Random-error minimization during cross-correlation of early-type spectra

APPLICATION OF THE RANDOM MATRIX THEORY ON THE CROSS-CORRELATION OF STOCK ‎PRICES

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...

Correlation Clustering Revisited: The "True" Cost of Error Minimization Problems

Correlation Clustering was defined by Bansal, Blum, and Chawla as the problem of clustering a set of elements based on a possibly inconsistent binary similarity function between element pairs. Their setting is agnostic in the sense that a ground truth clustering is not assumed to exist, and the only reasonable way to measure the cost of a solution is by comparing it with the input similarity fu...

Niho Type Cross-Correlation Functions and Related Equations Niho Type Cross-Correlation Functions and Related Equations

Multifractal cross-correlation spectra analysis on Chinese stock markets

In this paper, the long-range cross-correlation of Chinese stock indices is systematically studied. The multifractal detrended cross-correlation analysis (MF-DXA) appears to be one of the most effective methods in detecting long-range cross-correlation of two non-stationary variables. The Legendre spectrum and the large deviations spectrum are extended to the cross-correlation case, so as to pr...

Cross- and auto-correlation in early vision.

Neurons that respond selectively to the orientation of visual stimuli were discovered in V1 more than 50 years ago, but it is still not fully understood how or why this is brought about. We report experiments planned to show whether human observers use cross-correlation or auto-correlation to detect oriented streaks in arrays of randomly positioned dots, expecting that this would help us to und...