A Typology of Financial Networks According to Their Typological Characteristics (A Study of Tehran Stock Exchange)
Subject Areas : Financial engineeringMajid Montasheri 1 , Hojjatollah Sadeqi 2
1 - Department of Accounting and Finance, Faculty of Management . Yazd University, yazd, iran
2 - Department of Finance and Accounting, Faculty of Management , Yazd University, yazd, iran.
Keywords: Minimum Spanning Tree, Financial network, Centrality measures,
Abstract :
The purpose of this study is to establish and introduce a new financial network and to examine centrality measures for optimizing the portfolio of investors as well as identifying stock market leaders. In this study, 100 top stock companies with largest average market capitalization were selected from January 2009 to January 2020. The financial network was converted to logarithmic returns using adjusted closing price. The concepts of graph theory and prim algorithm were used to explore the relationships and distances between stocks to construct a minimum spanning tree. The results showed that based on the degree centrality measure, Iranian telecommunication stocks and Ayandeh Bank, based on closeness centrality measure, Bahman investment stocks, Omid capital financing and tourism bank, based on Betweenness centrality measure, Omid capital financing stocks, Bahman investment and Asia insurance, based on the bottleneck centrality measure, Asian Insurance stocks, Tourism Bank and Omid Capital has the most impact on the financial network and stock market. Finally, the financial network was divided into 9 clusters, each cluster showing the stronger relationship of its components with each other.
منابع
1, Gan, S. L., & Djauhari, M. A. (2015). New York Stock Exchange performance: evidence from the forest of multidimensional minimum spanning trees. Journal of Statistical Mechanics: Theory and Experiment, 2015(12), P12005.
2, Coletti, P. (2016). Comparing minimum spanning trees of the Italian stock market using returns and volumes. Physica A: Statistical Mechanics and its Applications, 463, 246-261.
3, Markowitz, H. (1952). Portfolio selection. The journal of finance, 7(1), 77-91.
4, Fama,E. F., & French, K. R.(1997). Industry costs of equity.Journal of financial economics, 43(2), 153-193.
5, Mantegna, R. N. (1999). Hierarchical structure in financial markets. The European Physical Journal B-Condensed Matter and Complex Systems, 11(1), 193-197.
6, Bonanno, G., Caldarelli, G., Lillo, F., Micciche, S., Vandewalle, N., & Mantegna, R. N. (2004). Networks of equities in financial markets. The European Physical Journal B, 38(2), 363-371.
7, Tumminello, M., Lillo, F., & Mantegna, R. N. (2010). Correlation, hierarchies, and networks in financial markets. Journal of Economic Behavior & Organization, 75(1), 40-58.
8, Graham, R. L., & Hell, P. (1985). On the history of the minimum spanning tree problem. Annals of the History of Computing, 7(1), 43-57.
9, Al-Taie, M. Z., & Kadry, S. (2017). Python for graph and network analysis (pp. 1-184). Cham: Springer International Publishing.
10, Gower, J. C., & Ross, G. J. (1969). Minimum spanning trees and single linkage cluster analysis. Journal of the Royal Statistical Society: Series C (Applied Statistics), 18(1), 54-64.
_||_
منابع
1, Gan, S. L., & Djauhari, M. A. (2015). New York Stock Exchange performance: evidence from the forest of multidimensional minimum spanning trees. Journal of Statistical Mechanics: Theory and Experiment, 2015(12), P12005.
2, Coletti, P. (2016). Comparing minimum spanning trees of the Italian stock market using returns and volumes. Physica A: Statistical Mechanics and its Applications, 463, 246-261.
3, Markowitz, H. (1952). Portfolio selection. The journal of finance, 7(1), 77-91.
4, Fama,E. F., & French, K. R.(1997). Industry costs of equity.Journal of financial economics, 43(2), 153-193.
5, Mantegna, R. N. (1999). Hierarchical structure in financial markets. The European Physical Journal B-Condensed Matter and Complex Systems, 11(1), 193-197.
6, Bonanno, G., Caldarelli, G., Lillo, F., Micciche, S., Vandewalle, N., & Mantegna, R. N. (2004). Networks of equities in financial markets. The European Physical Journal B, 38(2), 363-371.
7, Tumminello, M., Lillo, F., & Mantegna, R. N. (2010). Correlation, hierarchies, and networks in financial markets. Journal of Economic Behavior & Organization, 75(1), 40-58.
8, Graham, R. L., & Hell, P. (1985). On the history of the minimum spanning tree problem. Annals of the History of Computing, 7(1), 43-57.
9, Al-Taie, M. Z., & Kadry, S. (2017). Python for graph and network analysis (pp. 1-184). Cham: Springer International Publishing.
10, Gower, J. C., & Ross, G. J. (1969). Minimum spanning trees and single linkage cluster analysis. Journal of the Royal Statistical Society: Series C (Applied Statistics), 18(1), 54-64.