Self-organizing Ising model of financial markets

By Wei‐Xing Zhou, Didier Sornette. 2005

154 citations recorded by the source corpus.

Abstract. We study a dynamical Ising-like model of agents' opinions (buy or sell) with learning, in which the coupling coefficients are re-assessed continuously in time according to how past external news (time-varying magnetic field) have explained realized market returns. By combining herding, the impact of external news and private information, we find that the stylized facts of financial markets are reproduced only when agents misattribute the success of news to predict return to herding effects, thereby providing positive feedbacks leading to the model functioning close to the Ising critical point.

Subfields: Economics and Econometrics, Management Science and Operations Research, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/17f27b64f06e4edcb1e4f624eb18ce6dfb87938c

How researchers see this paper

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In Economics and Econometrics

1. Wolfgang Paul
2. Tobias Preis
3. Peter Virnau
4. Johannes Josef Schneider

In Management Science and Operations Research

1. Wolfgang Paul
2. Tobias Preis
3. Peter Virnau
4. Johannes Josef Schneider

In Statistical and Nonlinear Physics

1. Wolfgang Paul
2. Tobias Preis
3. Peter Virnau
4. Johannes Josef Schneider

Citations in the corpus

• GPU accelerated Monte Carlo simulation of the 2D and 3D Ising model (2009, methodology): “For example, a simple Ising model based simulation of an artificial stock market is presented in [11], in which specific properties of financial markets like consequences of the herding behavior can be reproduced.”