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Artificial Life Analysis of Financial Market Behavior

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Artificial Life Analysis of Financial Market Behavior Scholars' Mine Doctoral Dissertations Student Theses and Dissertations Fall 2007 Architecting system of systems: artificial life analysis of financial market behavior Nil Hande Ergin Follow this and additional works at: https://scholarsmine.mst.edu/doctoral_dissertations Part of the Systems Engineering Commons Department: Engineering Management and Systems Engineering Recommended Citation Ergin, Nil Hande, "Architecting system of systems: artificial life analysis of financial market behavior" (2007). Doctoral Dissertations. 1988. https://scholarsmine.mst.edu/doctoral_dissertations/1988 This thesis is brought to you by Scholars' Mine, a service of the Missouri S&T Library and Learning Resources. This work is protected by U. S. Copyright Law. Unauthorized use including reproduction for redistribution requires the permission of the copyright holder. For more information, please contact [email protected]. ARCHITECTING SYSTEM OF SYSTEMS: ARTIFICIAL LIFE ANALYSIS OF FINANCIAL MARKET BEHAVIOR by NIL HANDE ERGIN A DISSERTATION Presented to the Faculty of the Graduate School of the UNIVERSITY OF MISSOURI-ROLLA In Partial Fulfillment of the Requirements for the Degree DOCTOR OF PHILOSOPHY in SYSTEMS ENGINEERING 2007 _______________________________ _______________________________ C. H. Dagli, Co-Advisor D. Enke, Co-Advisor _______________________________ _______________________________ S. Ramakrishnan S. Grasman _______________________________ D. Tauritz iii ABSTRACT Today’s systems typically do not stand alone in isolation. Often a system fits within a System of Systems, a network of interconnected systems that often exhibits unpredictable behavior. This study is motivated by the challenges of understanding the emergent system level behavior of System of Systems given the opaque characteristics of social processes and continuously changing operating and environmental conditions. An artificial life based framework for modeling System of Systems is presented as an analysis technique. The framework comprises cognitive architectures embedded in multi- agent models. Financial markets are selected as an analysis domain to demonstrate the framework since they are a good example of self-organizing systems that exhibit System of Systems characteristics, specifically emergence on a grand scale. The effects of different mechanisms on system level market dynamics are analyzed. In particular, the effects of the covering mechanism, learning mechanism and bias mechanism are analyzed. A trader-based architecture is proposed to formulate a trader decision model that combines bias mechanisms with learning mechanisms. A prediction accuracy based Learning Classifier System is used to model the trader learning mechanism. Markov processes are utilized to model the bias mechanism of traders. Simulation experiments are generated using the Anylogic5.1™ software. Homogenous rational expectations equilibrium is utilized as the benchmark for comparison of results from the hybrid proposed model. The model derived from the framework contributes to understanding the market behavior and potential sources of deviation from efficient market equilibrium. The artificial life based framework provides a flexible way of modeling sub-systems of System of Systems and captures the adaptive and emergent behavior of the system. iv ACKNOWLEDGMENTS I would like to thank my advisors, Dr. Cihan H. Dagli and Dr. David Enke, for their continuous support, guidance and friendship throughout this study. Their vision, enthusiasm and dedication to science and education have been influential. There are no words to express my gratitude, admiration and affection for them. It has been a privilege to work under their supervision. I would like to thank my committee member, Dr. Sreeram Ramakrishnan, for his guidance and feedback at critical points in my research. I would like to thank my other committee members, Dr. Scott Grasman and Dr. Daniel Tauritz, for their valuable suggestions throughout this study. All together my committee’s insights enriched my dissertation immensely. I would like to thank the Engineering Management and Systems Engineering Department for providing me funding during my study. I have been fortunate to work among fellow students in the Smart Engineering Systems Lab and the Laboratory for Investment and Financial Engineering whom I found to be intellectually stimulating. I would like to thank all my friends for their friendship, the list of their names will simply not fit in this page. I am grateful and indebted to my mother and father, Yildiz and Erkan Kilicay, for their love, sacrifices and contributions throughout my life. I am grateful to my brother, Ozgur Kilicay, for supporting me and standing by my side