1
Associate Professor of Accounting, Faculty of Economics, Administrative Sciences and Management, Semnan University
2
Ph.D candidate in Finance, Faculty of Economics, Administrative Sciences and Management, Semnan University
10.22034/iaar.2024.206119
Abstract
The optimizing the investment portfolio is considered one of the most important topics in capital management. Our goal in this article is to design an optimal portfolio selection model based on the Minimum Spanning Tree method in the Iranian stock market. Designing and compiling a portfolio selection model includes two It is the basic stage. The first stage of choosing the investment portfolio was done using five criteria of centrality, betweenness, distance from the center, distance from correlation and distance from the distance criterion. The result of this work is the formation of two central and peripheral portfolios, respectively. It was the central portfolio and peripheral portfolio the network. In the second step, using risk and return measurement criteria, selected portfolios were optimized and risk managed. At the end, the extracted portfolios were evaluated with the total index and one share of the portfolio for a period of 200 days. The results showed that both portfolios had higher efficiency according to the market conditions. As expected, during the growth of the market, the surrounding portfolio recorded a higher return compared to the market.
Barbi A., Prataviera G., (2019), “Nonlinear dependencies on brazilian equity network from mutual information minimum spanning trees”, Physica A: Statistical Mechanics and its Applications, 523,876-885.
Birch J., Athanasios A. Pantelous, and Konstantin Zueva, (2015), “The Maximum Number of 3- and 4-Cliques within a Planar Maximally Filtered Graph”, Physica A: Statistical Mechanics and its Applications Volume 417, 1 January 2015, Pages 221-229
Birch Jenna Louisa,( 2015), “Modelling Financial Markets using Methods from Network Theory”, Thesis submitted in accordance with the requirements of the University of Liverpool for the degree of Doctor in Philosophy,
Eom C. , Oh G. , Kim S. , (2008), “Statistical investigation on connected structures of stock networks in a financial time series”, J. Korean Phys. Soc. 53, 3837–3841
Goh YK, Hasim HM, Antonopoulos CG (2018) “Inference of financial networks using the normalised mutual information rate”. PLoS ONE 13(2)
Guresen, E., Kayakutlu, G., and Daim, T.U. (2011) “Using artificial neural network models in stock market index prediction”. Expert Systems with Applications., 38(8), pp. 10389-10397.
Hafizah Bahaludin1, Mimi Hafizah Abdullah1, Lam Weng Siew, Lam Weng Hoe,(2019), “The Investigation on the Impact of Financial Crisis on Bursa Malaysia Using Minimal Spanning Tree”, Mathematics and Statistics Vol. 7(4A), pp. 1 - 8
Hartman D. , Hlinka J. , (2018), “Nonlinearity in stock networks”, Chaos: An Interdisciplinary Journal of Nonlinear Science,28
Jain, A. K. (2010), “Data Clustering: 50 Years Beyond K-Means”, Pattern Recognition Letters, 31, (8), 651-666
Kenett, D., Tumminello, M., Madi, A., Gur-Gershgoren, G., Mantegna, R. and Ben-Jacob, E., (2010), “Dominating clasp of the financial sector revealed by partial correlation analysis of the stock market”. PLoS One, 5
Mantegna, R.N., (1999), “Hierarchical structure in financial markets”. Eur. Phys. J. B, 11, 193–197
Markowitz, H., (1952), “Portfolio selection”. J. Finance, 7, 77–91
Marti G. , (2020), “Corrgan: Sampling realistic financial correlation matrices using generative adversarial networks”, Economics, Mathematics, Computer Science,
Massara G. P. , Di Matteo T. , Aste T. , (2017) , “Network filtering for big data: triangulated maximally filtered graph”, Journal of complex Networks, 5 161–178.
Musciotto F., Marotta L., Miccichè S., Mantegna R. N. (2018). "Bootstrap validation of links of a minimum spanning tree". Phys. A Stat. Mech. Appl. 512 1032–1043
Nanda, S., R., Mahanty, B. & Tiwari, M., K., (2010), “Clustering Indian stock market data for portfolio management”, Expert Systems with Applications, 37, 8793–8798
Simon, H. A. (1956). “Rational choice and the structure of the environment”. Psychological Review, 63(2), 129–138
Tumminello, M., Aste, T., Di Matteo, T. and Mantegna, R.N., (2005), “A tool for filtering information in complex systems”. Proc. Natl. Acad. Sci, 102 (30) 10421-10426
Tumminello, M., Lillo, F. and Mantegna, R.N., (2010), “Correlation, hierarchies, and networks in financial markets”. J. Econ. Behave. Org., 75, 40–58
Tumminello M. , Matteo T. Di , Aste T. , and Mantegna, R.N. , (2007), “Correlation based networks of equity returns sampled at different time horizons”, Eur. Phys. J. B, 55, 209–217
Zhi-Qiang Jiang, Wei-Xing Zhou, (2010), “Complex stock trading network among investors”, Physica A, 389 ,4929_4941
Kazem Ebrahimi,S. and Rajabi,H. R. (2024). A Model for Optimization and Portfolio Risk Management Using Financial Network Theory in the Iranian Stock Market. Accounting and Auditing Research, 16(62), 181-202. doi: 10.22034/iaar.2024.206119
MLA
Kazem Ebrahimi,S. , and Rajabi,H. R. . "A Model for Optimization and Portfolio Risk Management Using Financial Network Theory in the Iranian Stock Market", Accounting and Auditing Research, 16, 62, 2024, 181-202. doi: 10.22034/iaar.2024.206119
HARVARD
Kazem Ebrahimi S., Rajabi H. R. (2024). 'A Model for Optimization and Portfolio Risk Management Using Financial Network Theory in the Iranian Stock Market', Accounting and Auditing Research, 16(62), pp. 181-202. doi: 10.22034/iaar.2024.206119
CHICAGO
S. Kazem Ebrahimi and H. R. Rajabi, "A Model for Optimization and Portfolio Risk Management Using Financial Network Theory in the Iranian Stock Market," Accounting and Auditing Research, 16 62 (2024): 181-202, doi: 10.22034/iaar.2024.206119
VANCOUVER
Kazem Ebrahimi S., Rajabi H. R. A Model for Optimization and Portfolio Risk Management Using Financial Network Theory in the Iranian Stock Market. Accounting and Auditing Research, 2024; 16(62): 181-202. doi: 10.22034/iaar.2024.206119