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Walavalkar, Prakash M.
- A Pragmatic Investigation of the Mutual Fund Performance Determinants
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Authors
Affiliations
1 Department of MBA, Jain Institute of Technology, Davangere, Karnataka, IN
2 Department of Management Studies, Visvesvaraya Technological University, Belagavi, Karnataka, IN
3 Chartered Engineer & Approved Valuer, Belagavi, Karnataka, IN
1 Department of MBA, Jain Institute of Technology, Davangere, Karnataka, IN
2 Department of Management Studies, Visvesvaraya Technological University, Belagavi, Karnataka, IN
3 Chartered Engineer & Approved Valuer, Belagavi, Karnataka, IN
Source
International Journal of Financial Management, Vol 10, No 4 (2020), Pagination: 09-15Abstract
The research study attempts to make the mutual fund (MF) investor understand how the various risk parameters like Alpha, Asset under management, Beta, Expense Ratio, R-Squared, Sharpe Ratio, Sortino Ratio, and Standard deviation impact the returns of the MF. This information is instrumental to make dynamic investor choices. To narrow down the scope of the study analysis of 193 schemes of the top 15 MFs was considered. Only MFs with a minimum of 5 years of existence were considered. The relationship between the funds’ parameters was found using correlation and multiple regression statistical techniques. It was observed that the Sharpe ratio and Sortino ratio had a high positive correlation with the returns of the MF. The highest contributing regression predictor to explain the performance of the MF was the Sharpe ratio followed by Alpha, Expense ratio, & Asset under management.Keywords
MF Performance, Portfolio Management, Risk Parameters.
- A Study of the Identification of Efficient Mutual Funds - A Data Envelopment Analysis Approach
Abstract Views :164 |
PDF Views:0
Authors
Affiliations
1 Department of MBA, Jain Institute of Technology, Davangere, Karnataka, IN
2 Department of Management Studies, Visvesvaraya Technological University, Belagavi, Karnataka, IN
3 Belagavi, Karnataka, IN
1 Department of MBA, Jain Institute of Technology, Davangere, Karnataka, IN
2 Department of Management Studies, Visvesvaraya Technological University, Belagavi, Karnataka, IN
3 Belagavi, Karnataka, IN
Source
International Journal of Business Analytics and Intelligence, Vol 8, No 2 (2020), Pagination: 23-28Abstract
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.References
- 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/