  We introduce a method to predict which correlation matrix coefficients are
likely to change their signs in the future in the high-dimensional regime, i.e.
when the number of features is larger than the number of samples per feature.
The stability of correlation signs, two-by-two relationships, is found to
depend on three-by-three relationships inspired by Heider social cohesion
theory in this regime. We apply our method to US and Hong Kong equities
historical data to illustrate how the structure of correlation matrices
influences the stability of the sign of its coefficients.
