Artificial Intelligence, Learning and Computation in Economics and Finance

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This book presents frontier research on the use of computational methods to model complex interactions in economics and finance. Artificial Intelligence, Machine Learning and simulations offer effective means of analyzing and learning from large as well as new types of data. These computational tools have permeated various subfields of economics, finance, and also across different schools of economic thought. Through 16 chapters written by pioneers in economics, finance, computer science, psychology, complexity and statistics/econometrics, the book introduces their original research and presents the findings they have yielded.

Theoretical and empirical studies featured in this book draw on a variety of approaches such as agent-based modeling, numerical simulations, computable economics, as well as employing tools from artificial intelligence and machine learning algorithms. The use of computational approaches to perform counterfactual thought experiments are also introduced, which help transcend the limits posed by traditional mathematical and statistical tools.

The book also includes discussions on methodology, epistemology, history and issues concerning prediction, validation, and inference, all of which have become pertinent with the increasing use of computational approaches in economic analysis.


Author(s): Ragupathy Venkatachalam
Series: Understanding Complex Systems
Publisher: Springer
Year: 2023

Language: English
Pages: 330
City: Cham

Acknowledgements
Contents
Contributors
1 Computational Thinking in Economics and Finance: Introductory Remarks
1.1 Artificial Intelligence and Machine Learning: The Future?
1.2 Shu-Heng Chen and Computational Social Sciences
1.3 Brief Overview of the Contributions
References
2 Uncomputabilities, Games, Axioms, Proofs and Artificial Intelligence
2.1 Introductory Notes
2.2 The Hydra-Hercules Battle as an Uncomputable Arithmetic Game
2.3 The Hydra-Hercules Battle as a Busy Beaver Game
2.4 Notes on Axioms, Rules of Inference and Proofs in Mathematics and Logic
2.5 Concluding Notes
References
3 Logic and Epistemology in Behavioral Economics
3.1 Introduction
3.2 Forms of Complexity?
3.3 Dynamic Complexity and Knowledge
3.4 Knowledge Problems of Computational Complexity
3.5 Complexity Foundations of Bounded Rationality and Limited Knowledge
3.6 Conclusions
References
4 Agent-Based Computational Economics: Overview and Brief History
4.1 Introduction
4.2 Completely Agent-Based Modeling (c-ABM)
4.3 C-ABM: A Mathematics for the Real World?
4.4 Agent-Based Computational Economics
4.5 ACE Agent Rationality
4.6 ACE Agent Stochasticity
4.7 ACE Research Objectives
4.8 Brief History of ACE
4.9 Concluding Remarks
References
5 Sequential Monte Carlo Squared for Agent-Based Models
5.1 Introduction
5.2 The Particle Filter Within an SMC Sampler
5.3 Test Example
5.4 Monte Carlo Simulations
5.5 Conclusion
References
6 Toward a General Model of Financial Markets
6.1 Introduction
6.1.1 Efficient Market Hypothesis
6.1.2 Behavioral Finance
6.2 Broad Concept of Subjective Rationality
6.3 Candidate Decision Theories
6.3.1 Decision Theory 1
6.3.2 Decision Theory 2
6.3.3 Decision Theory 3
6.3.4 Decision Theory 4
6.3.5 Decision Theory 5
6.4 Paradoxes and Rationality
6.4.1 Insurance and Gambling
6.4.2 Equity Premium Puzzle
6.5 Fuzzy Representation of Market Efficiency
6.6 Conclusion
References
7 Sand Castles and Financial Systems: A Sandpile Metaphor
7.1 Prelude
7.2 Introduction
7.3 The Model
7.4 Public Intervention
7.5 Structure and Performance of the Financial System
7.6 Conclusions and Further Research Plans
Annex 1
Annex 2
References
8 A Systematic Review of Investor Attention: Measurements, Implications, and Future Directions
8.1 Introduction
8.2 Attention-Grabbing Events
8.3 Measurements of Investor Attention
8.3.1 Indirect Measures
8.3.2 Direct Measures
8.4 Investor Attention and Market Dynamics
8.4.1 Effects of Investor Attention
8.4.2 The Implications of Investor Inattention
8.5 Future Directions
8.6 Conclusion
References
9 What is the Market? The Essential Teachings from an AI Market Experiment
9.1 The Limitations of the Libertarian Idea of the Market and Our New Interest
9.2 Settlement Mechanism of the Exchange Market
9.2.1 Preliminaries
9.2.2 Numerical Examples at the Bitcoin Exchange
9.2.3 A Time-Scale Problem
9.3 AI Market Experiment
9.3.1 Experiment by the Use of the U-Mart System
9.3.2 Nakajima-Mori Agent Configuration for the Generation of Price Movement Similar to Its Referential Price Time Series
9.4 The Length Frequency Distribution Hinted by the Turing Machine
9.4.1 Fully Random Iterated Cellular Automata
9.4.2 Digit Length Distribution
9.5 Market Strategy Composition and Its Effect
References
10 Market Power and the Hayek Hypothesis: An Experimental Investigation
10.1 Introduction
10.1.1 The Hayek Hypothesis and the Experimental Evidence
