On the nature of the stock market: Simulations and experiments

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.

227 pages, PhD thesis

References in corpus (10)

• Scaling of the distribution of fluctuations of financial market indices
• Inverse Cubic Law for the Probability Distribution of Stock Price Variations
• Scaling of the distribution of price fluctuations of individual companies
• Toward a Theory of Marginally Efficient Markets
• Self-Organized Percolation Model for Stock Market Fluctuations
• Dynamical Optimization Theory of a Diversified Portfolio
• The sharp peak-flat trough pattern and critical speculation
• Probability distribution of drawdowns in risky investments
• A prognosis oriented microscopic stock market model
• Statistical Analysis of the Stock Index of the Budapest Stock Exchange