Newcomers' Priorities in Portfolio Selection: A Shannon Entropy Approach


1 Department of Industrial Engineering, University of Science and Technology of Mazandaran, Behshahr, Iran.

2 Faculty of Economics and Administrative Sciences, University of Mazandaran, Babolsar, Iran.

3 Department of Industrial Engineering, Babol Noshirvani University of Technology, Babol, Iran.


Having a good stock portfolio, which is one of the most important factors in making money in the stock market, requires the correct choice of criteria. This issue for new stock traders in the Tehran Stock Exchange (TSE) who do more than 50 percent of daily transactions in this market, due to their lack of sufficient experience, seems thoroughly essential. As a result, newcomers who were trading in the Tehran Stock Exchange in 2020 have been invited to participate in this study. After identifying the most influential variables in portfolio selection via the Delphi method, these factors have been ranked based on Shannon’s Entropy Approach. The results show that Familiarity, Net Profit Ratio, and Stock Price are respectively the main priorities of new entrants in choosing the stock portfolio. Besides, risk-related variables have generally the least importance in stock portfolio selection from the perspective of new entrants.


Abdelaziz, F. B., Aouni, B., & El Fayedh, R. (2007). Multi-Objective Stochastic Programming for Portfolio Selection. European Journal of Operational Research, 177(3), 1811-1823.
Dalkey, N., & Helmer, O. (1963). An Experimental Application of the DELPHI Method to the Use of Experts. Management Science, 9(3), 458–467.
Elfadil, A. M., Ibrahim, E. A., Riyadh, M., & Hussain, H. (2021). Impact of Corporate Performance on Stock Price Predictions in the UAE Markets: Neuro-Fuzzy Model. Intelligent Systems in Accounting, Finance and Management, 28(1), 52-71.
Fattahi, H., Arab Salehi, M., & Ismaili, M. (2019). Selection of Optimal Stock Portfolios Using Accounting Information, Value-Based Information and Balanced Scorecard Information. Journal of Accounting Advances, 11(2), 285-320.
Gold, S. C., & Lebowitz, P. (1999). Computerized Stock Screening Rules for Portfolio Selection. Financial Services Review, 8(2), 61-70.
Gong, X., Yu, C., Min, L., & Ge, Z. (2021). Regret Theory-Based Fuzzy Multi-Objective Portfolio Selection Model Involving DEA Cross-Efficiency and Higher Moments. Applied Soft Computing, 100(1), 1-20.
Hacioglu, Ü., DincerIs, H., & Çelik, E. (2013). The Evaluation of Financial Risk and Portfolio Selection. Managerial Issues in Finance and Banking (111-120). In U. Hacioglu and H. Dincer (Ed.), Managerial Issues in Finance and Banking: A Strategic Approach to Competitiveness. Berlin: Springer.
Hurson, C., & Ricci-Xella, N. (2002). Structuring Portfolio Selection Criteria for Interactive Decision Support. European Research Studies Journal, 5(1), 69-94.
Janani, M. H., Ehsanifar, M., & Bakhtiarnezhad, S. (2012). Selection of Portfolio by Using Multi Attributed Decision. Making (Tehran Stock Exchange). American Journal of Scientific Research, 44, 15-29.
Kamwaro, E. K. (2013). The Impact of Investment Portfolio Choice on Financial Performance of Investment Companies in Kenya (Master's Thesis, University of Nairobi, Kenya), Retrieved from
Kheradyar, S., Ibrahim, I., & Mat Nor, F. (2011). Stock Return Predictability with Financial Ratios. International Journal of Trade, Economics and Finance, 2(5), 391-396.
Kou, G., Ergu, D., Lin, C., & Chen, Y. (2016). Pairwise Comparison Matrix in Multiple Criteria Decision Making. Technological and Economic Development of Economy, 22(5), 738-765.
Li, B., & Hoi, S. C. (2012). Online Portfolio Selection: A Survey. ACM Computing Surveys, 46(3), 1-33.
Li, T., Zhang, W., & Xu, W. (2015). A Fuzzy Portfolio Selection Model with Background Risk. Applied Mathematics and Computation, 256(1), 505-513.
Liu, Y. -J., & Zhang, W. -G. (2017). Fuzzy Portfolio Selection Model with Real Features and Different Decision Behaviours. Fuzzy Optimization and Decision Making, 17(3), 317-336.
Markowitz, H. (1952). Portfolio Selection. The Journal of Finance, 7(1), 77-91.
Mercurio, P. J., Wu, Y., & Xie, H. (2020). An Entropy-Based Approach to Portfolio Optimization. Entropy, 22(3), Retrieved from
Salimi Rostami, S. R., & Jafari Samimi, A. (2020). Evaluating the Impact of Psychological Factors on Newcomers to the Tehran Stock Exchange through Machine Learning Approach. Third Conference on Industrial Engineering, Economics and Management, Valencia: Elsevier.
Shannon, C. E. (1948). A Mathematical Theory of Communication. Bell Labs Technical Journal, 27(3), 379-423.
Shen, D., Li, X., Teglio, A., & Zhang, W. (2016). The Impact of Information-Based Familiarity on the Stock Market. Working Paper, 2016/08, 1-31.
Simonelli, M. R. (2005). Indeterminacy in Portfolio Selection. European Journal of Operational Research, 163(1), 170-176.
Squyres, J. (1998). A Quick Peek According to Graham and Dodd. Journal of Financial Statement Analysis, 4(1), 79-83.
Suvitsakdanont, P. (2000). Factors Related to Individual Investors Stock Investment Decisions: a Cross-Cultural Comparative Study of American and Thai Investors (Doctoral Dissertation, United States International University, Kenya). Retrieved from
Tiryaki, F., & Ahlatcioglu, B. (2009). Fuzzy Portfolio Selection Using Fuzzy Analytic Hierarchy Process. Information Sciences, 179(1), 53-69.
Tobin, J. (1958). Liquidity Preference as Behaviour towards Risk. The Review of Economic Studies, 25(2), 65-86.
Wang, Z., & Yu, Y. (2011). Information Entropy Method for Project Portfolio Selection. Eighth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), Retrieved from
Zhai, J., & Ba, M. (2017). Uncertain Portfolio Selection with Background Risk and Liquidity Constraints. Mathematical Problem in Engineering, Retrieved from
Zheng, X. -h., Zhang, Q., & Luo, M. (2000). The Application of Entropy-Weight Coefficient Method to Risk Decision. Retrieved from