10.1.2 Traders with Market Power
10.1.3 How Should We View These Inconsistent Results?
10.1.4 Cognitive Ability and Economic Behavior
10.1.5 Research Questions and Hypotheses
10.2 Experimental Design
10.2.1 The Double Auction Experiments
10.2.2 Market Structures
10.2.3 Measuring Cognitive Ability
10.3 Results and Discussions
10.3.1 Market Power and Price Convergence
10.3.2 Cognitive Ability and Market Power
10.3.3 Cognitive Ability and Market Performance
10.3.4 Cognitive Ability and Convergence Towards the Competitive Equilibrium
10.3.5 Revelation of Market Information
10.4 Conclusion
References
11 Counterfactual Thinking and Causal Mediation: An Application to Female Labour Force Participation in India
11.1 Introduction and Motivation
11.1.1 Female Labour Force Participation in India as a Problem of Causal Mediation Analysis
11.2 Causal Structure and Methods
11.2.1 Identification and Estimation
11.3 Data and Variables
11.4 Results
11.5 Discussion
References
12 When Supply and Demand do NOT Meet: Sraffa's Critique of Economic Theory Restated
12.1 Prelude to a Critique of Economic Theory
12.2 Sraffa's Method for His Critique: The Self-replacing System
12.3 The System to Be Replicated and the Computation of Self-replacing Prices
12.3.1 Period of Production, the Harvest, and the Market Day
12.3.2 The Production Cycle and the Harvest Under Self-replacement
12.3.3 The Surplus Available for Distribution and Its Consumption
12.3.4 Definition of Self-replacing Prices
12.3.5 Distribution of the Surplus
12.4 Computation of Self-replacing Prices
12.5 Sraffian Schemes and General Equilibrium
12.6 Sraffa's Critique Is Circumvented by Postulation
12.7 An Algorithmic Digital Laboratory for an In-Depth Study
12.7.1 Numerical Definition of the Quantities Involved: left parenthesis bold upper A comma bold italic script l comma bold b right parenthesis(A, ell, b)
12.7.2 The Set {bold dd} of all Possible Discrete Functional Distributions
12.7.3 Computation of the Domain StartSet bold p Subscript StartSet bold d EndSet Baseline comma bold r Subscript StartSet bold d EndSet Baseline comma w Subscript StartSet bold d EndSet Baseline EndSet{p{d}, r{d}, w{d} } for the Self-Replacing Prices, Profit Rates, and Wage Rates
12.7.4 Population of Producers and Workers: n Subscript pinπ and n Subscript script lnell
12.7.5 Consumer Incomes, bold yy
12.7.6 Consumption cc and upper CC
12.8 Results of the Numerical Simulations
12.8.1 Virtual (Neoclassical) Economies
12.8.2 In Search of the Neoclassical Market Clearing Equilibria—Condition D)
12.8.3 Results Concerning the Personal Income Distributions
12.9 Conclusions
12.10 Sraffa's View on the Incapacity of the Economic System to Endogenously Determine Distribution
12.11 Existence of Equilibrium
12.12 Sources of Personal Income
12.13 Appendix. Distribution, Prices and Wage Rate once the Profit Rates are Given
References
13 Visualizing the Roles of Frequent Terms in LTEs Following Two Economic Crisis Trigger Articles
13.1 Introduction
13.2 Literature Review
13.3 Methodology
13.3.1 Generating LTE Corpora
13.3.2 Corpus Processing
13.3.3 Calculating Unique LTE Thresholds
13.3.4 Ranking the Top 25 Words
13.4 Findings and Discussion
13.4.1 Persistent Curves in One Corpus Only
13.4.2 Persistent Curves in Both Corpora
13.4.3 Different Terms with Similar Curves
13.4.4 Additional Interesting Curves Produced in the Study
13.5 Conclusions
Appendices
13.6 Appendix
13.7 Appendix
References
14 Design and Performance Metrics for Autonomous Human-Machine Teams and Systems (A-HMT-S)
14.1 Introduction
14.2 Justification for Interdependence Theory
14.3 A New Approach With Metrics
14.4 Field Results
14.5 Vulnerability
14.6 Vulnerability from the use of Deception
14.7 Future Research
14.8 Conclusion
References
15 Thirty-Five Years of Computational Economics
15.1 Tournaments to Explore the Iterated Prisoner’s Dilemma
15.2 Generalising Axelrod’s Iterated Prisoner’s Dilemma Tournaments
15.3 Enter Machine Learning: The Genetic Algorithm
15.4 From Genetic Algorithms to Agent-Based Models
15.5 The Issue of the Best Risk Profile for Risky Decision Making
15.6 Simulation, Not Optimisation
15.7 Connection with Shu-Heng Chen
15.8 Conclusion
References
16 Extending Herbert Simon's “Science of Design”: the Role of Collaboration and Users in Development of Technically Advanced Systems
16.1 Introduction
16.2 A Process Perspective of Technology Development
16.2.1 Search Process, Including the System Design
16.2.2 Recursing Through Task Trees
16.2.3 Bootstrapping Out of Uncertainty
16.3 Collaborative Development
16.3.1 The “Blackboard” with Fragmented Accumulation of Technology
16.3.2 Organization of Collaborative Development
16.4 Coping with Users in the ‘Outer Environment’
16.4.1 Irreconcilable Requirements of Users
16.4.2 Bootstrapping in specifications and requirements
16.4.3 Representatives, Intermediaries and Not Just Users
16.4.4 Testing of Subsystems
16.5 Synthesis
16.6 Conclusion
References