| تعداد نشریات | 60 |
| تعداد شمارهها | 2,089 |
| تعداد مقالات | 16,801 |
| تعداد مشاهده مقاله | 46,029,823 |
| تعداد دریافت فایل اصل مقاله | 25,775,180 |
Network centrality and portfolio optimization using the genetic algorithm | ||
| Journal of Mathematics and Modeling in Finance | ||
| دوره 1، شماره 2، اسفند 2021، صفحه 113-139 اصل مقاله (1.55 M) | ||
| نوع مقاله: Research Article | ||
| شناسه دیجیتال (DOI): 10.22054/jmmf.2021.13844 | ||
| نویسندگان | ||
| Asghar Abolhasani Hastiany1؛ Alireza Zamanpour* 2 | ||
| 1Economic Department , Payame Noor University , central Organization , Tehran , Iran | ||
| 2Financial Engineering Department, Islamic Azad University, Islamshar Branch, Tehran, Iran | ||
| چکیده | ||
| This study aims to optimize the portfolio using the genetic operator and network centralization. The statistical population of the study is the top 50 companies of Tehran Stock Exchange, in the first quarter of 2021, and to calculate the size of centrality, we used the difference in the overall performance of each company compared to all the top companies, based on a standard hybridization indicator. Then based on the companies’ performance in the capital market, the geometric mean of risk and return of efficient companies are determined, and given the real limitations of the budget, the requirements and expectations of the investors compared to the market’s performance and the risk-free investment, the problem of decision-making for the composition of the investment in the form of a multi-purpose paradigm is formulated. By using the modified optimization algorithm and the genetic algorithm with dual operators, we optimized the investment’s composition. Finally, we use the compound linear regression with data analysis approach to evaluate the effect of individual and systemic operators on determining the investment strategy, and the results represented the positive effect of these two operators. | ||
| کلیدواژهها | ||
| Portfolio optimization؛ Network centralization؛ Genetic algorithm؛ Risk؛ Return volatility | ||
| مراجع | ||
|
[1] Y. Amihud, Illiquidity and stock returns: cross-section and timeseries effects, Journal of Financial Markets, 5 (2020), 31-56. [2] Z. Dai, H. Zhu, F. Wen, Two nonparametric approaches to mean absolute deviation portfolio selection model, Journal of Industrial Management Optimization, 16(5) (2020), 2283. [3] V. DeMiguel, Y. Plyakha, R. Uppal, G. Vilkov, Improving portfolio selection using option-implied volatility and skewness, Journal of Financial and Quantitative Analysis, (2013), 1813-1845. [4] E. F. Fama, A review of theory and empirical work, The journal of Finance, 25(2) (1970), 383-417. [5] E. F. Fama, K. R. French, Multifactor explanations of asset pricing anomalies, The journal of nance, 51(1) (1996), 55-84. [6] R. Gopalan, O. Kadan, M. Pevzner, Managerial decisions, asset liquidity, and stock liquidity, Asset Liquidity, and Stock Liquidity, (2009). [7] B. Han, H. Y. Wong, MeanVariance Portfolio Selection Under Volterra Heston Model, Applied Mathematics Optimization, (2020), 1-28. [8] C. Iorio, G. Frasso, A. D'Ambrosio, R. Siciliano, A P-spline based clustering approach for portfolio selection, Expert Systems with Applications, 95 (2018), 88-103. [9] B. Li, Y. Zhu, Y. Sun, G. Aw, K. L. Teo, Multi-period portfolio selection problem under uncertain environment with bankruptcy constraint, Applied Mathematical Modelling, 56 (2018), 539-550. [10] J. Lintner, Distribution of incomes of corporations among dividends, retained earnings, and taxes, The American economic review, 46(2) (1956), 97-113. [11] J. Ma, J. D. Harstvedt, R. Jaradat, B. Smith, Sustainability driven multicriteria project portfolio selection under uncertain decision-making environment, Computers Industrial Engineering, 140 (2020), 106236. [12] N. Mansour, M. S. Cherif, W. Abdelfattah, Multi-objective imprecise programming for nancial portfolio selection with fuzzy returns, Expert Systems with Applications, 138 (2019), 112810. [13] H. Markowitz, The utility of wealth, Journal of political Economy, 60(2) (1952), 151-158. [14] J. A. Ohlson, Earnings, book values, and dividends in equity valuation, Con temporary accounting research, 11(2) (1995), 661-687. [15] G. Peralta, A. Zareei, A network approach to portfolio selection, Journal of Empirical Finance, 38 (2016), 157-180. [16] J. R. Ross, Constraints on variables in syntax, (1967). [17] W. F. Sharpe, A theory of market equilibrium under conditions of risk, The journal of nance, 19(3) (1964), 425-442. [18] Y. Zhang, P. Zhao, B. Li, Q. Wu, J. Huang, M. Tan, Cost-sensitive portfolio selection via deep reinforcement learning, IEEE Transactions on Knowledge and Data Engineering, (2020). [19] X. Zhong, D. Enke, Forecasting daily stock market return using dimensionality reduction, Expert Systems with Applications, 67 (2017), 126-139. | ||
|
آمار تعداد مشاهده مقاله: 501 تعداد دریافت فایل اصل مقاله: 527 |
||