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A Study of the Identification of Efficient Mutual Funds - A Data Envelopment Analysis Approach
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This paper attempts to identify efficient mutual funds, analysed on the basis of Data Envelopment Analysis (DEA). This is an endeavour to study the impact of parameters like expense ratio, asset under management, standard deviation, Sortino ratio, Sharpe ratio, beta, alpha, and R-Squared, on the performance of the mutual fund, and to identify efficient mutual funds which lie on the efficient frontier according to DEA. To specify the scope of the study, the above parameters of the open-ended equity schemes of the top 15 mutual funds were considered. A relationship between the funds’ parameters was found using the linear programming methodology, which is the DEA. It was observed that only 37 mutual fund schemes implementing the constant return to scale (CRS) and 61 mutual fund schemes implementing the variable return to scale (VRS), out of the 188 mutual fund schemes under consideration, were efficient, as per the DEA approach.
Keywords
Data Envelopment Analysis, Efficient Mutual Fund.
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- Briec, W., & Kerstens, K. (2009). Multi-horizon Markowitz portfolio performance appraisals: A general approach. Omega, 37(1), 50-62.
- Briec, W., Kerstens, K., & Jokung, O. (2007). Meanvariance-skewness portfolio performance gauging: A general shortage function and dual approach. Management Science, 53(1), 135-149.
- Choi, Y. K., & Murthi, B. P. S. (2001). Relative performance evaluation of mutual funds: A non-parametric approach. Journal of Business Finance & Accounting, 28(7/8), 853-876.
- Galagedra, D., & Silvapulle, P. (2002). Australian mutual fund performance appraisal using Data Envelopmnt Analysis. Managerial Finance, 28(9), 60-73
- Joro, T., & Na, P.(2006). Portfolio Performance evaluation in a mean-varience-skewness framework. European Journal of Operational Research, 175(1), 446-461.
- Matallin, C., Soler, J., & Tortosa-Ausina, E. (2014). On the informativenedd of persistence for evaluating mutual fund performanceusig prtial frontiners. Omega, 42(1), 47-64.
- Morey, M. R., & Morey, R. C.(1999). Mutual fund performance appraisals: A multihorizon perspective with endogenous benchmarking. Omega, 27(2), 241-258.
- Murthi, B. P. S., Choi, Y. K., & Desai, P. (1997). Efficiency of mutual funds and portfolio performance measurement: A non-parametric approach. European Journal of Operational Research, 98(2), 408-418.
- Wilkens, K., & Zhu, J. (2005). Classifying hedge funds using data envelopment analysis. In G. N. Gregoriou, F. Rouah, and V. N. Karavas (Eds.). Hedge Funds: Strategies, Risk Assessment, and Returns. Washington: Beard Books.
- Zhao, X., Wang, S., & Lai, K. K. (2011). Mutual performance evaluation based on endogenous benchmarks. Expert Systems with Applications, 38, 3663-3670.
- https://banxia.com/frontier/resources/frequent-questions/
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