Statistical properties of cross-correlation in the Korean stock market

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 <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$\beta_{473}$</EquationSource> </InlineEquation> 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 <InlineEquation ID="IEq2"> <EquationSource Format="TEX">$E(\sigma)$</EquationSource> </InlineEquation> with the portfolio risk σ for the original and filtered cross-correlation matrices are consistent with a power-law function, E(σ) ~ <InlineEquation ID="IEq3"> <EquationSource Format="TEX">$\sigma^{-\gamma}$</EquationSource> </InlineEquation>, with the exponent γ ~ 2.92 and those for Asian currency crisis decreases significantly. Copyright EDP Sciences, SIF, Springer-Verlag Berlin Heidelberg 2011