The uncertainty of fluctuation correlations in global stock markets

Faming Wang, Xueyun Rong and Lei Yin

Finance Research Letters, 2024, vol. 66, issue C

Abstract: Revealing the associations among stocks is fundamental for unveiling the underlying rules of global stock markets. In this work, we propose a combined entropy–complex network framework that detects fluctuation connections among stock prices. The results demonstrate that global stock markets show high uncertainty (high entropy). Based on our analysis of the system's symmetry and dominant correlation fluctuation patterns, we identified the least uncertain stock pair in the market: DEU and FRA. We also revealed the most reliable stocks as references for every stock. Quantifying the uncertainty found in global stock markets and identifying the driving fluctuation patterns can benefit investors by decreasing risk.

Keywords: Fluctuation correlation; Uncertainty; Dominant pattern; Complex network (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1544612324007372
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:66:y:2024:i:c:s1544612324007372

DOI: 10.1016/j.frl.2024.105707

Access Statistics for this article

Finance Research Letters is currently edited by R. Gençay

More articles in Finance Research Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().