THE TIME DEPENDENCE AND INTERCONNECTEDNESS OF DEVELOPED STOCK MARKETS

This study examines the interconnectedness in developed stock markets by fo- cusing on the time dependence of their multi-vocal relationships. Conceptually, we discuss the differences between financial contagion, interconnectedness and dominance in order to highlight the argument that stock markets are functionally connected. For capturing the shifts in markets’ correlation patterns over time, and their frequencies, we employ a method- ology in the framework of Wavelet Local Multiple Correlation (WLMC). We have involved in the analysis three developed stock markets, on a long-time span from 2005-2024. Our find- ings suggest that the correlation pattern displays significant variations over time at different frequencies.

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Publication Details

Journal
The Review of Finance and Banking
Published
2024-12-31
DOI
https://doi.org/10.24818/rfb.24.16.02.06
Primary Topic
Complex Systems and Time Series Analysis
Type
article
Field-Weighted Citation Impact
0.00
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article

THE TIME DEPENDENCE AND INTERCONNECTEDNESS OF DEVELOPED STOCK MARKETS

Bogdan Dima, Ştefana Maria Dima, Anca-Adriana SARAOLU
The Review of Finance and Banking
Complex Systems and Time Series Analysis
article

THE TIME DEPENDENCE AND INTERCONNECTEDNESS OF DEVELOPED STOCK MARKETS

Bogdan Dima, Ştefana Maria Dima, Anca-Adriana SARAOLU
article en

Abstract

This study examines the interconnectedness in developed stock markets by fo- cusing on the time dependence of their multi-vocal relationships. Conceptually, we discuss the differences between financial contagion, interconnectedness and dominance in order to highlight the argument that stock markets are functionally connected. For capturing the shifts in markets’ correlation patterns over time, and their frequencies, we employ a method- ology in the framework of Wavelet Local Multiple Correlation (WLMC). We have involved in the analysis three developed stock markets, on a long-time span from 2005-2024. Our find- ings suggest that the correlation pattern displays significant variations over time at different frequencies.

The Review of Finance and BankingVol. 16(2)
Openalex Percentile: Top 67%
Complex Systems and Time Series Analysis
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