Show simple item record

dc.contributor.authorWatson, John Ren_NZ
dc.identifier.citationWatson, J. R. (2003, September 2). Evaluating the relative efficiencies of Morningstar mutual funds using @RISK — A stochastic data envelopment analysis approach (Thesis, Master of Commerce). Retrieved from
dc.description.abstractInstitutional and individual investors have always been interested in identifying those mutual funds that appear to outperform the market more often than not. Identification of such funds is not difficult as a simple comparison against the market index allows individual fund performance to be evaluated on an absolute basis. However, this approach is insufficient for investors to make a comparison between funds with different return and risk levels. Entrenched in finance literature is the Sharpe measure and coefficient of variation, techniques that utilize both the standard deviation (a measure of risk) and expected return (a measure of return). This thesis proposes using a new methodology, Data Envelopment Analysis, to evaluate mutual funds on a relative basis. Data Envelopment Analysis (DEA) is widely used to analyse the relative efficiencies of decision-making units (DMUs) that are similar in nature. There are two important versions of DEA, namely, Deterministic Data Envelopment Analysis (DDEA) developed to consider deterministic input and output variables, and Stochastic Data Envelopment Analysis (SDEA) used extensively when input or output variables are random in nature. This thesis applies a simulation approach to SDEA based on EXCEL/@RISK, which provides a variety of informative statistical measures about the stochastic properties of the efficiency figure. The approach is illustrated by analyzing the relative performance of the largest United States equity mutual funds towards the end of the 20th century using historical data to identify significantly efficient and inefficient funds. The model is validated using an extensive window analysis where the results obtained by the SDEA model are compared with the traditional mean-variance approaches preferred in the past. This introduces to the portfolio performance evaluation literature a new tool for evaluating relative (as opposed to absolute) fund performance.en_NZ
dc.subjectmutual fundsen_NZ
dc.subjectmarket indexen_NZ
dc.subjectreturn and risken_NZ
dc.subjectportfolio performance evaluationen_NZ
dc.subjectfund performanceen_NZ
dc.subject.lcshHF Commerceen_NZ
dc.subject.lcshHF5601 Accountingen_NZ
dc.subject.lcshHG Financeen_NZ
dc.subject.lcshHF5601 Accountingen_NZ
dc.titleEvaluating the relative efficiencies of Morningstar mutual funds using @RISK — A stochastic data envelopment analysis approachen_NZ
otago.schoolFinanceen_NZ of Commerce of Otagoen_NZ Thesesen_NZ
otago.openaccessAbstract Only
dc.identifier.eprints574en_NZ & Quantitative Analysisen_NZ
dc.description.referencesAl-Faraj, Midi, A.S., and Bu-shait, K.A., 1993, "Evaluation of bank branches by means of data envelopment analysis, Journal of Operations and Production Management, 13, 45-52 Atkinson, S.E., and Wilson, P.W., 1995, Comparing mean efficiency and productivity scores from small samples: a bootstrap methodology, The Journal of productivity analysis, 6, 137- 162 Banker, R.D, Charnes, A., and Cooper, W.W., 1984, Some models for estimating technical and scale inefficiencies in data envelopment analysis, Management Science, 30, 1078-1092 Banker, R.D., and Morey, R.C., 1986, The use of categorical variables in data envelopment Analysis, Management Science, 32, 1613-1627 Banker, R.D., and Morey, R.C., 1989, Incorporating Value judgments in Efficiency Analysis, Research in Governmental and Nonprofit Accounting, 5, 245-267 Banker, R.D., 1993, Maximum Liklihood, Consistency and Data Envelopment Analysis: A Statistical Foundation, Management Science, 39, 1265-1273 Banker, R.D., Chang, H. and Cooper, W.W., 1996, Simulation studies of efficiency, returns to scale and misspecification with nonlinear functions in DEA, Annals of Operations Research, 66, 233-253 Bardhan, I.R., Cooper, W.W., and Kumbkakar, S.C., 1998, A Simulation Study of Joint Uses of Data Envelopment Analysis and Stochastic Regressions for Production Function Estimation and Efficiency Evaluation, Journal of Productivity Analysis, 9, 249-278. Berg, S.A., Forsund, F.R., Hjalmarsson, L., and Suominen, M., 1993, Banking Efficiency in the Nordic countries, Journal of Banking and Finance, 17, 371-388 Bickel, P.J., and Freedman, D.A., 1981, Some Asymptotic Theory for the Bootstrap, Annals of Statistics, 