Journal Article10.1016/J.PHYSA.2019.122960
Detrended moving average partial cross-correlation analysis on financial time series
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TL;DR: This work suggests a combination methodology of Detrended Moving Average Processing and Partial Cross-correlation Analysis to quantify the correlations between different time series, which it is found that this method can reveal the real cross-correlations between systems even when the indirect cross-Correlations established by other common factors exist.
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Abstract: Cross-correlations between nonlinear time series widely exist in complex systems. It is of great importance to accurately measure the correlations between time series. In this work, we suggest a combination methodology of Detrended Moving Average Processing and Partial Cross-correlation Analysis to quantify the correlations between different time series, which we call as Detrended Moving Average Partial Cross-correlation Analysis ( D M P C C A ). This novel approach combines the advantages of Detrended Moving Average Processing and Partial Cross-correlation Analysis, not only exploring power-law cross-correlations between two signals but removing underlying impacts of other signals on those two signals. To demonstrate the advantages of this approach, we carry out experiments with synthetic data generated by correlated processes and compare the performance of this measurement to traditional cross-correlation techniques. It is found that this method can reveal the real cross-correlations between systems even when the indirect cross-correlations established by other common factors exist. Then we go further study into the application of D M P C C A to financial time series in order to report its performance in stock markets and investigate cross-correlations between different stock indices. Furthermore, the rolling windows method is used in conjunction with D M P C C A to capture the changes of cross-correlations between stock indices as time goes on. We notice that there is a special period when D M P C C A coefficients between stock indices are obviously different from those of other periods.
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•Book
Substituent constants for correlation analysis in chemistry and biology
Corwin Hansch,Albert J. Leo +1 more
- 01 Jan 1979
TL;DR: In this paper, the book is the window to get in the world and you can open the world easily, and these wise words are really familiar with you, so bring home now the book enPDFd substituent constants for correlation analysis in chemistry and biology to be your sources when going to read.
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