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Raseta, M.* ; Silver, S.D.* ; Bazarova, A.

Phase transitions in an ising model of agent expectations in financial markets: Analytics and numerical results in one and two-dimensional network topologies.

IEEE Access 13, 181336-181348 (2025)
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Open Access Gold
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We cite correspondences between dynamics in competitive markets and information theory in the objective of recovering signal from noisy information sequences. In financial markets, this objective has been examined as recovering signal on phase transitions between ordered and disordered states of agents in the market. These transitions have been indicated to denote critical points in time series of market price. Although there is a noteworthy background in information theory in the study of the dynamics of the Ising model in this manuscript, we pursue a different modeling approach. Whereas phase transitions in a multicomponent model of market states have previously been studied with numerical methods, we provide an analytical demonstration that a multicomponent model as an Ising analogue can evidence phase transitions.
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Publication type Article: Journal article
Document type Scientific Article
Keywords Numerical models; Computer crashes; Analytical models; Mathematical models; Noise; Correlation; Stock markets; Predictive models; Network topology; Lattices; Agent price expectations; Ising market models; multicomponent models of phase transitions; signal in financial markets; Opinion Dynamics; Brownian-motion; Partial Sums; Approximation; Statistics; Crashes; Memory
Language english
Publication Year 2025
HGF-reported in Year 2025
ISSN (print) / ISBN 2169-3536
e-ISSN 2169-3536
Journal IEEE Access
Quellenangaben Volume: 13, Issue: , Pages: 181336-181348 Article Number: , Supplement: ,
Publisher IEEE
Publishing Place 445 Hoes Lane, Piscataway, Nj 08855-4141 Usa
Reviewing status Peer reviewed
Institute(s) Helmholtz Artifical Intelligence Cooperation Unit (HAICU)
POF-Topic(s) 30205 - Bioengineering and Digital Health
Research field(s) Enabling and Novel Technologies
PSP Element(s) G-530015-001
Grants Helmholtz Association Initiative and Networking Fund through the Frame of Helmholtz AI
DOI 10.1109/ACCESS.2025.3623946
WOS ID 001600763000004
Erfassungsdatum 2025-11-20
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