An ensemble approach for portfolio selection in a multi-criteria decision making framework

Sanjib Biswas; Gautam Bandyopadhyay; Banhi Guha; Malay Bhattacharjee

doi:10.31181/dmame2003079b

Authors

Sanjib Biswas Calcutta Business School, Diamond Harbour Road, Bishnupur, West Bengal, India
Gautam Bandyopadhyay Department of Management Studies, National Institute of Technology, Durgapur, West Bengal, India
Banhi Guha Amity University, Kolkata, West Bengal, India
Malay Bhattacharjee Department of Management Studies, National Institute of Technology, Durgapur, West Bengal, India

DOI:

https://doi.org/10.31181/dmame2003079b

Keywords:

Mutual Fund, Portfolio Selection, Multi-Criteria Decision Making, Data Envelopment Analysis (DEA), Entropy, Multi-Attribute Border Approximation Area Comparisons (MABAC).

Abstract

Investment in Mutual Funds (MF) has generated increasing interest among the investors over last few decades as it provides an opportunity for flexible and transparent choice of funds to diversify risk while having return potential. MF are essentially a portfolio wherein investors’ funds are invested in the securities traded in the capital market while sharing a common objective. However, selection and management of different asset classes pertaining to a particular MF are done by an active fund manager under regulatory supervision. Hence, for an individual investor, it is important to assess the performances of the MF before investment. Performances of MF depend on several criteria based on risk-return measures. Hence, selection of MF is subject to satisfying multiple criteria. In this paper, we have adopted an ensemble approach based on a two-stage framework. Our sample consists of the open ended equity large cap funds (direct plan) in India. In the first stage,the efficiencies of the funds are analyzed using DEA for primary selection of the funds. In order to rank the funds based on risk and return parameters for investment portfolio formulation, we have used MABAC approach in the second stage wherein criteria weights have been calculated using the Entropy method.

Downloads

Download data is not yet available.

References

Ali, A. I., & Seiford, L. M. (1990).Translation invariance in data envelopment analysis. Operations research letters, 9(6), 403-405.

Alptekin, N. (2009). Performance evaluation of Turkish type a mutual funds and pension stock funds by using TOPSIS method. International Journal of Economics and Finance Studies, 1(2), 11-22.

AMFI. (2018). Association of Mutual Funds in India. https://www.amfiindia.com/indian-mutual

Anand, S., & Murugaiah, V. (2006). Analysis of components of investment performance: An empirical study of mutual funds in India. 10th Indian Institute of Capital Markets Conference, IU, Hyderabad, India.

Anderson, R., Brockman, C., Giannikos, C., & McLeod, R. (2004). A non-parametric examination of real estate mutual fund efficiency. International Journal of Business and Economics, 3, 225–238.

Anitha, R., Devasenathipathi, T., & Radhapriya, C. (2011). Comparative analysis of market returns and fund flows with reference to mutual funds. International Journal of Research in Commerce, IT & Management, 1(4), 4558.

Arora, K. (2015). Riskadjusted performance evaluation of Indian mutual fund schemes.Paradigm, 19(1), 7994.

Babalos, V., Mamatzakis, E. C., & Matousek, R. (2015). The performance of US equity mutual funds. Journal of Banking & Finance, 52, 217-229.

Babalos, V., Philippas, N., Doumpos, M., & Zopounidis, C. (2011). Mutual Funds Performance Appraisal Using a Multi Criteria Decision Making Approach. Financial Engineering Laboratory (University of Crete).

Banker, R. D., Charnes, A., Cooper, W. W., & Clarke, R. (1989).Constrained game formulations and interpretations for data envelopment analysis. European Journal of Operational Research, 40(3), 299-308.

Barua, K. S., & Verma, J. R. (1991). Master shares: A bonanza for large investors. Vikalpa, 16(1), 2934.

Basso, A., & Funari, S. (2001). Data Envelopment Analysis Approach to Measure the Mutual Fund Performance. Europen Journal of Operational Research, 135, 477-492.

Briec, W., Kerstens, K., & Lesourd, J.B (2004). Single-period Markowitz portfolio selection, performance gauging, and duality: a variation on the Luenberger shortage function. Journal of Optimization Theory and Applications, 120(1), 1–27.

Cambell, J. Y., & Hentschel, L. (1992). No news is good news: An asymmetric model of changing volatility of stock returns. Journal of Financial Economics, 31, 281-318.

Carlos Matallín, J., Soler, A., &Tortosa-Ausina, E. (2014). On the informativeness of persistence for evaluating mutual fund performance using partial frontiers. Omega, 42(1), 47–64. DOI: 10.1016/j.omega.2013.03.001.

Chang, C. H., Lin, J. J., Lin, J. H., & Chiang, M. C. (2010). Domestic open-end equity mutual fund performance evaluation using extended TOPSIS method with different distance approaches. Expert systems with applications, 37(6), 4642-4649.

