Wang, D., Podobrink, B., Horvatic, D. and Stanley, H.E. (2011) Quantifying and Modeling Long-Range Cross-Correlations in Multiple Time Series with Applications to World Stock Indices. Physical Review E, 83, Article ID: 046121.
https://doi.org/10.1103/PhysRevE.83.046121

has been cited by the following article:

• TITLE: Analysis of Cross-Correlations in Emerging Markets Using Random Matrix Theory

  AUTHORS: Thomas Chinwe Urama, Patrick Oseloka Ezepue, Chimezie Peters Nnanwa

  KEYWORDS: Random Matrix Theory, Cross-Correlations, Emerging Markets, Option Pricing, Eigenvalues Eigenvectors, Inverse Participation Ratios and Implied Volatility

  JOURNAL NAME: Journal of Mathematical Finance, Vol.7 No.2, May 16, 2017

  ABSTRACT: This paper investigates the universal financial dynamics in two dominant stock markets in Sub-Saharan Africa, through an in-depth analysis of the cross-correlation matrix of price returns in Nigerian Stock Market (NSM) and Johannesburg Stock Exchange (JSE), for the period 2009 to 2013. The strength of correlations between stocks is known to be higher in JSE than that of the NSM. The stock price dynamics in the NSM is important for modeling Nigerian derivatives in the future, and in the light of this, it is pertinent to note that the interactions of other stocks with the oil sector are weak, whereas the banking stocks have strong positive interactions with the other sectors in the stock exchange. For the JSE, it is the oil sector and beverages that have greater sectorial correlations, instead of the banks which have a weaker one in relation to other assets in the stock exchange.