the analysis of cross-correlations is extensively applied for understanding of interconnections in stock markets. variety of methods are used in order to search stock cross-correlations including the random matrix theory (rmt), the principal component analysis (pca) and the hierachical ‎structures.‎ in ‎this work‎, we analyze cross-crrelations between price fluctuations of 20 ‎company ‎stocks‎‎...

We present a dedicated algorithm for the nonnegative factorization of a correlation matrix from an application in financial engineering. We look for a low-rank approximation. The origin of the problem is discussed in some detail. Next to the description of the algorithm, we prove, by means of a counter example, that an exact nonnegative decomposition of a general positive semidefinite matrix is...

is learned, it is stored in the brain, from e recalled later when required. Memory G y be d i v i d m t e r m ’ ” x m o r y , depending on the retention time (Arbib, 1989). Short-term memory refers to a compilation of knowledge representing the “current” state of the environment. Any discrepancies between knowledge stored in short-term memory and a “new” state are used to update the short-term ...

In this article we discuss a method to complete the correlation matrix in a multi-dimensional stochastic volatility model. We concentrate on the construction of a positive definite correlation matrix. Furthermore we present a numerical integration scheme for this system of stochastic differential equations which improves the approximation quality of the standard Euler-Maruyama method with minim...

A new model for associative memory, based on a correlamatrix, and the rest of the elements are put equal to zero. In tion matrix, is suggested. In this model information is accumulated on a t ~~~~~~~~~~~~~addition to such a ranldomly sam led matrix, we discuss a memory elements as products of component data. Denoting a key vector by q(P), and the data' associated with it by another vector x(P),...