The multiscale analysis between stock market time series

Wenbin Shi () and Pengjian Shang ()
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Wenbin Shi: School of Science, Beijing Jiaotong University, Beijing 100044, P. R. China
Pengjian Shang: School of Science, Beijing Jiaotong University, Beijing 100044, P. R. China

International Journal of Modern Physics C (IJMPC), 2015, vol. 26, issue 06, 1-12

Abstract: This paper is devoted to multiscale cross-correlation analysis on stock market time series, where multiscale DCCA cross-correlation coefficient as well as multiscale cross-sample entropy (MSCE) is applied. Multiscale DCCA cross-correlation coefficient is a realization of DCCA cross-correlation coefficient on multiple scales. The results of this method present a good scaling characterization. More significantly, this method is able to group stock markets by areas. Compared to multiscale DCCA cross-correlation coefficient, MSCE presents a more remarkable scaling characterization and the value of each log return of financial time series decreases with the increasing of scale factor. But the results of grouping is not as good as multiscale DCCA cross-correlation coefficient.

Keywords: DCCA cross-correlation coefficient; multiscale cross-sample entropy; multiscale analysis; stock market time series (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (2)

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DOI: 10.1142/S0129183115500710

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