Random matrix theory analysis of cross-correlations in the US stock market: Evidence from Pearson’s correlation coefficient and detrended cross-correlation coefficient

Analysis of the Dynamic Evolutionary Behavior of American Heating Oil Spot and Futures Price Fluctuation Networks

“…Through the calculation, it can be obtained that the Spearman correlation coefficients [36] of the two are 0.6153 and 0.1239 in the periods of stable fluctuation and sharp volatility. At the same time, based on the Pearson correlation coefficient formula [37,38], we find that the correlation values of them in stable fluctuation period and violent fluctuation period are 0.9013 and 0.1410, respectively. However, it is acknowledged that the Pearson correlation coefficient is more accurate and more sensitive than the Spearman rank correlation coefficient, and only if the Pearson correlation coefficient does not significantly deviate from the Spearman rank correlation coefficient can we use the former, if the difference between the two is too large, then the original data is irregular.…”

Analysis of Cross-Correlations in Emerging Markets Using Random Matrix Theory

“…Also, [7] declare that following the introduction of RMT into the financial markets by [8] and [9], the concept has been used in the study of the statistical properties of cross-correlations in different financial markets [10]- [22]. Laurent Laloux et al [8] opine that for financial assets, the study of the empirical correlation matrix is very relevant, since, from their finding, it is its estimation in the price movements of different assets that constitutes a significant and indispensable aspect of risk management.…”

EEG Epilepsy Seizure Signal Characterization through theories of Random Matrix Analysis

“…It is witnessed that random matrix theory approach for statistical analysis of cross-correlation matrix has brought attention of researcher to analyze natural time series data especially from financial and biological systems [20][21][22][23][24][25][26]. The purpose of this paper is to propose a real time analysis technique to characterize epilepsy patients with seizure from healthy human or patients who achieved complete seizure control using EEG signals that are measured for different recordings simultaneously making a high dimensional data for analysis using the random matrix theory.…”