کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
7382607 | 1480180 | 2014 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Detrended cross-correlation analysis approach for assessing asymmetric multifractal detrended cross-correlations and their application to the Chinese financial market
ترجمه فارسی عنوان
رویکرد تجزیه و تحلیل همبستگی متوازن برای ارزیابی همبستگی متقابل چندپارکتالی نامتقارن و کاربرد آنها در بازار مالی چین
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کلمات کلیدی
نامتقارن، چندبخلقی متقابل متقابل، بازار سهام چینی، قیمت ارز،
موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
فیزیک ریاضی
چکیده انگلیسی
We propose a new method called the multifractal asymmetric detrended cross-correlation analysis method (MF-ADCCA) to investigate the asymmetric cross-correlations in nonstationary time series that combine the multifractal detrended cross-correlation analysis (MF-DCCA) and asymmetric detrended fluctuation analysis (A-DFA). The study aims to determine whether different scaling properties of the cross-correlations are obtained if a one-time series trending is either positive or negative. We apply MF-ADCCA to analyze empirically the scaling behavior of the cross-correlations among the Chinese stock market, the RMB exchange market, and the US stock market. Empirical results indicate that the cross-correlations between the Chinese stock market and the RMB/USD exchange market are more persistent when any one of the markets is falling. On the contrary, the cross-correlations between the Chinese stock market and the RMB/EU, RMB/GBP, RMB/JPY exchange markets and the US stock market are more persistent when one of the markets is rising. Moreover, asymmetric cross-correlations between any two of the selected financial markets are multifractal.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Physica A: Statistical Mechanics and its Applications - Volume 393, 1 January 2014, Pages 460-469
Journal: Physica A: Statistical Mechanics and its Applications - Volume 393, 1 January 2014, Pages 460-469
نویسندگان
Guangxi Cao, Jie Cao, Longbing Xu, LingYun He,