Chang, K. P. (2004). Evaluating mutual fund performance: an application of minimum convex input requirement set approach. Computers & Operations Research, 31(6), 929–940.

Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European journal of operational research, 2(6), 429-444.

Chu, J., Chen, F., & Leung, P. (2010). ETF performance measurement—Data envelopment analysis. In 2010 7th International Conference on Service Systems and Service Management (pp. 1-6). IEEE.

Daraio, C., & Simar, L. (2006). A robust nonparametric approach to evaluate and explain the performance of mutual funds. European Journal of Operational Research, 175, 516–542.

Eling, M., & Schuhmacher, F. (2007). Does the choice of performance measure influence the evaluation of hedge funds? Journal of Banking and Finance, 31(9), 2632 2647.

Galagedera, D., & Silvapulle, P. (2002). Australian Mutual Fund Performance Appraisal Using Data Envelopment Analysis. Managerial Finance, 28(9), 60–73.

Gladish, B. P., Jones, D. F., Tamiz, M., & Terol, A. B. (2007). An interactive three-stage model for mutual funds portfolio selection. Omega, 35(1), 75-88.

Gupta, A. (2000). Investment performance of Indian mutual funds: An empirical study. Finance India, 14(3), 833866.

Gupta, S., Bandyopadhyay, G., Biswas, S., & Upadhyay, A. (2019). A hybrid machine learning and dynamic nonlinear framework for determination of optimum portfolio structure. In Innovations in Computer Science and Engineering: Proceedings of the Sixth ICICSE 2018 (pp. 437-448). Springer Singapore.

Haslem, J., & Scheraga, C. (2003). Data envelopment analysis of Morningstar’s large-cap mutual funds. Journal of Investing, 12 (4), 41–48.

Hwang, C. L., & Yoon, K. (1981). Multiple attribute decision making: Methods and applications. Heidelberg: Springer.

Jahan, A., & Edwards, K. L. (2015). A state-of-the-art survey on the influence of normalization techniques in ranking: Improving the materials selection process in engineering design. Materials & Design (1980-2015), 65, 335-342.

Jayadev, M. (1996). Mutual fund performance: An analysis of monthly returns. Finance India, 10 (1), 7384.

Jensen, M. (1968). The performance of mutual funds in the period 1945–64.Journal of Finance, 23, 389– 416.

Joro, T., & Na, P. (2006). Portfolio performance evaluation in a mean–variance–skewness framework. European Journal of Operational Research, 175(1), 446-461.

Kacperczyk, M., Sialm, C. & Zheng, L. (2005).On the industry concentration of actively managed equity mutual funds.The Journal of Finance, 60(4), 19832011.

Karmakar, P., Dutta, P., & Biswas, S. (2018). Assessment of mutual fund performance using distance based multi-criteria decision making techniques-An Indian perspective. Research Bulletin, 44(1), 17-38.

Kooli, M., Morin, F., & Sedzro, K. (2005).Evaluation des mesures de performance des hedge funds’, Communication at International Conference of the French Association of Finance, June, Paris, France.

Kundu, A. (2009). Stock selection performance of mutual fund managers in India: an empirical study. Journal of Business and Economic Issues, 1(1), 6973.

Lau, A. H. L., Lau, H. S., & Wingender, J. R. (1990). The distribution of stock returns: New evidence against the stable model. Journal of Business & Economic Statistics, 8(2), 217-223.

Lin, J. J., Chang, C. H., & Chiang, M. C. (2007). A comparison of usual indices and extended TOPSIS Methods in mutual funds’ performance evaluation. Journal of Statistics & Management Systems 10(6), 869883.

Markowitz, H. (1952). Portfolio selection. The Journal of Finance, 7(1), 77-91.

Markowitz, H. M. (1959). Portfolio selection: Efficient diversification of investment. John Wiley & Sons, New York.

McMullen, P. R., & Strong, R. A. (1998). Selection of mutual funds using data envelopment analysis. Journal of Business and Economic Studies, 4(1), 1–12.

Morey, M. R., & Morey, R. C. (1999). Mutual fund performance appraisals: a multi-horizon perspective with endogenous benchmarking. Omega, 27(2), 241–258.

Murthi, B. P. S., & Choi, Y. K. (2001). Relative performance evaluation of mutual funds: A non-parametric approach. Journal of Business Finance and Accounting, 28, 853–876.

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.

Nguyen-Thi-Thanh, H. (2006). On the Use of Data Envelopment Analysis in Hedge Fund Selection, Working Paper, Universitéd’ Orléans. http://repec.org/mmf2006/up.18346.1145733238.pdf (Accessed on 10th July, 2018).

