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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)
Verlagsversion DOI
Open Access Gold
Creative Commons Lizenzvertrag
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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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter 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
Sprache englisch
Veröffentlichungsjahr 2025
HGF-Berichtsjahr 2025
ISSN (print) / ISBN 2169-3536
e-ISSN 2169-3536
Zeitschrift IEEE Access
Quellenangaben Band: 13, Heft: , Seiten: 181336-181348 Artikelnummer: , Supplement: ,
Verlag IEEE
Verlagsort 445 Hoes Lane, Piscataway, Nj 08855-4141 Usa
Begutachtungsstatus Peer reviewed
Institut(e) Helmholtz Artifical Intelligence Cooperation Unit (HAICU)
POF Topic(s) 30205 - Bioengineering and Digital Health
Forschungsfeld(er) Enabling and Novel Technologies
PSP-Element(e) G-530015-001
Förderungen 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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