Network Theory and Agent-Based Modeling in Economics and Finance (eBook)

Contents 5
Complexity and Emergence: A New Paradigm for Economic Modeling 7
1 Introduction 7
1.1 Behavioral Rules Versus Optimization: Why Agent-Based Models? 9
1.2 Networks as Building Blocks of Economic and Financial Complexity 10
2 Interactive Models with Boundedly Rational Agents 10
3 Financial and Economic Linkages 12
4 Summary and Outlook 14
References 14
Interactive Models with Boundedly Rational Agents 15
Information Selection Efficiency in Networks: A Neurocognitive-Founded Agent-Based Model 16
1 Introduction 17
1.1 Emotions and Economic Decision-Making 18
1.2 Deliberative Heuristics 18
1.3 Social Transmission 19
2 The Agent Zero Information Selection Model 20
2.1 Information Signals 20
2.2 Agent Cognition: The Deliberative Component 21
2.3 Agent Cognition: The Affective Component 22
2.4 Individual, Social, and Total Disposition to Act 22
3 Implementation 24
4 Results and Discussion 25
4.1 Deliberative Module Analysis 26
4.2 Affective Module Analysis 27
4.3 The Deliberative and Social Components 30
4.4 The Affective and Social Interaction 31
4.5 The Deliberative and Affective Interaction 33
4.6 Information Selection with Agent Zero Population 35
5 Conclusion 36
References 38
Diversification by Self-reinforcement of Preferences and Change of Interaction Type 40
1 Introduction 40
2 Model 42
2.1 Social Network 42
2.2 Type of Interactions 42
2.3 Preferences and Heterogeneity of Agents 43
3 Behaviors of Agents 43
3.1 Choices: Best Response Rule 43
3.2 Movable for New Neighbors 44
3.3 Self-reinforcement of Preferences 45
3.4 Decision Errors 46
3.5 Changes in Interaction Types 46
4 Simulation Settings 47
5 Simulation Results 48
5.1 Self-reinforcement and Mobility 48
5.2 Decision Errors 51
5.3 Changes of Interaction Types 56
6 Discussion 61
7 Conclusion 62
References 63
Price Distortions and Public Information: Theory, Experiments, and Simulations 64
1 Introduction 64
2 The Model 66
2.1 Information Set 66
2.2 Agents' Decisions 67
2.3 Endogenous Order Flow 71
2.4 Transactions 72
3 Laboratory Experiment 74
4 Model Calibration 75
4.1 Results 76
4.2 Monte Carlo Simulations 78
5 Corroborating Evidence: Observed Versus Simulated Data 81
6 Conclusions 82
7 Public Signal Scenario 83
7.1 Sophisticated Proposers 83
7.2 Sophisticated Receivers 84
8 Common Signal Scenario 85
8.1 Sophisticated Traders 86
8.2 Transactions 86
9 Robustness: Does Market Configuration Matter? 88
References 89
Order Book on Financial Networks 91
1 Introduction 91
2 The Model 94
2.1 Simulative Steps of Microstructure 95
2.2 Stylized Facts of Financial Markets 99
3 Model Parameters and Market Stability 100
3.1 Subjective Factors 101
3.2 Objective Factors 102
4 Market Signals, Pressure and Financial Networks 103
4.1 Information, Imitation and Social Topology 103
5 Conclusive Remarks 108
References 110
Detection of Factors Influencing Market Liquidity Using an Agent-Based Simulation 115
1 Introduction 115
2 Market Liquidity 117
2.1 Market Liquidity and the Four Liquidity Indicators 117
3 Artificial Market Model 119
3.1 Order Process 120
3.2 Learning Process 121
4 Simulation Results and Discussion 121
4.1 Overview 121
4.2 Validation of Proposed Artificial Market 122
4.3 Results 123
4.4 Relationship Among Four Liquidity Indicators 129
4.5 Market Liquidity Based on Original Meaning of Resiliency 130
5 Conclusion 134
References 135
Macroscopic Properties in Economic System and Their Relations 136