9, 1196-1217 Bodie, Z., Kane, A., and Marcus, A.J., 2000, Investments, Fifth Edition, New York, McGraw- Hill Brockett, P.L., Cooper, W.W., Golden, G.L., Rousseau, J.J., and Wang, Y., 1998, DEA Evaluation of Organisational Forms and Distribution System in the U.S. Property and Liability Insurance Industry, International Journal of Systems Science Brown, S.J., Goetzmann, W.N., Ibbotson, R.G., and Ross, S.A., 1992, Surviorship Bias in Performance Studies, Review of Financial Studies, 5, 553-580 Callen, J.L., 1991, Data Envelopment Analysis: Partial Survey and Applications for Management Accounting, Journal of Management Accounting Research, 35-55 Camm, J.D., and Burwell, T.H., 1991, Sensitivity analysis in linear programming models with common inputs, Decision Science, 22, 512-518 Charnes, A., Cooper, W.W., and Rodes, E., 1978, Measuring the efficiency of decision making units, European Journal of Operational Research, 2, 429-444 Charnes, A., Cooper, WM., and Rhodes, E., 1981, Evaluating program and managerial efficiency: An application of data envelopment analysis to program follow through, Management Science, 27, 668-697 Charnes, A., Clark, T., Cooper W.W., and Golany, B. (1985) A developmental study of data envelopment analysis in measuring the efficiency of maintenance units in the U.S. air forces, Annals of Operational Research, 2, 95-112 Chillingerian, J.A., 1995, Evaluating physician efficiency in hospitals: a multivariate analysis of best practices, European Journal of Operational Research, 80, 548-574 Cholos, P., 1997, An examination of budgetary inefficiency in education using data envelopment Analysis, Financial Accountability and Management, 13, 55-69 Cooper, W.W., Huang, Z., Li, S.X., and Olsen, 0.B., 1998, Chance Constrained Programming Formulations for Stochastic Characterizations of Efficiency and Dominance in DEA, Journal of Productivity Analysis, 9, 53-79. Cooper, W.W., Seiford, L.M., and Tone, K., 2000, Data Envelopment Analysis, Massachusetts, Kluwer Academic Publishers Copeland, T.E., and Weston, J.F., 1992, Financial Theory and Corporate Policy, Third Edition, Massachusetts, Addison-Wesley Dimson, E., Marsh, P., and Staunton, M., 2000, Twelve centuries of capital market returns, Working Paper, London Business School. Donna, L.R., and Richard, C.M., 1993, A goal programming method of stochastic allocative data envelopment analysis, European Journal of Operational research, 71, 379-397. Drake, L., and Howcraft, B., 1994, Relative efficiency in the branch network of a UK bank: an empirical study, Omega, 22, 83-90 Dyson, R.G., Allen R., Camanho A.S., Podinovski, V.V., Sarrico C.S. and Shale E.A., 2001, Pitfalls and Protocols in DEA, European Journal of Operational Research, Vol 132, 245-259. Efron, B., 1979, Bootstrap methods: another look at the jackknife, Annals of Statistics, 7, 1-26 Efron, B., 1981a, Nonparametric estimates of standard error: the jackknife, the bootstrap and other Methods, Biometrika, 68, 589-599 Efron, B., 1981b, Nonparametric standard errors and confidence intervals, Canadian Journal of Statistics, 9, 139-172 Efron, B., 1982, The jackknife, the bootstrap and other resampling plans. Volume 38 of CBMS-NSF Regional Conference Series in Applied Mathematics, SIAM Efron, B., and Tibshirani, R.J., 1993, An Introduction to the Bootstrap, United States of America, Chapman and Hail Farrell, M.J., 1957, The management of productive efficiency, Journal of Royal Statistical Society Series A, 253-290 Giokas, D., 1991, Bank Branch Operating Efficiency: a comparative application of DEA and the loglinear model, Omega, 19, 549-557 Gitman, and Joehnk, M.D., 1999, Personal Financial Planning, Eighth Edition" Orlando, Dryden Grinblatt, M., and Titman, S., 1989, Mutual Fund Performance: An Analysis of Quarterly Portfolio Holdings, Journal of Business, 62 Iss. 3, 393-416 Grinblatt, M., and Titman, S., 1993, Performance measurement without benchmarks: An examination of mutual fund returns, Journal of Business, 66, 47-68 Haag, S., Jaska, P., and Semple, J., 1992, Assessing the relative efficiency of agricultural production units in the Blackland Prairie, Texas, Applied Econometrics, 24, 559-565 Hirsch, J.S., 1996, Magellans Stansky Puts More Money in Stocks, Wall Street Journal Interactive Edition, 13, 1-4 Huber, P.J., 1985, Projection Pursuit, The Annals of Statistics, 13(2), 435-475 Hutching, C., 1997, Southpac's funds to turn passive, National Business Review, Feb. 7, 61 Investment Company Institute, 1997. Mutual Fund Fact Book. See ( Jensen, M., 1968, The