| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 7383070 | Physica A: Statistical Mechanics and its Applications | 2011 | 9 Pages |
Abstract
⺠DMCA is proposed to detect cross-correlation between two non-stationary time series. ⺠We compare DMCA and DCCA by generating ARFIMA process and estimating the correlation. ⺠DMCA improves the estimation of cross-correlation with less calculating amounts. ⺠DMCA reduces impacts of trends on detection of power-law cross-correlation. ⺠We apply DMCA to investigate real-world data to detect cross-market correlation.
Related Topics
Physical Sciences and Engineering
Mathematics
Mathematical Physics
Authors
Ling-Yun He, Shu-Peng Chen,