1 Introduction 136
2 Database Statistical Properties 138
3 Properties at Fixed Time 138
3.1 Power-Law Distribution 139
3.2 Log-Normal Distribution 139
4 Properties in Short-Term Period 140
4.1 Equilibrium or Quasi-equilibrium State of System 140
4.2 Short-Term Growth Properties 141
4.3 Inactive Rate of Firms 143
5 Long-Term Properties 144
5.1 Firm-Age Distribution 144
5.2 Long-Term Growth Properties 145
6 Relationships Among Fixed-Time, Short-Term, and Long-Term Properties 146
6.1 Derivation of Fixed-Time Properties from Short-Term Properties 146
6.2 Derivation of Long-Term Properties from Short-Term Properties 153
6.3 Relationship Between Short-Term Growth and Inactive Rate of Firms 156
7 Conclusion and Discussion 157
References 158
How Much Income Inequality is Fair? Nash Bargaining Solution and Its Connection to Entropy 161
1 Introduction 161
2 Potential Game-Theoretic Framework: Summary of Past Work 163
2.1 Utility of a Fair Opportunity for a Better Future 164
2.2 Modeling the Disutility of a Job 165
2.3 Effective Utility from a Job 166
2.4 Equilibrium Income Distribution 166
3 Entropy as a Measure of Fairness: An Intuitive Explanation of S = -sumi=1n pilnpi 168
4 Nash Bargaining Solution 170
5 NBS of the Income Distribution Game 172
6 Summary and Conclusions 175
References 176
A Limit Cycle View of Inequality 177
1 Introduction 177
2 The Model: Cognitive and Physical Workers 182
2.1 Aggregate Income and Inequality 184
3 Logit Dynamic 186
4 Dynamics of Income and Inequality 188
4.1 Discussion 194
5 Variations in the Search Distribution 197
5.1 Characterization of the Limit Cycles 199
6 Conclusion 201
7 Appendix 202
7.1 Proofs in Sect. 2 202
References 203
Simulated Maximum Likelihood Estimation of Agent-Based Models in Economics and Finance 204
1 Introduction 204
2 Estimation Versus Calibration in Economic Modeling 206
2.1 Calibration 207
2.2 Estimation 209
3 Agent-Based Models in Economics and Finance 210
4 Simulated Maximum Likelihood Estimator 211
5 Agent-Based Model with Behavioral Switching 213
6 Monte Carlo Simulation Study 214
6.1 Setup 215
6.2 Estimation Performance of the Switching Parameter 216
6.3 Shape of the Simulated Log-likelihood Function 219
6.4 Estimation Performance of the Two-Type Model 220
6.5 Shape of the Simulated 4D Log-likelihood 222
7 Conclusion 223
8 Appendix 224
References 225
Emergent Urban Morphologies in an Agent-Based Model of Housing 228
1 Introduction 228
2 Background 232
3 Model 234
4 Results 236
4.1 Population Density, Home Prices, and Floor Areas 236
4.2 Competition Between Two Income Groups 237
4.3 Competition Between Two Transportation Modes 238
4.4 Effects of Highways 239
5 Conclusions 244
References 245
The Transferability of Human Capital, the Brain Drain and the Brain Gain 248
1 Introduction 248
2 Literature Review 250
3 Model 251
4 Utility Maximisation 252
4.1 The Case Where an Individual Does not Attempt to Migrate 252
4.2 The Case Where an Individual Attempts to Migrate 253
5 The Migration Decision 255
6 Home Country’s Human Capital 257
7 The Brain Drain or the Brain Gain in Steady State and the Short Run 260
8 Concluding Remarks 262
References 263
Is Life (or at Least Socioeconomic Aspects of It) Just Spin and Games? 265
1 Introduction 265
2 Collective Decision-Making by Agents: Spins… 268
3 Collective Decision-Making by Agents: …and Games 271
4 In Lieu of a Conclusion 279
References 280
Financial and Economic Linkages 282
An Agent-Based Model of BCVA and Systemic Risk 283
1 Introduction 283