throughout my tough days. Of course I would be remiss if I did not mention the extensive support and love of my mother and father-in-law, Sabahat and Ali Ergin, as well as my brother-in- law, Taner Ergin. I would also like to remember in memory of my grandfather, Dr. Ismet Gunes, whose life story and his dedication to medical science has been an inspiration on me. Finally and most specially, this study is dedicated to my husband, Okan Ergin, who finds the best in me and stands by me with his endless patience, strength, friendship and love through the life journey. v TABLE OF CONTENTS Page ABSTRACT ....................................................................................................................iii ACKNOWLEDGMENTS ................................................................................................. iv LIST OF ILLUSTRATIONS............................................................................................. ix LIST OF TABLES............................................................................................................. xi NOMENCLATURE ......................................................................................................... xii SECTION 1. INTRODUCTION...................................................................................................... 1 1.1. THE PROBLEM AND MOTIVATION............................................................. 1 1.2. OBJECTIVES..................................................................................................... 3 1.3. APPROACH ....................................................................................................... 5 1.4. ORGANIZATION OF THE THESIS................................................................. 7 2. TERMINOLOGY....................................................................................................... 8 2.1. DEFINITION OF SYSTEM OF SYSTEMS...................................................... 8 2.2. DEFINITION OF SYSTEMS ARCHITECTING .............................................. 8 2.3. DEFINITION OF AN AGENT .......................................................................... 9 2.4. DEFINITION OF ARTIFICIAL LIFE ............................................................. 11 3. SYSTEM OF SYSTEMS AS COMPLEX ADAPTIVE SYSTEMS....................... 13 3.1. COMPLEX ADAPTIVE SYSTEMS ............................................................... 13 3.1.1. Emergence.............................................................................................. 15 3.1.2. Self-organization. ................................................................................... 15 3.2. SYSTEM OF SYSTEMS VS COMPLEX ADAPTIVE SYSTEMS ............... 16 3.3. COMPLEXITY THEORY................................................................................ 17 3.4. SYSTEM ARCHITECT’S TOOLBOX: THE ROLE OF ARTIFICIAL LIFE.................................................................................................................. 19 3.4.1. Cellular Automata. ................................................................................. 21 3.4.2. Agent-Based Models. ............................................................................. 21 3.4.3. Evolutionary Algorithm. ........................................................................ 23 3.4.3.1 Genetic algorithms. ....................................................................23 vi 3.4.3.2 Learning classifier systems.........................................................24 3.4.3.3 Genetic programming .................................................................24 3.4.4. Animats………………………………………………………………... 25 3.4.5. Cognitive Architecture Studies……………………………………… .. 25 3.4.6. Swarm Intelligence……………………………………………………..27 3.4.6.1 Ant colony optimization. ............................................................27 3.4.6.2 Particle swarm optimization…………………………………... 27 3.4.7. Multi-Agent Systems (MAS)………………………………………….. 28 3.4.7.1 Agent architectures……………………………………………. 28 3.4.7.2 Agent-system architectures…………………………………….29 3.4.7.3 Agent infrastructures...................................................................29 3.4.7.4 Design methodology. ..................................................................30 3.5. SUMMARY………………………………………………………………….. 30 4. ARTIFICIAL LIFE FRAMEWORK FOR MODEL FORMULATION OF SYSTEM OF SYSTEMS................................................................................... 32 4.1. COMPLEX SYSTEMS ARCHITECTING...................................................... 33 4.2. THE FRAMEWORK........................................................................................ 34 4.2.1. Sub-system Models. ............................................................................... 35 4.2.2. Environment Models. ............................................................................
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