پیوندهای مفید
آمار
| تعداد نشریات | 21 |
| تعداد شماره‌ها | 653 |
| تعداد مقالات | 9,565 |
| تعداد مشاهده مقاله | 68,474,464 |
| تعداد دریافت فایل اصل مقاله | 47,931,752 |
Evaluation and comparison of portfolio optimization with the degree of stock risk adjustment based on the performance measurement model based on the hybrid metaheuristic algorithm and gray wolf optimization algorithm | ||
| International Journal of Nonlinear Analysis and Applications | ||
| مقاله 6، دوره 15، شماره 6، شهریور 2024، صفحه 63-70 اصل مقاله (356.86 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2023.29965.4307 | ||
| نویسندگان | ||
| Amir Mosazadeh1؛ Javad Ramezani* 1؛ Mona Aliakbari2؛ Mehdi Safari Geraiely3؛ Ramezan Rezaeian4 | ||
| 1Department of Accounting, Nour Branch, Islamic Azad University, Nour, Iran | ||
| 2Department of Accounting, Noushahr Branch, Islamic Azad University, Noushahr, Iran | ||
| 3Department of Accounting, Bandargaz Branch, Islamic Azad University, Bandargaz, Iran | ||
| 4Department of Mathematics and Statistics, Nour Branch, Islamic Azad University, Nour, Iran | ||
| تاریخ دریافت: 26 آبان 1401، تاریخ بازنگری: 02 اسفند 1401، تاریخ پذیرش: 08 اسفند 1401 | ||
| چکیده | ||
| The investment portfolio optimization process including allocation of assets allocated capital percentage to each asset, risk management, and creating a new portfolio with a certain level of risk and return based on investors' expectations has always been an attractive and controversial issue in the field of financial decision making. The objective of this research is to evaluate and compare portfolio optimization with the degree of stock risk adjustment based on the performance measurement model based on the hybrid metaheuristic algorithm and gray wolf optimization algorithm. The statistical population of this research is the research statistical population which is all the listed companies in Tehran Stock Exchange for 7 years from 2014 to 2020. Based on the limitations imposed on the statistical population, the active companies in Tehran Stock Exchange have been investigated as the research sample. The obtained results from the tests show that a hybrid metaheuristic algorithm improves the adjusted risk. | ||
| کلیدواژه‌ها | ||
| portfolio optimization؛ degree of stock risk adjustment؛ performance measurement model؛ hybrid metaheuristic algorithm؛ gray wolf optimization algorithm | ||
| مراجع | ||
|
[1] N. Abdi, M. Moradzadeh Fard, H. Ahmadzadeh, and M. Khoddam, A hybrid model for portfolio optimization based on stock price forecasting with LSTM recurrent neural network using cardinality constraints and multicriteria decision making methods (Case study of Tehran Stock Exchange), J. Financ. Manag.t Perspect. 11 (2021), no. 36, 119–143. [2] S. Davoodi and A. Sadri, Comparing meta-heuristic algorithms on optimal model of multi-period portfolio based on the value at risk, J. Secur. Exchange 11 (2018), no. 41, 121–152. [3] K. Dowd, Money and the Nation State: The Financial Revolution, Government and the World Monetary System, Routledge, 2020. [4] L. Dymova, K. Kaczmarek, and P. Sevastjanov, A new approach to the bi-criteria multi-period fuzzy portfolio selection, Knowledge-Based Syst. 234 (2021), 107582. [5] M.F. Fallahshams, A. Abdollahi, and M. Moghaddassi, Examining the performance of different risk criteria in portfolio selection and optimization, using the ant colony algorithm in companies Listed at the Tehran Stock Exchange, J. Financ. Manag. Strategy 1 (2013), no. 2, 22–39. [6] N. Geraviyan, Stable optimization and simulation of multi-period stock portfolio, Master Thesis, Amirkabir University of Technology, Tehran, Iran, 2007. [7] T. Gholizadehsalteh, M. Eghbalnia, and M.E. Aghababaei, Grey wolf optimization evolving kernel extreme learning machine: Application to bankruptcy prediction, Financ. Res. J. 21 (2019), no. 2, 187–212. [8] S. Guo, L. Yu, X. Li, and S. Kar, Fuzzy multi-period portfolio selection with different investment horizons, Eur. J. Oper. Res. 254 (2016), no. 3, 1026–1035. [9] S. Homaeifar and E. Roghanian, The application of robust optimization and goal programming in multi-period portfolio selection problem, Financ. Engin. Portfolio Manag. 7 (2016), no. 28, 153–167. [10] J. Jablonsky, Efficiency analysis in multi-period systems: An application to performance evaluation in Czech higher education, Central Eur. J. Oper. Res. 24 (2016), 283–296. [11] H. Jalota, P.K. Mandal, M. Thakur, and G. Mittal, A novel approach to incorporate investor’s preference in fuzzy multi-objective portfolio selection problem using credibility measure, Expert Syst. Appl. 212 (2023), 118583. [12] A.A. Najafi and S. Moushekhian, Modeling and providing the optimal solution for optimization, Financ. Engin. Portfolio Manag. 5 (2014), no. 21, 13–35. [13] P. Pandey, Research Methodology Tools and Techniques, Bridge Center, 2015. [14] F. Rahnamay Rudposhti and Y. Mirabbasi, Modified standard risk assessment based on optimal capacity investment decisions and portfolio optimization (Infrastructure speculation and new financial instrument), Islamic Finance Res. 2 (2013), no. 2, 87–122. [15] H. Sadeghi and S. Behboodi, Using extreme value theory to estimate value at risk (Case study: Foreign exchange rate), J. Asset Manag. Financ. 4 (2016), no. 2, 77–94. [16] W. Yan, R. Miao, and S. Li, Multi-period semi-variance portfolio selection: Model and numerical solution, Appl. Math. Comput. 194 (2007), no. 1, 128–134. [17] W.G. Zhang, Y.J. Liu, and W.J. Xu, A possibilistic mean-semivariance-entropy model for multi-period portfolio selection with transaction costs, Eur. J. Oper. Res. 222 (2012), no. 2, 341–349. [18] G. Zomorodian, F. Hanifi, and B. Mahboubi, The impact of financial and money market developments on foreign direct investment in Iran, J. Invest. Knowledge 7 (2018), no. 25, 223–244. | ||
|
آمار تعداد مشاهده مقاله: 18,747 تعداد دریافت فایل اصل مقاله: 11,045 |
||