performance of mutual funds in the period 1945-1964, Journal of Finance, 23, 398-416 Kelton, D.W., and Law, A.M., 1991, Simulation, Modeling and Analysis, Second Edition, New York, McGraw-Hill, Klopp, G., 1985, The Analysis of the Efficiency of Production System with Multiple Inputs and Outputs, Ph. D. thesis (Chicago: University of Illinois at Chicago, Industrial and Systems Engineering College). Korostolev A.O., Simar, L. and Tsybakov., 1995, On Estimation of Monotone and Convex Boundaries, Annals of Statistics, 23, 476-489 Lewin, A., and Morey, R.C., 1981, Measuring the Relative Efficiency and Output Potential of Public Sector Organisations: An Application of Data Envelopment Analysis, Journal of Policy Analysis and Information Systems, 5 No. 4, 267-285 Lothgren, M., 1997, On the consistency of the DEA-based average technical efficiency bootstrap, Working Paper, The Economic Research Institute Stockholm School of Economics, Stockholm, Sweden Manly, B.F.J., 1997, Randomization, Bootstrap and Monte Carlo Methods in Biology, Chapman and Hall, London Markowitz, Harry M., 1952, Portfolio Selection, Journal of Finance, March, 77-91 McEwen, D., 1996, Slow decline in managed fund inflows, National Business Review, Nov 8, 71 McGeehan, P.,2000, Fraud Charge Filed Against Dean Witter, The New York Times, Nov 21 McMullen, P.R., and Strong, R.A., 1998, Selection of mutual funds using data envelopment Analysis, Journal of Business and Economic Studies, 4, 1-12 Morey, R.C., and McCann, J., 1980, Evaluating and Improving the Recruiting Process for the Navy, Management Science, 26 No. 12, 1198-1210 Murthi, B.P.S., Choi, Y.K., and Desai, P., 1997, Efficiency of mutual funds and portfolio performance measurement: a non parametric approach, European Journal of Operational Research, 98, 408-418 Olsen, 0.B., and Peterson, N.C., 1995, Chance constrained efficiency evaluation, Management Science, 41 Iss. 3, 442-457 Pilgrim, K., 1996, Investors lost confidence in Vinik, CNNfn, May 23, 1 Premachandra, I.M, 1996, A numerical approach for stochastic data envelopment analysis using @RISK, Department of Finance and Quantitative Analysis, Working Paper no. 9605, University of Otago Premachandra, I.M, Powel J.G., Jing Shi, 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 Premachandra, 1.M., Powell, J.G., and Watson, J.R., 2000, A Simulation Approach for Stochastic Data Envelopment Analysis, International Journal of Information and Management Science, 11 No.1, 11-31 Retzlaff-Roberts, D.L., and Morey, R.C., 1993, A goal programming method of stochastic allocative data envelopment analysis, European Journal of Operational Research, 71, 373- 397 Sedzro, K., and Sardano, D., 2000, Mutual fund performance evaluation using data envelopment Analysis, Working Paper, School of Business, University of Quebec, Montreal, Canada Sengupta, J.K., 1987, Data envelopment analysis for efficiency measurement in the stochastic Case, Computers and Operations Research, 14, 117-129 Sharpe, W.F., 1966, Mutual Fund Performance, Journal of Business, 34, 119-138 Sharpe, W.F., 1994, The Sharpe Ratio, The Journal of Portfolio Management, Fall, 49-58 Simar, L., and Wilson, P.W., 1998, Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models, Management Science, 44, 49-61 Sinuany-Stern, Z., and Mehrez, A., and Barboy, A., 1994, Academic departments efficiency via DEA, Computers & Operations Research, 21 Iss. 5, 543 – 556 Talluri, S., 2000, Data Envelopment Analysis: Models and Extensions, Decision Line, May, 8-11 Thanassoulios, E., 1996, Assessing the effectiveness of schools with pupils of differing ability using data envelopment analysis, The Journal of Operational Research Society, 47, Iss. 1, 84-97 Thanassoulios, E., Boussofiane, A., and Dyson, R.G., 1996, A comparison of data envelopment analysis and ratio analysis as tools for performance assessment, Omega, 24 Iss.3, 229-234 Treynor, J., 1966, How to rate management of investment funds, Harvard Business Review,43, 53-75 Vos, W., 1997, Measuring mutual fund performance, Canadian Investment Review, 10, 33-37en_NZ
 Find in your library

Files in this item


There are no files associated with this item.

This item is not available in full-text via OUR Archive.

If you would like to read this item, please apply for an inter-library loan from the University of Otago via your local library.

If you are the author of this item, please contact us if you wish to discuss making the full text publicly available.

This item appears in the following Collection(s)

Show simple item record