Understanding agent-based models of financial markets: a bottom-up approach based on order parameters and phase diagrams
Ribin Lye, James Peng Lung Tan, Siew Ann Cheong

TL;DR
This paper introduces a bottom-up framework using order parameters and phase diagrams to analyze agent-based models of financial markets, illustrating how different trader behaviors influence market phases.
Contribution
It presents a novel approach to understanding agent-based financial models through phase diagrams derived from order parameters, bridging deterministic and stochastic models.
Findings
Identified three market phases: dead, boom, and jammed.
Stochasticity eliminates the dead market phase.
Order parameters from steady-state distributions effectively characterize market states.
Abstract
We describe a bottom-up framework, based on the identification of appropriate order parameters and determination of phase diagrams, for understanding progressively refined agent-based models and simulations of financial markets. We illustrate this framework by starting with a deterministic toy model, whereby independent traders buy and sell stocks through an order book that acts as a clearing house. The price of a stock increases whenever it is bought and decreases whenever it is sold. Price changes are updated by the order book before the next transaction takes place. In this deterministic model, all traders based their buy decisions on a call utility function, and all their sell decisions on a put utility function. We then make the agent-based model more realistic, by either having a fraction of traders buy a random stock on offer, or a fraction of traders sell a…
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Taxonomy
TopicsComplex Systems and Time Series Analysis · Financial Markets and Investment Strategies · Auction Theory and Applications
