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On the management efficiency of Brazilian stock mutual funds

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Abstract

In this paper, we suggest a technology process assuming that a stock mutual fund, as an usual firm, can be seen as a decision-making unit, so that we can measure the effect of its decisions regarding allocation of resources for administrative and non-administrative expenses on its own levels of gain and risk. Theoretically, this approach enables us to take into account some of the critiques reported in the fund’s performance literature. In practice, we can test it by applying nonparametric linear mathematical programming methods. Here, we perform an empirical exercise based on bootstrapped Directional Distance Function in order to analyze the management efficiency of stock mutual funds in Brazil. We are able to evidence a high level of persistence in terms of efficiency over years. We can identify that the most efficient funds have higher values of net assets and that they allocate more weighted resources to administrative expenses than do the inefficient ones. Therefore, we get a high correlation of average weighted expenses on administrative expenses and average bootstrapped efficiency, about 0.7. We claim that investors should also perceive this kind of efficiency measure proposed here—relevant under the point of view of the fund managers—as a signal of performance in a short run.

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Notes

  1. A highly cited application of this arithmetic is Fama and French (2010). They use traditional asset pricing frameworks to infer about whether the performance of investment funds is random—good or bad luck—or systematic, signaling management skill.

  2. See Kerstens et al. (2012).

  3. The problem of choosing a direction vector is as old as the definition of DDF. Recently, an effort has been devoted to reaching a modeling allow choosing the direction vector with some criterion. In Fare et al. (2013) for example, the authors proposes use the optimization problem that define the directional distance function for choose the direction vector on unit simplex. It is worth to notice that this approach have problems as well. With three or more DMUs and one efficient the direction vector remains undefined.

  4. Brazilian practice draws a distinction between administration and portfolio management of investment funds. In the case of funds administered by banks, the portfolio manager is generally a part of the same financial conglomerate, so here we use the expressions administer and manage as synonyms.

  5. The standard deviation does not yet satisfy the characteristics in the sense of Artzner et al. (1999).

  6. For the sake of compatibility with the frequency of the accounting variables, we annualize the financial data in the exercise, in order to measure the inefficiency. The average return was annualized from the average daily return and the number of business days in the year, while the semivariance, as a particular case of the standard deviation, was annualized by the product of the latter (obtained from daily data) and the square root of the number of business days. These relations are easily derived if the daily returns are assumed to be i.i.d.

  7. See Andrews and Pregibon (1978).

  8. There is no rule for the number of DMUs that must be deleted, but the computational cost for six or more deletion is huge vis-à-vis a low benefit.

  9. See Avkiran (1999) for details.

  10. Except for the GWI LEVERAGE fund (F35), which was excluded from the sample in 2008 because its annualized return was negative.

References

  • Andrews D, Pregibon D (1978) Finding outliers that matter. J R Stat Soc Ser B 40:85–93

    Google Scholar 

  • Artzner P, Delbaen F, Eber J, Heath D (1999) Coherent measure of risk. Math Finance 9:203–228

    Article  Google Scholar 

  • Avkiran N (1999) The evidence on efficiency gains: the role of mergers and the benefits to the public. J Bank Finance 23:991–1013

    Article  Google Scholar 

  • Banker R, Charnes A, Cooper W (1984) Some models for estimating technical and scale inefficiencies in data envelopment analysis. Manage Sci 30:1078–1092

    Article  Google Scholar 

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

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Briec W, Kerstens K (2009) Multi-horizon Markowitz portfolio performance appraisals: a general approach. Omega Int J Manage Sci 37:50–62

    Article  Google Scholar 

  • Ceretta P, Costa N Jr (2001) Avaliação e seleção de fundos de investimento: um enfoque sobre múltiplos atributos. Rev Adm Contemp 5:7–22

    Google Scholar 

  • Chambers R, Chung Y, Färe R (1996) Benefit and distance functions. J Econ Theory 70:407–419

