Market Dynamics subject PhD Thesis Katalin Boer-Sorb

On January 25, Katalin Boer-Sorbán has defended her PhD thesis entitled “Agent-Based Simulation of Financial Markets”. Her promotor is Prof.dr. A. de Bruin, Professor at the Department of Computer Science, Erasmus School of Economics, Erasmus University Rotterdam.

The aim of this thesis is to contribute to the understanding of market dynamics by extending the agent-based computational approach. It provides the user with a flexible mechanism to implement many of the varying and hardly observable aspects of stock markets and traders' behavior. In this way it can contribute to the understanding of market dynamics as it can be used both as a test bed to replicate and evaluate existing market models, and to compare dynamics of multiple ASMs, as well as a tool to conduct experiments with new models and traders.

About Katalin Boer-Sorbán
Katalin Boer-Sorbán was born in Miercurea-Ciuc, Romania, on 1 June, 1976. She completed her secondary education witch specialization informatics at Márton Áron High School, in Miercurea-Ciuc. In 1994 she started her higher education at Babeş-Bolyai University, Faculty of Mathematics and Computer Science, Cluj-Napoca, Romania. She received her B.Sc. degree in Computer Science, in 1998, and her M.Sc. degree with major in Information Systems, specialization Database Management, in 1999. During her studies, Katalin obtained fellowships at the Budapest University of Technology, and the Eötvös Lóránd University, Budapest, Hungary within the Central European Exchange Program for University Studies (CEEPUS).

In 2000, Katalin has joined the Computer Science group at the Econometric Institute of the Erasmus School of Economics at Erasmus University Rotterdam, The Netherlands. Here, first, she carried out research in the area of biometric authentication methods. Then, in 2002 she became a Ph.D. candidate in the area of agent-based simulation of financial markets. She has presented parts of her Ph.D. research at several international conferences and workshops. A version of Chapter 5 of this thesis is published in the Computational Intelligence journal. During her Ph.D. studies Katalin has been involved in teaching Bachelor and Master courses at Erasmus School of Economics, and at the Business Administration Program, at Rotterdam School of Management. As per 2008, Katalin, is affiliated with the Econometric Institute of the Erasmus School of Economics as an assistant professor.

Abstract
The dynamics of financial markets is subject of much debate among researchers and financial experts trying to understand and explain how financial markets work and traders behave. Diversified explanations result from the complexity of markets, and the hardly observable aspects of price formation mechanisms and of participants' motivation behind trading decisions. In an attempt to provide a better understanding of market dynamics, studies in the realm of agent-based computational economics represent markets from bottom-up.

The aim of this thesis is to contribute to the understanding of market dynamics by extending the agent-based computational approach. In order to achieve our goal we propose a modular, continuous-time, agent-based trading environment, with individual, autonomous representation of market participants. In order to be able to develop such an environment we first analyze and compare real and artificial stock markets (ASMs). Based on this analysis we propose a conceptual framework to describe real markets. By enriching the framework with design and implementation issues we get a multi-dimensional taxonomy of artificial stock markets. ABSTRACTE, the proposed modular environment is an operational form of these frameworks. ABSTRACTE is aimed to embed the common aspects of real markets that exhibit big variations and are rarely represented in artificial stock markets. This environment provides the user with a flexible mechanism to implement many of the varying and hardly observable aspects of stock markets and traders' behavior. In this way it can contribute to the understanding of market dynamics as it can be used both as a test bed to replicate and evaluate existing market models, and to compare dynamics of multiple ASMs, as well as a tool to conduct experiments with new models and traders.

More Information
Pictures of the Defense
Full text of the Dissertation