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Stock Market Differences In Correlation-Based Weighted Network

Author

Listed:
  • JANGHYUK YOUN

    (Technology Management Economics and Policy Program, Seoul National University, Seoul 151-742, Republic of Korea)

  • JUNGHOON LEE

    (Technology Management Economics and Policy Program, Seoul National University, Seoul 151-742, Republic of Korea)

  • WOOJIN CHANG

    (Industrial Engineering, Seoul National University, Seoul 151-742, Republic of Korea)

Abstract

We examined the sector dynamics of Korean stock market in relation to the market volatility. The daily price data of 360 stocks for 5019 trading days (from January, 1990 to August, 2008) in Korean stock market are used. We performed the weighted network analysis and employed four measures: the average, the variance, the intensity, and the coherence of network weights (absolute values of stock return correlations) to investigate the network structure of Korean stock market. We performed regression analysis using the four measures in the seven major industry sectors and the market (seven sectors combined). We found that the average, the intensity, and the coherence of sector (subnetwork) weights increase as market becomes volatile. Except for the "Financials" sector, the variance of sector weights also grows as market volatility increases. Based on the four measures, we can categorize "Financials," "Information Technology" and "Industrials" sectors into one group, and "Materials" and "Consumer Discretionary" sectors into another group. We investigated the distributions of intrasector and intersector weights for each sector and found the differences in "Financials" sector are most distinct.

Suggested Citation

  • Janghyuk Youn & Junghoon Lee & Woojin Chang, 2011. "Stock Market Differences In Correlation-Based Weighted Network," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 22(11), pages 1227-1245.
    • Handle: RePEc:wsi:ijmpcx:v:22:y:2011:i:11:n:s0129183111016853
    DOI: 10.1142/S0129183111016853
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    1. ., 2006. "Physical and Social Indicators," Chapters, in: Middle East Oil Exporters, chapter 5, Edward Elgar Publishing.
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    Cited by:

    1. 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.
    2. Zhong, Tao & Peng, Qinke & Wang, Xiao & Zhang, Jing, 2016. "Novel indexes based on network structure to indicate financial market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 583-594.

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