  The cross-correlation matrix of daily returns of stock market indices in a
diverse set of 37 countries worldwide was analyzed. Comparison of the spectrum
of this matrix with predictions of random matrix theory provides an empirical
evidence of strong interactions between individual economies, as manifested by
three largest eigenvalues and the corresponding set of stable, non-random
eigenvectors. The observed correlation structure is robust with respect to
changes in the time horizon of returns ranging from 1 to 10 trading days, and
to replacing individual returns with just their signs. This last observation
confirms that it is mostly correlations in signs and not absolute values of
fluctuations, which are responsible for the observed effect. Correlations
between different trading days seem to persist for up to 3 days before decaying
to the level of the background noise.
