Neural network DEA for measuring the efficiency of mutual funds

Efficiency in the mutual fund (MF), is one of the issues that has attracted many investors in countries with advanced financial market for many years. Due to the need for frequent study of MF's efficiency in short-term periods, investors need a method that not only has high accuracy, but also high speed. Data envelopment analysis (DEA) is proven to be one of the most widely used methods in the measurement of the efficiency and productivity of decision making units (DMUs). DEA for a large dataset with many inputs/outputs would require huge computer resources in terms of memory and CPU time. This paper uses neural network back-ropagation DEA in measurement of mutual funds efficiency and shows the requirements, in the proposed method, for computer memory and CPU time are far less than that needed by conventional DEA methods and can therefore be a useful tool in measuring the efficiency of a large set of MFs. Copyright © 2014 Inderscience Enterprises Ltd.

[1]  Joe Zhu,et al.  Hedge fund performance appraisal using data envelopment analysis , 2005, Eur. J. Oper. Res..

[2]  Ali Emrouznejad,et al.  A mathematical model for dynamic efficiency using data envelopment analysis , 2005, Appl. Math. Comput..

[3]  John A. Haslem,et al.  Data Envelopment Analysis of Morningstar's Large-Cap Mutual Funds , 2003 .

[4]  Ali Emrouznejad,et al.  Measuring the Performance of Neonatal Care Units in Scotland , 2003, Journal of Medical Systems.

[5]  Paul Na,et al.  Portfolio performance evaluation in a mean-variance-skewness framework , 2006, Eur. J. Oper. Res..

[6]  Joe Zhu,et al.  Best-performing US mutual fund families from 1993 to 2008: Evidence from a novel two-stage DEA model for efficiency decomposition , 2012 .

[7]  Mahmoud Omid,et al.  Measuring productive efficiency of horticultural greenhouses in Iran: A data envelopment analysis approach , 2012, Expert Syst. Appl..

[8]  F. Sortino,et al.  Performance Measurement in a Downside Risk Framework , 1994 .

[9]  Ali Emrouznejad,et al.  A framework for performance evaluation of employment offices: a case of Tunisia , 2011, Int. J. Appl. Decis. Sci..

[10]  Matthias Staat,et al.  Efficiency of hospitals in Germany: a DEA-bootstrap approach , 2006 .

[11]  Ali Emrouznejad,et al.  A combined neural network and DEA for measuring efficiency of large scale datasets , 2009, Comput. Ind. Eng..

[12]  John Quigley,et al.  Using data envelopment analysis to model the performance of UK coastguard centres , 2005, J. Oper. Res. Soc..

[13]  Fadzlan Sufian.  The evolution of Malaysian banking sector's efficiency during financial duress: consequences, concerns, and policy implications , 2010, Int. J. Appl. Decis. Sci..

[14]  Hassiba Djema,et al.  A two-stage DEA with partial least squares regression model for performance analysis in healthcare in Algeria , 2012, Int. J. Appl. Decis. Sci..

[15]  Fadzlan Sufian,et al.  Trends in the efficiency of Singapore's commercial banking groups , 2007 .

[16]  Shouyang Wang,et al.  Empirical Study on Chinese Mutual Funds' Performance , 2007 .

[17]  John A. Haslem,et al.  Data Envelopment Analysis of Morningstar's Small-Cap Mutual Funds , 2003 .

[18]  Johann deVilliers,et al.  Beyond Mean–Variance: Performance Measurement in a Nonsymmetrical World , 1999 .

[19]  Patrizia Beraldi,et al.  Using DEA and financial ratings for credit risk evaluation: an empirical analysis , 2013 .

[20]  Ma Zhanxin,et al.  Program Design of DEA Based on Windows System , 2012 .

[21]  Greg N. Gregoriou,et al.  Risk-Adjusted Performance of Funds of Hedge Funds Using a Modified Sharpe Ratio , 2003 .

[22]  Antonella Basso,et al.  A Data Envelopment Analysis Approach to Measure the Mutual Fund Performance , 2001, Eur. J. Oper. Res..

[23]  Sebastián Lozano,et al.  Data envelopment analysis of mutual funds based on second-order stochastic dominance , 2008, Eur. J. Oper. Res..

[24]  Preyas S. Desai,et al.  Efficiency of mutual funds and portfolio performance measurement: A non-parametric approach , 1997 .

[25]  William W. Cooper,et al.  Handbook on data envelopment analysis , 2011 .

[26]  Yu-chuan Chen,et al.  MUTUAL FUND PERFORMANCE EVALUATION – APPLICATION OF SYSTEM BCC MODEL , 2011 .

[27]  K. Lai,et al.  Mutual funds return and risk decomposition evaluation based on quadratic-constrained DEA models , 2011 .

[28]  Robert J. Schalkoff,et al.  Artificial neural networks , 1997 .

[29]  Andreas Burger,et al.  Performance analysis on process level: benchmarking of transactions in banking , 2010 .

[30]  Ali Emrouznejad,et al.  Evaluation of research in efficiency and productivity: A survey and analysis of the first 30 years , 2008 .

[31]  D. Wu,et al.  Measuring bank performance using DEA and Monte Carlo simulation , 2008 .

[32]  Marvin D. Troutt,et al.  The potential use of DEA for credit applicant acceptance systems , 1996, Comput. Oper. Res..

[33]  Tripta Thakur,et al.  Measurement of relative operational efficiency of SOEUs in India using data envelopment analysis , 2009, Int. J. Appl. Decis. Sci..

[34]  Shengzhi Du,et al.  An intelligent character recognition system for automatic mark capturing , 2014, 2014 7th International Congress on Image and Signal Processing.

[35]  P. Andersen,et al.  A procedure for ranking efficient units in data envelopment analysis , 1993 .

[36]  Joe Zhu,et al.  Portfolio Evaluation and Benchmark Selection , 2001 .

[37]  Fred D. Arditti.  RISK AND THE REQUIRED RETURN ON EQUITY , 1967 .

[38]  Michael J. Stutzer,et al.  A Portfolio Performance Index , 2000 .

[39]  Payam Hanafizadeh,et al.  Defining strategic processes in investment companies: An exploration study in Iranian Investment Companies , 2009, Bus. Process. Manag. J..

[40]  Ali Emrouznejad,et al.  DEA models for ratio data:convexity consideration , 2009 .

[41]  Kuo-Ping Chang,et al.  Evaluating mutual fund performance: an application of minimum convex input requirement set approach , 2004, Comput. Oper. Res..

[42]  H. Nguyen-Thi-Thanh.  Hedge fund behavior: An ex-post analysis , 2004 .

[43]  Christos I. Giannikos,et al.  A Non-Parametric Examination of Real Estate Mutual Fund Efficiency , 2004 .

[44]  Antonella Basso,et al.  Measuring the performance of ethical mutual funds: a DEA approach , 2002, J. Oper. Res. Soc..

[45]  Kristiaan Kerstens,et al.  Mean-Variance-Skewness Portfolio Performance Gauging: A General Shortage Function and Dual Approach , 2007, Manag. Sci..

[46]  Abraham Charnes,et al.  Measuring the efficiency of decision making units , 1978 .