Document Type : Original Research


Faculty of Management, Islamic Azad University, South Tehran Branch, Tehran, Iran


Performance appraisal refers to the process of performance measurement, assessment, valuation, and judgement over time. Performance ranking based on several criteria of different values is possible only when multi-criteria decision models are adopted. In this regard, different indicators are used in accordance with the type of ranking. Accordingly, inspired by the support vector machine model (SVM) and the Promethee technique, the present study aimed to develop a performance appraisal model for mutual funds and rank them accordingly. In this study, 34 mutual funds accepted in Iran’s capital market were selected during 2016-2018 using the systematic random sampling method. First, the key performance indicators were detected using the indicators of post-modern portfolio theory, which were then approved by managers, experts, and professionals. Then some information about each indicator was collected, and the experts and professionals’ comments were used to weight the indicators and specify the importance and priority of each indicator. Afterwards, an applied model was developed to represent the indicators effective in ranking mutual funds. Finally, the SVM model and the Promethee technique were adopted to rank the concerned mutual funds. The findings revealed that, in comparison to the indicators of downside risk and Sortino, upside potential ratio has the greatest effect on the performance appraisal of the mutual funds accepted in Iran’s capital market.


Main Subjects

Abzari M., S. S. (2008, Autumn & Winter). An Assessment of Effective Factors on Investment in Stock Exchange (case study: Isfahan Regional Stock Exchange). Biquarterly Journal of Economic Essays, pp. 137-162.
Adel Azar, A. R. (2012). Applied Decision Making MADM Approach. Tehran: Negah Danesh.
Awan,M & Arshad,S; (2012). “Factors Valued by Investors While Investing in Mutual Funds - A Behavioral Context”. Interdisciplinary Joural of Contemporary Research in Business; Vol. 8. No. 1, pp: 1-11.
Chen, W. K., Y. J. Chen, and T. Ch. Chen, (2007), "Using Efficiency Ratio to Measure Fund Performance", Journal of Asset Management Vol. 8, No. 6, Pp: 352–360.
Estrada, J. (2007),"Mean-Semi variance behavior: Downside risk and capital asset pricing", International Review of Economics and Finance 16 P.169-185.
Hassan Ghalibafasl, M. K. (2013). Overconfidence of Investment Managers and the Performance Assessment Indexes of Mutual Funds. Journal of Financial Management Strategy.
Jarkko Peltomäki, (2017)," Investment styles and the multifactor analysis of market timing skill ", International Journal of Managerial Finance, Vol. 13 Iss 1 pp. 21 – 35.
Kurdbacheh, H.‌ (fall 2012). Assessment of Risk-Adjusted Performance of Mutual Funds in Iran. Quaterly Journal of Economic Research and Policies, 51-82.
Lien, Donald, (2002)," A Note on the Relationship between Some Risk-Adjusted Performance Measures", Journal of Future Market, Vol 22, No5, pp. 483-495
Markowitz, H., (1959), "Portfolio Selection: Efficient Diversification of Investments", John Wiley Sons
Sharpe, William F., Gordon J. Alexander & Jeffery V. Baily, (1999), "Investments", 6d.ed, Prentice-Hall, P.825. 22- Sortino, F., Plantiga, A., and Van der Meer, R., (1999), "The Dutch Triangle: A Framework to Measure Upside Potential Relative Downside Risk", Journal of Portfolio Management, Vol. 26, No. 1,
Smith, D. M. (2014). Equity hedge fund performance, cross-sectional return dispersion, and active share. Signs that Markets are Coming Back (Research in Finance, Volume 30) Emerald Group Publishing Limited, 30, 1-22.
Sortino, F., Plantiga, A., Van der Meer, R., (2001), "The Impact of Downside Risk On Risk-Adjusted Performance Of Mutual Funds In The Euro next Markets",
Sun, Y., Grace, A., Lay Teo, K., Zhu, Y., & Wang, X. (2016). Multi-period portfolio optimization under probabilistic risk measure. Finance Research Letters, 1-7.