Simulating sample correlation matrices is important in many areas of statistics. Approaches such as generating Gaussian data and finding their sample correlation matrix or generating random uniform ...

This example defines modules to compute correlation coefficients between numeric variables and standardized values for a set of data. /* Module to compute correlations */ ...

For a symmetric correlation matrix, the Inverse Correlation Matrix table contains the inverse of the correlation matrix, as shown in Figure 40.14. The diagonal elements of the inverse correlation ...

William N. Goetzmann, Lingfeng Li, K. Geert Rouwenhorst, Long‐Term Global Market Correlations, The Journal of Business, Vol. 78, No. 1 (January 2005), pp. 1-38 ...

Cleaning correlation matrices The determination of correlation matrices is typically affected by in-sample noise. Joël Bun, Jean-Philippe Bouchaud and Marc Potters propose a simple, yet optimal, ...

Random sampling from a multivariate normal distribution is essential for Monte Carlo simulations in many credit risk models. For a portfolio of N obligors, standard methods usually require O(N2) ...

The asset correlation matrix proves that Treasuries are great diversifiers. It shows the correlation coefficient between Treasuries, developed markets, and emerging market stocks.