Document Type : Research Article
Author
Department of Applied Mathematics, Yadegar-e-Imam Khomeini (RAH) Shahre Rey Branch, Islamic Azad University, Tehran, Iran
Abstract
In this paper, considering risks of a portfolio such as mean return, variance of returns, and moments of higher order as output variables including desirable and undesirable outputs, we introduce a non-radial and slack based score to measure efficiency of portfolios. Using the present measure, ranking of portfolios is provided which is consistent with standard risk-return ratios in finance. We provide illustrations to show the effects of this contribution on the measures of technical efficiency and ranking of portfolios on a sample set of daily prices of banks and credit institutions listed on the first stock market of Tehran Securities Exchange (TSE). The advantage of this paper is to present a model based on stock market returns and risk, which is based on the DEA view of the production possibility set. Of course, in making it, the quadratic property of variance and the origin of coordinates have been used as a moderating point.
Keywords
[2] A. Basso, and S. Funari, A data envelopment analysis approach to measure the mutual fund performance, Europe-an Journal of Operational Research, 135, (2001), pp. 477-492.
[3] A. Charnes, and W. W. Cooper, and E. Rhodes, Measuring the efficiency of decision making units, European Journal of Operational Research, 2(6), (1978), pp. 429-444.
[4] T.A. Christine, and L. Herve, Portfolio analysis with DEA: prior to choosing a model, Omega, 75, (2018), pp. 57-76.
[5] W.W. Cooper, L.M. Seiford,and K. Tone, Data envelopment analysis: A comprehensive text with models, appli-cations, references, and DEA-Solver soft-ware. Boston, Kluwer Academic, 2000.
[6] M.Eling, Performance measurement of hedge funds using data envelopment analysis, Financial Markets Port-folio Management, 20, (2006), pp. 442-471.
[7] D.A. Galagedera, and P. Silvapulle, Australian mutual fund performance appraisal using data envelopment analysis, Managerial Finance, 28(9), (2002), pp. 60-73.
[8] H.M. Markowitz, Portfolio selection, Journal of Finance, 7(1), (1952), pp.77-91.
[9] P.R. McMullen, R.A. Strong, Selection of Mutual Fund Using Data Envelopment Analysis, Journal of Business and Economic Studies, 4(1), (1998), pp. 1-14.
[10] M.R. Morey, and R.C. Morey, Mutual fund performance appraisals: a multi-horizon perspective with endogenous benchmarking, Omega, 27, (1999), pp. 241-258.
[11] B.P.S. Murthi, Y.K. Choi, and P. Desai, Efficiency of mutual funds and portfolioperformance measure-ment: A non-parametric approach, European Journal of OperationalResear.ch, 98, (1997), pp. 408-418
[12] I. Premachandra, J.G. Powell, and J. Shi, Measuring the Relative Efficiency ofFund Management Strate-gies in New Zealand Using a Spreadsheet-based Stochastic Data Envelopment Analysis Model, Omega, 26(2), (1998), pp. 319-331.
[13] J.K. Sengupta, Nonparametric Tests of Efficiency of Portfolio Investment, Journal of Economics, 50(1), (1989), pp. 1-15.
[15] A.C. Tarnaud, and H. Leleu, Portfolio analysis with DEA: Prior to choosing a model, Omega, 75, (2018), pp. 57-76.