    Article  Google Scholar 

  • Chambers R, Chung Y, Färe R (1998) Profit, directional distance functions and Nerlovian efficiency. J Optim Theory Appl 98:351–364

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Chung Y, Färe R, Grosskopf S (1997) Productivity and undesirable outputs: a directional distance function approach. J Environ Manage 51:229–240

    Article  Google Scholar 

  • Dalmácio F, Nossa V, Zanquetto Filho H (2007) Avaliação da relação entre a performance e a taxa de administração dos fundos de ações ativos brasileiros. Rev Educ Pesqui Contab 1:1–30

    Google Scholar 

  • Devaney M, Webe W (2005) Efficiency, scale economies and risk-return performance of real estate investment trusts. J Real Estate Finance Econ 31:301–317

    Article  Google Scholar 

  • Duvernoy T (2009) Avaliação de performance de fundos de investimento utilizando fatores estocásticos de desconto admissíveis não paramétricos. Dissertação de mestrado submetida à Escola de Pós-Graduação em Economia da Fundação Getulio Vargas, EPGE/FGV-RJ

  • Fama E, French K (2010) Luck versus skill in the cross-section of mutual fund returns. J Finance 65:1915–1947

    Article  Google Scholar 

  • Färe R, Grosskopf S (2004) New directions: efficiency and productivity. Kluwer, Dordrecht

    Google Scholar 

  • Fare R, Grosskopf S, Whittaker G (2013) Directional output distance functions: endogenous directions based on exogenous normalization constraints. J Prod Anal 40:267–269

    Article  Google Scholar 

  • Farias A, Ornelas J, Silva A Jr (2009) Accounting for skewness in performance evaluation of brazilian mutual funds. Bank Finance Rev 1:119–132

    Google Scholar 

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

    Article  Google Scholar 

  • Fukuyama H, Weber W (2002) Estimating output allocative efficiency and productivity change: application to Japanese banks. Eur J Oper Res 137:177–190

    Article  Google Scholar 

  • Gattoufi S, Oral M, Reisman A (2004) Data envelopment analysis literature: a bibliography update (1951–2001). Socio-Econ Plan Sci 38:159–229

    Article  Google Scholar 

  • Grossman S, Stiglitz J (1980) On the impossibility of informationally efficient markets. Am Econ Rev 70:393–408

    Google Scholar 

  • Haslem J (2009) Mutual funds: portfolio structures, analysis, management and stewardship. Kolb Series in Finance. Wiley, New York

    Book  Google Scholar 

  • Huesler A, Malevergne Y, Sornette D (2014) Investors’ expectations, management fees and the underperformance of mutual funds. Int J Portf Anal Manage 1:345–379

    Google Scholar 

  • Huji J, Lansdorp S (2012) Mutual fund performance persistence, market efficiency, and breadth and breadth. Social Science Research Network Working Paper

  • Jin I (2003) Risk adjusted rate of return: directional distance function approach. Ph.D. thesis Rice University

  • Kerstens K, Mounir A, Van de Woestyne I (2012) Benchmarking mean-variance portfolios using a shortage function: the choice of direction vector affects rankings! J Oper Res Soc 63:1199–1212

    Article  Google Scholar 

  • Kneip A, Simar L, Wilson P (2008) Asymptotics and consistent bootstraps for DEA estimators in non-parametric frontier models. Econ Theory 24:1663–1697

    Article  Google Scholar 

  • Laes M, da Silva M (2014) Performance of mutual equity funds in Brazil—a bootstrap analysis. ANPEC J 15:294–306

    Google Scholar 

  • Luenberger D (1992) Benefit functions and duality. J Math Econ 21:461–481

    Article  Google Scholar 

  • Markowitz H (1952) Portfolio selection. J Finance 7:77–91

    Google Scholar 

  • Matos P, Castro A (2012) Brazilian stock mutual funds: Performance and management expertise. Braz Bus Rev Spec Edn 1–38

