A novel application of the correlation matrix formalism to study dynamics of the financial evolution is presented. This formalism allows to quantify the memory effects as well as some potential repeatable intraday structures in the financial time series. The present study is based on the...

We apply random matrix theory to compare correlation matrix estimators C obtained from emerging market data. The correlation matrices are constructed from 10 years of daily data for stocks listed on the Johannesburg stock exchange (JSE) from January 1993 to December 2002. We test the spectral...

The statistics of the eigenvalues of symmetric random matrices, composed by real and statistically independent elements following the distribution that maximizes Tsallis's entropy, is carried numerically in the limit of large matrices. For entropic indexes in the interval −∞<q<53, by using a convenient rescale of variables, it is possible to show that such matrices fall in the same class of the Gaussian orthogonal ensemble (GOE). For the entropic index 53⩽q<3, the density of eigenvalues and the distribution of level spacings do not seem to follow a simple rescale of variables involving different values of q, and exhibit a behavior very distinct from the GOE: both quantities present long tails for 53⩽q⩽2, and such long tails die out when q>2. The density of...</q<53,>

Minimum market transparency requirements impose hedge fund (HF) managers to use the statement declared strategy in practice. However, each declared strategy may actually generate a multiplicity of implemented management decisions. Is then the “actual ” strategy the same as the...

A method for extracting information carrying eigenvalues of the correlation matrix is presented based on the topological transformation of the manifold defined by the data matrix itself. The transformation, performed with the use of the minimum spanning tree and the barycentric transformation,...

We consider the Hessian matrices of simple liquid systems as a new type of random matrices. By numerically comparing the distribution of the nearest-neighbor level spacing of the eigenvalues with the Wigner's surmise, we found that the level statistics is akin to the generic Gaussian Orthogonal...

The random matrix theory is useful in the study of large systems such as electric grids. These transmission systems can be modeled as complex networks, with high-voltage lines the edges that connect nodes representing power plants and substations. We draw upon established literature of complex...

We report briefly on an application of random matrix theory to the analysis of SA financial market data (An Analysis of cross-correlations in South African financial market data, e- print cond-mat/0402389). Correlation matrices C are constructed from 10 years of daily data for stocks listed on...

We study the evolution of the distribution of consumption of individuals in the majority population in China during the period 1995–2012 and find that its probability density functions (PDFs) obey the rule Pc(x)=K(x−μ)e−(x−μ)22σ2. We also find (i) that the PDFs and the individual...