The Opinion Game: Stock price evolution from microscopic market modelling

TL;DR

This paper introduces a microscopic agent-based model for stock price evolution, capturing market dynamics through stochastic opinion changes and matching offers, with some analytical insights and simulation results reflecting real market features.

Contribution

It presents a novel Markovian agent-based framework that models stock prices from individual buyer and seller opinions, incorporating interaction mechanisms and analytical results.

Findings

Non-interacting model yields analytical results.

Simulations reproduce key features of real stock prices.

Interaction mechanisms improve model realism.

Abstract

We propose a class of Markovian agent based models for the time evolution of a share price in an interactive market. The models rely on a microscopic description of a market of buyers and sellers who change their opinion about the stock value in a stochastic way. The actual price is determined in realistic way by matching (clearing) offers until no further transactions can be performed. Some analytic results for a non-interacting model are presented. We also propose basic interaction mechanisms and show in simulations that these already reproduce certain particular features of prices in real stock markets.