کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
977731 | 1480152 | 2015 | 10 صفحه PDF | دانلود رایگان |
• A new method is proposed to detect discrete long-range correlations.
• Sectors in a same stock turn out to have continuous long-range correlations.
• Sectors in different stock markets prove to have discrete scaling invariance.
The de-trended cross-correlation analysis (DCCA) is converted to a new form, which turns out to be a periodic function modulated power-law, to evaluate discrete-scale long-range cross-correlation between time series. If the modulator is dominated with one frequency, the derived form will degenerate to a log-periodic power-law. We investigate a total of five important stock markets distributing in different continents. Calculations show that the cross-correlations between different stock markets may hint at log-periodic oscillations. This finding may be helpful for us to evaluate financial state in a global way.
Journal: Physica A: Statistical Mechanics and its Applications - Volume 421, 1 March 2015, Pages 161–170