A NASDAQ market simulation : insights on a major market from the science of complex adaptive systems

This pioneering book describes the applications of agent-based modeling to financial markets. It presents a new paradigm for finance, where markets are treated as complex systems whose behavior emerges as a result of interactions of market participants, market institutions, and market rules. This includes both a presentation of the conceptual model and its software implementation. It also summarises the result of the profound research on the successful practical application of this new approach to answer questions regarding the Nasdaq Stock Market s decimalization that was implemented in 2001. The book presents conceptual foundations for modeling markets as complex systems. It describes the agent-based model of the Nasdaq stock market, including strategies used by market-makers and investors, market participants interactions, and impacts of rules and regulations. It includes analyses of simulation behavior, comparison with the behaviors observed in the real-world markets (existence of fat tails, spread clustering, etc.), and predictions about possible outcomes of decimalization. A framework for calibrating the market behavior and individual market-makers strategies to historical data is also presented. Contents......Page 12 Preface......Page 8 1.1 Introduction......Page 16 1.2 What is Agent-Based Modeling?......Page 23 1.3 Nasdaq Market Overview......Page 27 1.4 Nasdaq Simulation Model Overview......Page 28 1.5 Existing Market Modeling and Simulation Work......Page 30 1.5.1 Complexity and Agent-Based Modeling......Page 31 1.5.2 Financial Markets and Agent-Based Modeling......Page 32 1.5.3 Artificial Intelligence, Machine Learning, and Other Approaches to Modeling Agent Strategies......Page 34 2.1 Introduction......Page 36 2.3 Summary of the Glosten-Milgrom Model......Page 38 2.3.1 GM Model, Information, and Bayesian Updates......Page 39 2.3.3 Tick-Size Effects......Page 41 2.4 Extension of the GM Model to Multinomial Prices......Page 42 2.4.2 Updating the Probability in the Recursive Case......Page 43 2.4.3 Setting the Bid-Ask Prices......Page 45 2.4.4 The Binomial Case......Page 46 2.5 Multinomial Additions......Page 47 2.6 Extension of GM to Incorporate Inventory......Page 49 2.6.1 Convergence of Beliefs......Page 50 2.7 Price Dynamics......Page 51 3.1 Introduction......Page 54 3.2.1 Market......Page 56 3.2.2 Strategies......Page 57 3.2.3 Evolutionary Selection of Strategies and Learning Strategies......Page 61 3.3 An Outline of the Computer Model......Page 63 3.4.1 Tick Size Effects on Price Discovery......Page 65 3.4.2.1 Effects of Parasitism......Page 71 3.4.2.2 Effects of Tick Size......Page 72 3.5 Aggregate Behavior of the Market......Page 73 3.6 Fat Tails......Page 74 3.6.1 Herding Effects......Page 75 3.6.2 Range of Fat Tails......Page 77 3.7 Spread Clustering......Page 78 3.9 Profitability of Market Makers' Strategies......Page 80 3.12 Market's Predictability......Page 81 3.14 Effects of Learning and Evolution......Page 82 3.15 Conclusions......Page 84 4.1 Introduction......Page 86 4.2.1 Spread Clustering with Learning and Basic Inventory Market Makers......Page 87 4.2.2 Spread Clustering with Other Dealer Types......Page 89 4.3.1 Real World Relevance of the Spread Clustering Results......Page 91 4.4 Validity of the Observed Clustering Effects......Page 92 4.5 Possible Reasons for Observed Clustering of Spread Sizes......Page 94 4.6 Conclusions......Page 95 5.1 Types of Reinforcement-Learning Dealers......Page 96 5.2 The Reinforcement-Learning Framework and Incentive Structure......Page 99 5.3 Learning in the Market......Page 101 6.1 Introduction......Page 104 6.2 Results......Page 105 6.3.2 Calibration on the Individual Level......Page 107 6.4 Quantitative Behaviors: Calibrating Simulated Strategies Against Real-World Strategies......Page 108 6.4.1 Parameter Discovery for Basic Dealers......Page 110 6.4.2.1 Time series comparisons......Page 112 6.4.2.2 Statistical analysis......Page 114 6.4.3 Identification of Analytic Parasites......Page 115 6.4.4 Results - Basic Dealers......Page 116 6.4.5 Results - Volume Dealers and Parasitic Dealers......Page 118 6.5 Wealth Effects Analysis......Page 123 6.6 Conclusions......Page 125 7.1.1 Time Series Regularization Procedure......Page 126 7.1.2 Price Response to the Number of Transactions and Their Volume......Page 127 7.2 Phase Transitions Analysis......Page 129 7.3 Conclusions......Page 130 8.1 Introduction......Page 134 8.2.1 Negative Effects on the Price Discovery Process......Page 136 8.2.2 Possible Volume Increases......Page 137 8.2.3 Ambiguous Investor Wealth Effects......Page 138 8.2.6 More Effective Parasitic Strategies......Page 139 8.3 Conclusions and Directions for the Future......Page 140 9.1 Qualitative Scenario Investigation......Page 142 9.4 Agent Soup of the Day......Page 143 Appendix A: The Agent-Based Model Software......Page 146 A.1 Graphical User Interface......Page 147 A.2 Menus......Page 150 A.3.1 Market and Pricing Charts......Page 151 A.3.3 Investor Performance......Page 154 A.4 Interacting with the Market......Page 155 A.5 Batch Mode......Page 156 A.6 Basic Description of Object Simulation Framework......Page 157 Bibliography......Page 160 Index......Page 166 "This book describes the applications of agent-based modeling to financial markets. It presents a new paradigm for finance, where markets are treated as complex systems whose behavior emerges as a result of interactions of market participants, market institutions, and market rules. This includes both a presentation of the conceptual model and its software implementation. It also summarises the result of the profound research on the successful practical application of this new approach to answer questions regarding the Nasdaq Stock Market's decimalization that was implemented in 2001"--Jacket Describes the applications of agent-based modeling to financial markets. Presenting conceptual foundations for modeling markets as complex systems, this book describes the agent-based model of the Nasdaq stock market, including strategies used by market-makers and investors, market participants interactions, and impacts of rules and regulations.