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Deterministic factors of stock networks based on cross-correlation in financial market

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  • Eom, Cheoljun
  • Oh, Gabjin
  • Kim, Seunghwan

Abstract

The stock market has been known to form homogeneous stock groups with a higher correlation among different stocks according to common economic factors that influence individual stocks. We investigate the role of common economic factors in the market in the formation of stock networks, using the arbitrage pricing model reflecting essential properties of common economic factors. We find that the degree of consistency between real and model stock networks increases as additional common economic factors are incorporated into our model. Furthermore, we find that individual stocks with a large number of links to other stocks in a network are more highly correlated with common economic factors than those with a small number of links. This suggests that common economic factors in the stock market can be understood in terms of deterministic factors.

Suggested Citation

  • Eom, Cheoljun & Oh, Gabjin & Kim, Seunghwan, 2007. "Deterministic factors of stock networks based on cross-correlation in financial market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 383(1), pages 139-146.
    • Handle: RePEc:eee:phsmap:v:383:y:2007:i:1:p:139-146
    DOI: 10.1016/j.physa.2007.04.102
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    Cited by:

    1. Eom, Cheoljun & Jung, Woo-Sung & Kaizoji, Taisei & Kim, Seunghwan, 2009. "Effect of changing data size on eigenvalues in the Korean and Japanese stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(22), pages 4780-4786.
    2. Eom, Cheoljun & Park, Jong Won, 2017. "Effects of common factors on stock correlation networks and portfolio diversification," International Review of Financial Analysis, Elsevier, vol. 49(C), pages 1-11.
    3. Lee, Junghoon & Youn, Janghyuk & Chang, Woojin, 2012. "Intraday volatility and network topological properties in the Korean stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1354-1360.
    4. Gautier Marti & Frank Nielsen & Miko{l}aj Bi'nkowski & Philippe Donnat, 2017. "A review of two decades of correlations, hierarchies, networks and clustering in financial markets," Papers 1703.00485, arXiv.org, revised Nov 2020.
    5. B. Goswami & G. Ambika & N. Marwan & J. Kurths, 2011. "On interrelations of recurrences and connectivity trends between stock indices," Papers 1103.5189, arXiv.org.
    6. Songtao Wu & Jianmin He & Chao Wang, 2017. "Effects of Common Factors on Dynamics of Stocks Traded by Investors with Limited Information Capacity," Discrete Dynamics in Nature and Society, Hindawi, vol. 2017, pages 1-15, September.
    7. Tabak, Benjamin M. & Serra, Thiago R. & Cajueiro, Daniel O., 2010. "Topological properties of stock market networks: The case of Brazil," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(16), pages 3240-3249.
    8. Jang, Wooseok & Lee, Junghoon & Chang, Woojin, 2011. "Currency crises and the evolution of foreign exchange market: Evidence from minimum spanning tree," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(4), pages 707-718.
    9. Goswami, B. & Ambika, G. & Marwan, N. & Kurths, J., 2012. "On interrelations of recurrences and connectivity trends between stock indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(18), pages 4364-4376.
    10. Kazemilari, Mansooreh & Djauhari, Maman Abdurachman, 2015. "Correlation network analysis for multi-dimensional data in stocks market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 429(C), pages 62-75.
    11. Mansooreh Kazemilari & Maman Abdurachman Djauhari & Zuhaimy Ismail, 2016. "Foreign Exchange Market Performance: Evidence from Bivariate Time Series Approach," Papers 1608.07694, arXiv.org.

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