Complexity and Artificial Markets (eBook)

Preface 5
Acknowledgements 8
Contents 9
Contributors 14
Market Mechanisms 17
Zero-Intelligence TradingWithout Resampling 18
1.1 Introduction 18
1.2 The Model 19
1.3 Results 22
1.4 Conclusions 28
References 29
Understanding the Price Dynamics of a Real Market Using Simulations: The Dutch Auction of the Pescara Wholesale Fish Market 30
2.1 Introduction 30
2.2 Market Description 31
2.3 Modeling the Buyers’ Bidding Behavior 32
2.4 Simulations and Validation 35
2.5 Discussion and Conclusions 38
2.6 Appendix 39
References 40
Market Behavior Under Zero-Intelligence Trading and Price Awareness 41
3.1 Introduction 41
3.2 The Model 42
3.3 Results 45
3.4 Conclusions 50
References 51
Evolution and Decision Making 52
Evolutionary Switching between Forecasting Heuristics: An Explanation of an Asset- Pricing Experiment 53
4.1 Introduction 53
4.2 Laboratory Experiment 54
4.3 Evolutionary Model 58
4.4 Simulations of the Model 62
4.5 Conclusion 64
References 64
Prospect Theory Behavioral Assumptions in an Artificial Financial Economy 66
5.1 Introduction 67
5.2 The Model 68
5.3 Results and Discussion 71
5.4 Conclusions 76
References 77
Computing the Evolution of Walrasian Behaviour 78
6.1 Introduction 78
6.2 The Vega–Redondo Economy Model 80
6.3 The Behavioural Rules Set 81
6.4 Walrasian Equilibrium Revisited 85
6.5 Conclusions 85
References 87
Multidimensional Evolving Opinion for Sustainable Consumption Decision 88
7.1 Introduction 88
7.2 Multidimensional Opinion 89
7.3 Computer Simulation and Results 93
7.4 Conclusion 97
References 97
Information Economics 99
Local Interaction, Incomplete Information and Properties of Asset Prices 100
8.1 Introduction 100
8.2 The Economy 103
8.3 Simulation Results 107
8.4 Conclusion 112
References 113
Long-Term Orientation in Trade 115
9.1 Introduction 116
9.2 Long- vs. Short-Term Orientation 116
9.3 The Effect of LTO on Trade Processes 118
9.4 Representation in Agents 120
9.5 Experimental Verification 123
9.6 Conclusion 125
References 126
Agent-Based Experimental Economics in Signaling Games 128
10.1 Three Approaches to Study Signaling Games 128
10.2 Human-Subject Behaviour in a Signaling Game Experiment 130
10.3 Modelling Artificial Agents’ Behaviour in Signalling Games 131
10.4 Parameters and Scenarios of the Simulation 134
10.5 Some Simulations Results 134
10.6 Conclusions 135
References 136
Methodological Issues 137
Why do we need Ontology for Agent-Based Models? 138
11.1 Introduction 138
11.2 From Ontology in Philosophy and Computer Science to Ontological Design for ABM 139
11.3 From Individuals to Spatial Entities: What Entities Make Sense from the Ontological Standpoint? 141
11.4 Model vs. "Real” World and Ontological Test 144
11.5 Conclusion 148
References 149
Production and Finance in EURACE 151
12.1 Introduction 152
12.2 The EURACE Project 152
12.3 The Financial Management Module 155
12.4 Conclusion 162
References 162
Serious Games for Economists 163
13.1 Introduction 163
13.2 Individual-Based Methods 165
13.3 System Theories 166
13.4 Mathematical Biology and Game Theory 167
13.5 Simulation Methods 168
13.6 AI in Computer Games 169
13.7 Conclusions 172
References 173
Invited Speakers 176
Computational Evolution 177
14.1 Introduction 177
14.2 Catastrophic Events in Macro Evolution 179
14.3 Variations of Micro Evolution 183
14.4 Bottom-Up Evolution by Digital Biochemistry 189
14.5 Summary and Outlook 193
References 194
Artificial Markets: Rationality and Organisation 196
15.1 Introduction 196
15.2 Relationships in Markets 198
15.3 The Marseille Fish Market (Saumaty) 200
15.4 A Simple Market Model 202
15.5 Trading Relationships Within the Market 203
15.6 A Little Formal Analysis 204
15.7 An Artificial Market Based on a Simpler Modelling Approach 210
15.8 Other Forms of Market Organisation 217
15.9 MERITAN a Market Based on Dutch Auctions 218
15.10 The Empirical Evidence 220
15.11 Price Dynamics 220
15.12 Loyalty Again 222
15.13 Comparison Between Auctions and the Decentralised Market in an Agent- Based Model 224
15.14 Common Features 225
15.15 The Auction Market 226
15.16 Profit Generated by the Rules 228
15.17 Simulations 228
15.18 Results with a Large Supply 229
15.19 Results with a Limited Supply 232
15.20 The Market when Both Sides Learn 232
15.21 Conclusion 232
References 234