Jensen-Detrended Cross-Correlation function for non-stationary time series with application to Latin American stock markets

Javier E. Contreras-Reyes, Fabiola Jeldes-Delgado and Raúl Carrasco

Physica A: Statistical Mechanics and its Applications, 2024, vol. 654, issue C

Abstract: Variance has an important role in statistics and information theory fields, by forming the basis for many well-known information measures. Based on Jensen’s inequality and variance, the Jensen-variance information has been previously proposed to measure the distance between two random variables. Jensen-variance distance is based on the convexity property of random variable variance. Based on the relationship between Jensen-variance distance and classical Detrended Cross-Correlation (DCC) of two not necessarily stationary process, the Jensen-Detrended Covariance and Jensen-DCC functions are proposed in this paper. Moreover, Jensen-DCC function is also considered for Hénon and Logistic chaotic maps for simulated time series. Then we considered a stock market time series dataset for the study of similarity of Latin American indexes with S&P500 and Shanghai ones. We obtained a useful tool to study the similarity or distance of two non-stationary time series based on DCC coefficient.

Keywords: Detrended Cross-Correlation coefficient; Non-stationary processes; Jensen-variance distance; Convexity; Chaotic maps; Stock market indexes (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:654:y:2024:i:c:s0378437124006241

DOI: 10.1016/j.physa.2024.130115

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