On the nature of the stock market: Simulations and experiments

TL;DR

This paper develops and compares two simple stock market models, finding that a decentralized model exhibits realistic market phenomena only near critical points, suggesting real markets may operate at such criticality.

Contribution

Introduces a decentralized stock market model that reproduces empirical market properties, highlighting the importance of criticality and endogenous interactions.

Findings

Decentralized model captures key market properties.

Market phenomena emerge at critical parameter values.

Models suggest real markets may operate near critical points.

Abstract

In this dissertation two simple models of stock exchange are developed and simulated numerically. The first is characterized by centralized trading with a market maker. Unfortunately, this model is unable to generate realistic market dynamics. The second model discards the requirement of centralized trading. Under variation of the control parameter the model exhibits two phase transitions: both a first- and a second-order (critical). The decentralized model is able to capture many of the interesting properties observed in empirical markets. Significantly, these properties only emerge when the parameters are tuned such that the model spans the critical point. This suggests that real markets may operate at or near a critical point, but is unable to explain why this should be. One of the main points of the thesis is that these empirical phenomena are not present in the stochastic driving force, but emerge endogenously from interactions between agents.