Welcome to Francis Academic Press

Academic Journal of Computing & Information Science, 2023, 6(10); doi: 10.25236/AJCIS.2023.061013.

Portfolio Optimization Based on Complex Networks and Genetic Algorithms


Bo Liu

Corresponding Author:
Bo Liu

School of Mathematics, Jilin University, Changchun, 130012, China


Portfolio optimization is a crucial endeavor in finance which aims to effectively manage investment risks and maximize returns. This paper explores the application of complex networks and genetic algorithms as a solution to the challenges associated with portfolio optimization. This paper strives to optimize the composition of portfolios, mitigate risks, and enhances potential returns by analyzing the interdependencies and correlations among financial assets using complex networks and utilizing genetic algorithms as an optimization technique. The results demonstrate that the portfolio resulting from the optimization of genetic algorithms applied to complex networks exhibits remarkable risk control capabilities. This integrated approach effectively minimizes risks associated with investments, contributing to the creation of a more stable and resilient portfolio, particularly in volatile financial markets.


Portfolio Optimization, Complex Network, Genetic Algorithm, Risk Control

Cite This Paper

Bo Liu. Portfolio Optimization Based on Complex Networks and Genetic Algorithms. Academic Journal of Computing & Information Science (2023), Vol. 6, Issue 10: 85-92. https://doi.org/10.25236/AJCIS.2023.061013.


[1] Markowitz, H. (1952). Portfolio Selection. Journal of Finance 7(1): 77-91.

[2] Sharpe, W. F. (1964). Capital-Asset Prices - A Theory of Market Equilibrium under Conditions of Risk. Journal of Finance 19(3): 425-442.

[3] Lintner, J. (1965). The Valuation of Risk Assets and the Selection of Risky Investments in Stock Portfolios And Capital Budgets. Review of Economics and Statistics 47(1): 13-37.

[4] Pontes, L. S. D. and L. C. Rego (2022). Impact of macroeconomic variables on the topological structure of the Brazilian stock market: A complex network approach. Physica a-Statistical Mechanics and Its Applications 604: 14.

[5] Zhou, Y., et al. (2023). Analysing and forecasting co-movement between innovative and traditional financial assets based on complex network and machine learning. Research in International Business and Finance 64.

[6] Hu, S. Y., et al. (2019). An analysis of the clustering effect of a jump risk complex network in the Chinese stock market. Physica a-Statistical Mechanics and Its Applications 523: 622-630.

[7] Liu, C. and N. Arunkumar (2019). Risk prediction and evaluation of transnational transmission of financial crisis based on complex network. Cluster Computing-the Journal of Networks Software Tools and Applications 22(2): S4307-S4313.

[8] Samal, A., et al. (2021). Network geometry and market instability. Royal Society Open Science 8(2).

[9] Bonanno, G., et al. (2003). Topology of correlation-based minimal spanning trees in real and model markets. Physical Review E 68(4).

[10] Li, Y., et al. (2019). Portfolio optimization based on network topology. Physica a-Statistical Mechanics and Its Applications 515: 671-681.

[11] Clemente, G. P., et al. (2021). Asset allocation: new evidence through network approaches. Annals of Operations Research 299(1-2): 61-80.

[12] Zhang, P. M. (2022). Research on Securities Portfolio Model Based on Genetic Optimization Neural Network. Security and Communication Networks 2022: 10.

[13] Zhang, Q. and M. Z. Li (2022). A betweenness structural entropy of complex networks. Chaos Solitons & Fractals 161.