pdfs/rankings.pdf

  • Galagedera D, Silvapulle P (2002) Australian mutual fund performance appraisal using data envelopment analysis. Manag Financ 28(9):60–73

    Google Scholar 

  • Gregoriou G (2003) Performance appraisal of funds of hedge funds using data envelopment analysis. J Wealth Manag 5:88–95

    Article  Google Scholar 

  • Gregoriou G, Sedzro K, Zhu J (2005) Hedge fund performance appraisal using data envelopment analysis. Eur J Oper Res 164:555–571

    Article  Google Scholar 

  • Haslem J, Scheraga C (2003) Data envelopment analysis of Morningstar’s large-cap mutual funds. J Invest 12(4):41–48

    Article  Google Scholar 

  • Haslem J, Scheraga CA (2006) Data envelopment analysis of Morningstar’s small-cap mutual funds. J Invest 12:87–92

    Article  Google Scholar 

  • Holod D, Lewis HF (2011) Resolving the deposit dilemma: a new DEA bank efficiency model. J Bank Financ 35:2801–2810

    Article  Google Scholar 

  • Hsu C, Lin J (2007) Mutual fund performance and persistence ion Taiwan: a non parametric approach. Serv Ind J 27:509–523

    Article  Google Scholar 

  • Hu J, Chang T (2008) Decomposition of mutual fund performance. Appl Financ Econ Lett 4:363–367

    Article  Google Scholar 

  • Investment Company Institute (ICI) (2010) Investment company fact book, 50th edn. Washington, DC

    Google Scholar 

  • Investment Company Institute (ICI) (2013) Investment company fact book. 53rd edn. Washington, DC

    Google Scholar 

  • Kao C, Hwang SN (2008) Efficiency decomposition in two-stage data envelopment analysis: an application to non-life insurance companies in Taiwan. Eur J Oper Res 185:418–429

    Article  Google Scholar 

  • Kempf A, Ruenzi S (2008) Family matters: rankings within fund families and fund inflows. J Bus Finance Acc 35:177–199

    Article  Google Scholar 

  • Koopmans T (1951) An analysis of production as an efficient combination of activities. In: Koopmans TC (ed) Activity analysis of production and allocation. Wiley, New York, pp 33–97

    Google Scholar 

  • Latzko D (1999) Economies of scale in mutual fund administration. J Financ Res 22:331–340

    Article  Google Scholar 

  • Lewis H, Sexton T (2004) Network DEA: efficiency analysis of organizations with complex internal structure. Comput Oper Res 31:1365–1410

    Article  Google Scholar 

  • Liang L, Cook WD, Zhu J (2008) DEA models for two-stage processes: game approach and efficiency decomposition. Nav Res Logist 55:643–653

    Article  Google Scholar 

  • Lozano S, Guiterrez E (2008) Data envelopment analysis of mutual funds based on second-order stochastic dominance. Eur J Oper Res 189:230–244

    Article  Google Scholar 

  • Malhotra D, McLeod R (1997) An empirical analysis of mutual fund expenses. J Financ Res 20:175–190

    Article  Google Scholar 

  • Malhotra DK, Martin R, Russel P (2007) Determinants of cost efficiencies in the mutual fund industry. Rev Financ Econ 16:323–334

    Article  Google Scholar 

  • Matallin C, Soler A, Tortosa-Ausina E (2014) On the informativeness of persistence for evaluating mutual fund performance using partial frontiers. Omega 42(1):47–64

    Article  Google Scholar 

  • McLeod R, Malhotra D (1994) A re-examination of the effects of 12b-1 plans on mutual fund expense ratios. J Financ Res 17:231–240

    Article  Google Scholar 

  • McMullen P, Strong R (1998) Selection of mutual funds using data envelopment analysis. J Bus Econ Stud 4:1–12

    Google Scholar 

  • Morningstar Research Pty Ltd (2012) Vanguard data pages. Document retrieved April 3, 2012. http://www.morningstar.com/FundFamily/vanguard.html

  • Murthi BP, Choi Y, Desai P (1997) Efficiency of mutual funds and portfolio performance measurement: a non-parametric approach. Eur J Oper Res 98:408–418

    Article  Google Scholar 

  • Nguyen-Thi-Thanh H (2006) On the use of data envelopment analysis in hedge fund selection. Working paper, Université d’Orléans

    Google Scholar 

  • Powers J, McMullen P (2000) Using data envelopment analysis to select efficient large market cap securities. J Bus Manag 7:31–42

    Google Scholar 

  • Premachandra I, Powel J, Shi J (1998) Measuring the relative efficiency of fund management strategies in New Zealand using a spreadsheet-based stochastic data envelopment analysis model. Omega 26:319–331

    Article  Google Scholar 

  • Premachandra I, Bhabra G, Sueyoshi T (2009) DEA as a tool for bankruptcy assessment: a comparative study with logistic regression technique. Eur J Oper Res 193:412–424

    Article  Google Scholar 

  • Premachandra IM, Zhu J, Watson J, Galagedera DUA (2012) Best-performing US mutual fund families from 1993 to 2008: evidence from a novel two-stage DEA model for efficiency decomposition. J Bank Finance 36:3302–3317

    Article  Google Scholar 

  • Rubio J, Hassan M, Merdad H (2012) Non-parametric performance measurement of international and Islamic mutual funds. Account Res J 25(3):208–226

    Article  Google Scholar 

  • Sedzro K, Sardano D (2000) Mutual fund performance evaluation using data envelopment analysis. In: Dahiya SB (ed) The current state of business disciplines. Spellbound, Rohtak, pp 1125–1144

    Google Scholar 

  • Sengupta J (2003) Efficiency tests for mutual fund portfolios. Appl Financ Econ 13:869–876

    Article  Google Scholar 

  • Siems TF, Barr RS (1998) Benchmarking the productive efficiency of U.S. banks. Financial industry studies. Federal Reserve Bank of Dallas, pp 11–24

    Google Scholar 

  • Smith DM (2010) The economics of mutual funds. In: Haslem JA (ed) Mutual funds: portfolio structures, analysis, management, and stewardship. Wiley, Hoboken

    Google Scholar 

  • Tone L, Tsutsui M (2009) Network DEA: a slacks-based measure approach. Eur J Oper Res 197:243–252

    Article  Google Scholar 

  • Tower E, Zheng W (2008) Ranking of mutual fund families: minimum expenses and maximum loads as markers for moral turpitude. Int Rev Econ 55:315–350

    Article  Google Scholar 

  • Wilkens K, Zhu J (2005) Classifying hedge funds using data envelopment analysis. In: Gregoriou GN, Rouah F, Karavas VN (eds) Hedge funds: strategies, risk assessment, and returns. Beard Books, Washington, DC

    Google Scholar 

  • Zhao X, Yue W (2012) A multi-subsystem fuzzy DEA model with its application in mutual funds management companies’ competence evaluation. Procedia Comput Sci 1(1):2469–2478

    Article  Google Scholar 

  • Zhu J (2002) Quantitative models for performance evaluation and benchmarking: data envelopment analysis with spreadsheets. Kluwer, Boston

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Don U. A. Galagedera .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer Science+Business Media New York

About this chapter

Cite this chapter

Premachandra, I.M., Zhu, J., Watson, J., Galagedera, D.U.A. (2016). Mutual Fund Industry Performance: A Network Data Envelopment Analysis Approach. In: Zhu, J. (eds) Data Envelopment Analysis. International Series in Operations Research & Management Science, vol 238. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7684-0_7

Download citation

Publish with us

Policies and ethics