The Fuzzy Mean-Entropy Portfolio Model : Sensitivity Analysis, Transaction Costs Based on Credibility Theory

Subject Areas : Journal of Investment Knowledge

Mahmoud Lari Dashtbayaz ¹ (Assistant profesor of accounting, Ferdowsi University of Mashhad, Mashhad, Iran)
Shaban Mohammadi ² (MSc. Department of Accounting- Hakim Nezami institution of higher education at Quchan , Iran)
Nader Naghshbandi ³ (Associate profesor of Accounting, Hakim Nezami institution of higher education at Quchan, Iran)

Received: 2017-09-23 Accepted : 2018-03-13 Published : 2019-03-21

Keywords: Sensitivity analysis, Entropy, transaction costs, fuzzy,

Abstract :

The purpose of this study is to investigate the stock portfolio model based on the average entropy in a fuzzy environment with transaction costs based on the theory of credit for 10 stocks in Tehran Stock Exchange in 1396.The present study is not based on average-entropy based models but on the sensitivity analysis of the target function coefficients and the limiting coefficients, especially in maximizing the recursive model and the minimum risk model. Entropy and sensitivity analysis were used to measure the risk and the coefficients of the objective function and the limitations. The results show that when the coefficients change in the range of values, either the optimized answer or the fixed values of the objective function are obtained. The research results help investors to be more confident in their choices.  

References:

*       بهزادی، عادل؛ بختیاری، مصطفی(1395). ارائه مدلی بر مبنای میانگین– آنتروپی– چولگی برای بهینه سازی  سبد سهام در محیط فازی، مجله مهندسی مالی و مدیریت اوراق بهادار،شماره نوزدهم،صص39-55.

*       آقایی، محمد علی؛ سپاسی، سحر؛ کاظم‌پور، مرتضی.(1395). بررسی جامع روابط درونی ساختار سرمایه، جریان وجه نقد آزاد، انتروپی تنوع‌پذیری‌ محصولات و عملکرد (شرکت‌های پذیرفته شده در بورس اوراق بهادار تهران)،فصلنامه دانش سرمایه گذاری، دوره 5، شماره 20، صص 223-242.

*       Markowitz H,)1952(, Portfolio selection. J. Financ. 7, 77–91.

*       *  Markowitz, H,(1959), Portfolio Selection: Efficient Diversification of Investment.       Wiley, New York.

*       Markowitz, H.: Mean-Variance Analysis in Portfolio Choice and Capital Markets. Basil Blackwell, Oxford (1987).

*       Best J., Hlouskova J.,)2000(, The efficient frontier for bounded assets. Math. Methods Oper. Res. 52, 195–212.

*       Merton R.,)1972(, An analytic derivation of the efficient frontier. J. Financ. Quantit. Anal. 9, 1851–1872.

*       Pang J.,)1980(, A new efficient algorithm for a class of portfolio selection problems. Oper. Res. Int. J. 28, 754–767.

*       Perold, A.F.: Large-scale portfolio optimization. Manag. Sci. 30, 1143–1160.

*       Sharpe W.,)1970(, Portfolio Theory and Capital Markets. McGrawHill, New York.

*       Stein M., Branke J., Schmeck H.,)2008(, Efficient implementation of an active set algorithm for large-scale portfolio selection. Comput. Oper. 35, 3945–3961.

*       Anagnostopoulos K., Mamanis G.,)2011(,The mean-variance cardinality constrained portfolio optimization problem: an experimental evaluation of five multiobjective evolutionary algorithms. Expert Syst. 38, 14208–14217.

*       Liu B.,)2010(, Uncertainty Theory, 3rd edn. Spring-Verlag, Berlin.

*       Liu B., 2006, A survey of credibility theory. Fuzzy Optim. Decis. 5, 387–408.

*       Liu B., Iwamura K., 1998, Chance constrained programming with fuzzy parameters. Fuzzy Sets Syst. 94, 227–237.

*       Amiri M., Ekhtiari M., Yazdani M., 2011, Nadir compromise programming: a model for optimization of multi-objective portfolio problem. Experts Syst. Appl. 38, 7222–7226.

*       Bhattacharyya R., Kar S., Majumder, D., 2011, Fuzzy mean-variance-skewness portfolio selection models by interval analysis. Comput. Math.. 61, 126–137.

*       Dastkhan H., Gharneh N., Golmakani H., 2011, A linguisticbased portfolio selection model using weighted max-min operator and hybrid genetic algorithm. Expert Syst. Appl. 38, 11735–11743.

*       Philippatos G., Wilson C., 1972, Entropy, market risk, and the selection of efficient portfolios. Appl. Econ. 4, 209–220.

*       Huang, X., 2008, Mean-Entropy models for fuzzy portfolio selection. IEEE Trans. Fuzzy Syst. 16, 1096–1101.

*       Huang, X., 2011, Mean-risk model for uncertain portfolio selection. Fuzzy Optim Decis Mak 10, 71–89.

*       Mukesh K.,2016, Credibilistic mean-entropy models for multi-period portfolio selection with multi-choice aspiration levels. Inf. Sci. 345, 9–26.

*       Zhou R., Zhan Y., Cai R., Tong G., 2015, A mean-variance hybrid-entropy model for portfolio selection with fuzzy returns. Entropy 17, 3319–3331.

*       Zhang W., Zhang X., Chen Y.,2011, Portfolio adjusting optimization with added assets and transaction costs based on credibility measures. Insur. Math. Econ 49, 353–360.

*       Sadjadi S., Seyedhosseini S., Hassanlou, K.,2011, Fuzzy multi period portfolio selection with different rates for borrowing and lending. Appl. Soft Comput. 11, 3821–3826.

*       Li P., Liu, B.,2007, Entropy of credibility distributions for fuzzy variables. IEEE Trans. Fuzzy Syst. 16, 123–129.

*       Liu, S.,2011, The mean-absolute deviation portfolio selection problem with interval-valued returns. J. Comput. Appl. Math. 235, 4149–4157.

*       Liu S.,2011, A fuzzy modeling for fuzzy portfolio optimization. Experts Syst. Appl. 38, 13803–13809.

*       Qin Z., Li X., Li X.,2009, Portfolio selection based on fuzzy cross-entropy. J. Comput. Appl. Math. 228, 139–149.

*       Zhou R., Yang Z., Yu M.,2015, A portfolio optimization model based on information entropy and fuzzy time series. Fuzzy Optim Decis. 14, 381–397.

*       Yue W., Wang Y.,2017, A new fuzzy multi-objective higher order moment portfolio selection model for diversified portfolios. Phys. A 465, 124–140.

*       Chen W., Wang Y., Mehlawat M., A hybrid FA-SA algorithm for fuzzy portfolios selection with transaction costs. doi:10.1007/s9-016-2365-3.

*       Zadeh L.,1978, Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets Syst. 1, 3–28.