Pamučar, D., & Ćirović, G. (2015). The selection of transport and handling resources in logistics centers using Multi-Attributive Border Approximation area Comparison (MABAC). Expert Systems with Applications, 42(6), 3016-3028.

Pedersen, C. S., & RudholmAlfvin, T. (2003). Selecting riskadjusted shareholder performance measure. Journal of Asset Management, 4(3), 152172.

Pendaraki, K., & Zopounidis, C. (2003). Evaluation of equity mutual funds’ performance using a multicriteria methodology. Operational Research, 3(1), 69-90.

Pendaraki, K., Doumpos, M., & Zopounidis, C. (2004). Towards a goal programming methodology for constructing equity mutual fund portfolios. Journal of Asset Management, 4(6), 415–428.

Pendaraki, K., Zopounidis, C., & Doumpos, M. (2005). On the construction of mutual fund portfolios: A multicriteria methodology and an application to the Greek market of equity mutual funds. European Journal of Operational Research, 163(2), 462481.

Plantinga, A., & de Groot. D. (2002). Riskadjusted performance measures and implied risk attitudes. Journal of Performance Measurement, 6, 922.

Redman, A. L., Gullett, N. S., & Manakyan, H. (2000). The performance of global and international mutual funds”, Journal of Financial and Strategic Decisions, 13(1), 7585.

Roy, J., Chatterjee, K., Bandyopadhyay, A., & Kar, S. (2018). Evaluation and selection of medical tourism sites: A rough analytic hierarchy process based multi‐attributive border approximation area comparison approach. Expert Systems, 35(1), e12232.

Roy, J., Ranjan, A., Debnath, A., & Kar, S. (2016). An extended MABAC for multi-attribute decision making using trapezoidal interval type-2 fuzzy numbers.arXiv preprint arXiv:1607.01254.

Scott, R. C., & Horvath, P. A. (1980). On the direction of preference for moments of higher order than the variance. Journal of Finance, 35, 915-919.

Sehgal, S., & Jhanwar, N. (2008). On stock selection skills and market timing abilities of mutual fund managers in India. International Research Journal of Finance and Economics, 15, 307317.

Sengupta, J. (2003). Efficiency tests for mutual fund portfolios. Applied Financial Economics, 13, 869–876.

Shannon, C. E. (1948). The mathematical theory of communication.Bell System Technical Journal, 27, 379423.

Sharma, H. K., Roy, J., Kar, S., & Prentkovskis, O. (2018). Multi Criteria Evaluation Framework for Prioritizing Indian Railway Stations Using Modified Rough AHP-MABAC Method. Transport and Telecommunication Journal, 19(2), 113-127.

Sharma, H. P., & Sharma, D. K. (2006). A multiobjectivedecisionmaking approach for mutual fund portfolio. International Business & Economics Research Journal, 4, 13–24.

Sharpe, W. F. (1966). Mutual fund performance.Journal of Business, 39, 119138.

Sielska, A. (2010). Multicriteria rankings of open-end investment funds and their stability.Operations research and decisions, 1(20), 112-129.

Tarim, S. A., & Karan, M. B. (2001). Investment fund performance measurement using weightrestricted data envelopment analysis: an application to the turkish capital market. Russian and East European Finance and Trade, 37(5), 64–84.

Tobin, J. (1958). Liquidity preference as behavior towards risk.Review of Economic Studies, 25(1), 6586.

Treynor, J. (1965). How to rate management of investment funds. Harvard Business Review 43, 63–75.

Tripathy, N. P. (2004). An empirical analysis on performance evaluation of mutual funds in India: A study on equity linked saving schemes. The IUP Journal of Applied Finance, 10(7), 307317.

Tsolas, I. (2011). Natural resources exchange traded funds: performance appraisal using DEA modeling’, The Business and Economics Research Journal, 4(2), 250–259.

Vesković, S., Stević, Ž., Stojić, G., Vasiljević, M., & Milinković, S. (2018). Evaluation of the railway management model by using a new integrated model DELPHI-SWARA-MABAC. Decision Making: Applications in Management and Engineering, 1(2), 34-50.

Wilkens, K., & Zhu, J. (2001). Portfolio evaluation and benchmark selection: a mathematical programming approach. The Journal of Alternative Investments, 4(1), 9–19.

Yu, S. M., Wang, J., & Wang, J. Q. (2017). An interval type-2 fuzzy likelihood-based MABAC approach and its application in selecting hotels on a tourism website. International Journal of Fuzzy Systems, 19(1), 47-61.

Zeng, Q. L., Li, D. D., & Yang, Y. B. (2013). VIKOR method with enhanced accuracy for multiple criteria decision making in healthcare management. Journal of Medical System, 37, 1–9.

Zhao, X., Wang, S., & Lai, K. K. (2011). Mutual funds performance evaluation based on endogenous benchmarks. Expert Systems with Applications, 38 (4), 3663–3670.