Date of Award

2015

Document Type

Thesis

Degree Name

Bachelors

Department

Social Sciences

First Advisor

Khemraj, Tarron

Keywords

Markets, Economics, Financial Markets, Applied Mathematics

Area of Concentration

Economics

Abstract

Through coalescing nonlinear dynamics, chaos theory, game theory, network theory, complex adaptive systems, quantum mechanics, and financial economics, one is able to capture salient emergent properties found in financial markets. This thesis develops this potential, drawing on and extending powerful results from a variety of fields for applications in signal and statistical analysis. Their power is illustrated by a sustained application of nonlinear and quantum processes within the context of financial econometrics. We construct a discrete-time agent-based model for a population of competing companies whose evolutionary performance is evaluated by a secondary market made up of value investors and arbitrageurs. This allows for game equilibria and nonlinear/chaotic dynamics to be addressed. The overarching goal is to address the emergence of complex phenomena with regards to market efficiency, with particular emphasis on the role that agent behavior, arbitrage, and multifractal signatures have in the dynamics of financial returns and volatility.

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