2 Credit Risk and Value Adjustments 284
2.1 CVA/DVA 285
2.2 BCVA 286
3 Literature Review 286
4 Model 287
4.1 Financial Network 287
4.2 Contracts and Payments 288
4.3 Derivative Network 289
4.4 BCVA 290
4.5 Parameters 290
5 Results 291
5.1 Systemic Risk Versus Leverage 292
5.2 Systemic Risk Versus Connectivity 294
5.3 Systemic Risk Versus Premiums 297
6 Conclusion 297
References 298
Additional Default Probability in Consideration of Firm's Network 299
1 Introduction 299
2 Model 302
2.1 Single Neighbor Case 302
2.2 Multiple Neighbors Case 304
3 Numerical Experiment 304
4 Conclusion 307
5 Appendix 308
References 310
Systemic Risk: Fire-Walling Financial Systems Using Network-Based Approaches 311
1 Introduction 311
2 Nodes and Links of a Financial Network 313
3 Contagion via Interbank Linkages 317
3.1 Contagion via Default Spreading 317
3.2 Contagion via Valuation Adjustments 319
3.3 Strategic Reactions and Network Structure 320
4 Contagion via Fire Sale of Assets 321
4.1 Contagion via Overlapping Portfolios 321
4.2 Fire-Walling Financial Networks 322
5 Conclusion and Future Directions 324
References 326
Spectral and Network Method in Financial Time Series Analysis: A Study on Stock and Currency Market 329
1 Introduction 329
2 System and Data 330
3 Correlation Matrix 331
4 Spectral Properties 333
4.1 Eigenvalue Distribution 336
4.2 Localization of Eigenvector: Eigenvector Entropy 338
4.3 Eigenvector 339
5 Network Analysis 343
5.1 Network Properties 343
5.2 Average Degree 346
6 Average Clustering Coefficient 347
7 Conclusion 347
References 348
Research on Loss Absorption of Financial Group 350
1 Introduction 351
2 Proposed Method 355
2.1 Modeling of the Balance Sheet 355
2.2 Consideration of the Reserve Ratio (RR) and Capital Adequacy Ratio (CAR) 357
2.3 Implementation of Agent-Based Modeling 358
2.4 Strengthen Management Foundation by Regional Bank Financial Group 361
3 Verification Results 362
3.1 Verification of Change in the Number of a Chain Reaction of Failures Resulting from Financial Groups of Regional Banks 362
3.2 Evaluation of Verification Result 365
4 Conclusion 369
References 370
Knowledge-Driven Approaches for Financial News Analytics 371
1 Introduction 371
2 Methods in Financial News Analytics 373
2.1 Sentiment Analysis 373
2.2 Event and Topic Recognition 376
3 News Analytics and Financial Variables 378
4 Tools and Resources for Financial News Analytics 380
4.1 Linguistic Resources in Finance 380
4.2 Resources for Financial Sentiment Analysis 384
4.3 Ontologies in Finance 385
5 Addressing the Domain-Specific Needs in Financial News Analytics 387
5.1 Understanding Investor Perspective in Sentiment Analysis 387
5.2 Computing Sentiment in Finance 389
5.3 Neural Networks for Event Detection 392
6 Conclusions 395
References 395
Network-Based Policies Versus Tax Evasion 401
1 Introduction 402
2 Agent-Based Model Implementation 403
3 Nash Equilibrium and Social Norms 411
4 Optimal Audit Policies 414
5 Conclusions 422
References 423
Network Games: The Cooperative Approach 425
1 Introduction 426
2 Preliminaries 429
2.1 Cooperative Games 430
2.2 Bi-cooperative Games 431
2.3 Consistency of the LG Value 433
3 Network Games 436
3.1 The Myerson Value and the Position Value 437
3.2 Allocation Rules Based on Multilateral Interactions 439
4 Bi-cooperative Network Games 442
4.1 The Position Value for Bi-cooperative Network Games 443
4.2 The Myerson Value for Bi-cooperative Network Games 446
5 Application Possibilities 450
References 452