Statistical properties of cross-correlation in the Korean stock market

被引:0
|
作者
G. Oh
C. Eom
F. Wang
W.-S. Jung
H. E. Stanley
S. Kim
机构
[1] Chosun University,Division of Business Administration
[2] Pusan National University,Division of Business Administration
[3] Boston University,Center for Polymer Studies and Department of Physics
[4] Graduate Program for Technology and Innovation Managemant,Department of Physics
[5] Pohang University of Science and Technology,undefined
[6] Pohang University of Science and Technology,undefined
[7] Asia Pacific Center for Theoretical Physics,undefined
来源
关键词
Stock Return; Large Eigenvalue; Random Matrix Theory; Portfolio Return; Eigenvalue Distribution;
D O I
暂无
中图分类号
学科分类号
摘要
We investigate the statistical properties of the cross-correlation matrix between individual stocks traded in the Korean stock market using the random matrix theory (RMT) and observe how these affect the portfolio weights in the Markowitz portfolio theory. We find that the distribution of the cross-correlation matrix is positively skewed and changes over time. We find that the eigenvalue distribution of original cross-correlation matrix deviates from the eigenvalues predicted by the RMT, and the largest eigenvalue is 52 times larger than the maximum value among the eigenvalues predicted by the RMT. The \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$\beta_{473}$\end{document} coefficient, which reflect the largest eigenvalue property, is 0.8, while one of the eigenvalues in the RMT is approximately zero. Notably, we show that the entropy function \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$E(\sigma)$\end{document} with the portfolio risk σ for the original and filtered cross-correlation matrices are consistent with a power-law function, E(σ) ~ \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$\sigma^{-\gamma}$\end{document}, with the exponent γ ~ 2.92 and those for Asian currency crisis decreases significantly.
引用
收藏
页码:55 / 60
页数:5
相关论文
共 50 条
  • [41] Cross-correlation properties of perfect binary sequences
    Hertel, D
    [J]. SEQUENCES AND THEIR APPLICATIONS - SETA 2004, 2005, 3486 : 208 - 219
  • [43] Cross-correlation properties of perfect binary sequences
    Zhuo, Ze-Peng
    Xiao, Guo-Zhen
    [J]. Beijing Youdian Daxue Xuebao/Journal of Beijing University of Posts and Telecommunications, 2010, 33 (02): : 78 - 81
  • [44] DCCA cross-correlation coefficient: Quantifying level of cross-correlation
    Zebende, G. F.
    [J]. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2011, 390 (04) : 614 - 618
  • [45] Detrended multiple moving average cross-correlation analysis and its application in the correlation measurement of stock market in Shanghai, Shenzhen, and Hong Kong
    Cao, Guangxi
    Xie, Wenhao
    [J]. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2022, 590
  • [46] Generalized Cross-Correlation Properties of Chu Sequences
    Kang, Jae Won
    Whang, Younghoon
    Ko, Byung Hoon
    Kim, Kwang Soon
    [J]. IEEE TRANSACTIONS ON INFORMATION THEORY, 2012, 58 (01) : 438 - 444
  • [47] SOME CROSS-CORRELATION PROPERTIES FOR DISTORTED SIGNALS
    BROWN, JL
    [J]. IEEE TRANSACTIONS ON INFORMATION THEORY, 1975, 21 (04) : 453 - 458
  • [48] Robust Statistical Detection of Power-Law Cross-Correlation
    Duncan A. J. Blythe
    Vadim V. Nikulin
    Klaus-Robert Müller
    [J]. Scientific Reports, 6
  • [49] Multifractal detrended cross-correlation analysis of Indian Electricity market
    Pal, Mayukha
    Rao, P. Madhusudana
    Manimaran, P.
    [J]. 2015 50TH INTERNATIONAL UNIVERSITIES POWER ENGINEERING CONFERENCE (UPEC), 2015,
  • [50] Multifractal temporally weighted detrended cross-correlation analysis to quantify power-law cross-correlation and its application to stock markets
    Wei, Yun-Lan
    Yu, Zu-Guo
    Zou, Hai-Long
    Vo Anh
    [J]. CHAOS, 2017, 27 (06)