  • Matos P, Correa W, Silva F (2013) Sorte versus habilidade na análise de desempenho de fundos de investimento em ações no Brasil. VIII Prêmio Anbima de Mercado de Capitais

  • Matos P, Balbina A, Penna C (2015) Why are the Brazilian stock mutual funds so different? Braz Bus Rev 12:110–144

    Article  Google Scholar 

  • Matsumoto A (2005) Vale à pena correr risco em fundos de investimentos alavancados no Brasil? 5º Congresso USP Controladoria e Contabilidade

  • Monteiro R (2006) Persistência de Performance nos Fundos de Investimento em Ações no Brasil. Repositório Científico de Acesso Aberto de Portugal

  • Murthi B, 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 

  • Park K, Weber W (2006) A note on efficiency and productivity growth in the Korean banking industry, 1992–2002. J Bank Finance 30:2371–2386

    Article  Google Scholar 

  • Pendaraki K (2015) Mutual fund performance benchmarking using a quadratic directional distance function approach. Int J Financ Eng Risk Manage 2:30–47

    Article  Google Scholar 

  • Resende Neto A (2006) Uma proposta de construção de indicador de performance de fundos de investimento. Dissertação de mestrado submetida à Escola de Pós-Graduação em Economia da UNB

  • Sengupta J (2000) Dynamic and stochastic efficiency analysis: economics of data envelopment analysis. World Scientific Publishing Co., Pte. Ltd, Singapore

    Book  Google Scholar 

  • Sharpe W (1991) The arithmetic of active management. Financ Anal J 47:7–9

    Article  Google Scholar 

  • Shephard R (1953) Cost and production functions. Princeton University Press, Princeton

    Google Scholar 

  • Shephard R (1970) Theory of cost and production functions. Princeton University Press, Princeton

    Google Scholar 

  • Simar L, Vanhems A, Wilson P (2012) Statistical inference for DEA estimators of directional distances. Eur J Oper Res 220:853–864

    Article  Google Scholar 

  • Sobrinho J (2003) Estratégias de gestão de fundos de investimentos em ações: análise da performance de fundos de gestão ativa no período de 1996 a 2000. Anais do VI Semead—Seminários de Administração

  • Tsolas I, Charles V (2015) Green exchange-traded fund performance appraisal using slacks-based DEA models. Oper Res Int Journal 15:51–77

    Article  Google Scholar 

  • Varga G (2001) Índice de Sharpe e outros indicadores de performance aplicados a fundos de ações brasileiros. Rev Adm Contemp 5:215–245

    Article  Google Scholar 

  • Wilson P (1993) Detecting outliers in deterministic nonparametric frontier models with multiple outputs. J Bus Econ Stat 11:319–323

    Google Scholar 

  • Zakamouline V, Koekebakker S (2009) Portfolio performance evaluation with generalized sharpe ratios: beyond the mean and variance. J Bank Finance 33:1242–1254

    Article  Google Scholar 

Download references

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Authors and Affiliations

  1. CAEN/UFC, Avenida da Universidade, 2700, Bairro Benfica, Ceará, CEP 60.020.181, Fortaleza, Brazil

    Paulo Matos & Maurício Benegas

  2. Petrobrás, Fortaleza, Brazil

    Guilherme Padilha

Authors
  1. Paulo Matos
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  2. Guilherme Padilha
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  3. Maurício Benegas
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Correspondence to Paulo Matos.

Additional information

This paper has greatly benefited from comments and suggestions by participants at 2013 First International Workshop in Financial Econometrics.

Appendix

Appendix

See Table 8 below.

Table 8 Bootstrapped DDF: complementary results
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Matos, P., Padilha, G. & Benegas, M. On the management efficiency of Brazilian stock mutual funds. Oper Res Int J 16, 365–399 (2016). https://doi.org/10.1007/s12351-015-0204-y

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