A new methodology for local cross-correlation between two nonstationary time series

DOI10.1016/j.physa.2019.121307OpenAlexW2946430724MaRDI QIDQ2161929

Chenhua Shen, Xiaobin Wu

Publication date: 5 August 2022

Published in: Physica A (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.physa.2019.121307

zbMATH Keywords

nonstationary time seriesdetrended fluctuation analysis (DFA) scaling exponentslocally intrinsic cross-correlationlocally weighted Pearson correlation coefficientseasonal changes

Mathematics Subject Classification ID

Statistical mechanics, structure of matter (82-XX)

Cites Work

• Unnamed Item
• Multifractal detrended fluctuation analysis of nonstationary time series
• Modeling traffic flow correlation using DFA and DCCA
• Analysis of detrended time-lagged cross-correlation between two nonstationary time series
• Mixed-correlated ARFIMA processes for power-law cross-correlations
• Cross-correlations between volume change and price change
• Locally Weighted Regression: An Approach to Regression Analysis by Local Fitting

This page was built for publication: A new methodology for local cross-correlation between two nonstationary time series