The Oxford Handbook of Computational Economics and Finance

ISBN : 9780199844371

Shu-Heng Chen; Mak Kaboudan; Ye-Rong Du
784 Pages
171 x 248 mm
Pub date
Feb 2018
Oxford Handbooks
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The Oxford Handbook of Computational Economics and Finance provides a survey of both the foundations of and recent advances in the frontiers of analysis and action. It is both historically and interdisciplinarily rich and also tightly connected to the rise of digital society. It begins with the conventional view of computational economics, including recent algorithmic development in computing rational expectations, volatility, and general equilibrium. It then moves from traditional computing in economics and finance to recent developments in natural computing, including applications of nature-inspired intelligence, genetic programming, swarm intelligence, and fuzzy logic. Also examined are recent developments of network and agent-based computing in economics. How these approaches are applied is examined in chapters on such subjects as trading robots and automated markets. The last part deals with the epistemology of simulation in its trinity form with the integration of simulation, computation, and dynamics. Distinctive is the focus on natural computationalism and the examination of the implications of intelligent machines for the future of computational economics and finance. Not merely individual robots, but whole integrated systems are extending their immigration to the world of Homo sapiens, or symbiogenesis.


1. Computational Economics in the Era of Natural Computationalism: 50 Years after The Theory of Self-Reproducing Automata; Shu-Heng Chen, Mak Kaboudan, and Ye-Rong Du; 2. Dynamic Stochastic General EquilibriumModels: A Computational Perspective; Michel Juillard; 3.Tax-rate Rules for Reducing Government Debt: An Application of Computational Methods for Macroeconomic Stabilization; G. C. Lim and Paul D. McNelis; 4.Solving Rational Expectations Models; Jean Barthelemy and Magali Marx; 5.Computable General EquilibriumModels for Policy Evaluation and Economic Consequence Analysis; Ian Sue Wing and Edward J. Balistreri; 6. Multifractal Models in Finance: Their Origin, Properties, and Applications; Thomas Lux and Mawuli Segnon; 7. Particle Filters for Markov Switching Stochastic Volatility Models; Yun Bao, Carl Chiarella, and Boda Kang; 8. Economic and Financial Modeling with Genetic Programming - A Review; Cliodhna Tuite, Michael O'Neill, and Anthony Brabazon; 9. Algorithmic Trading Based on Biologically-inspired Algorithms; Vassilios Vassiliadis and Georgios Dounias; 10. Algorithmic Trading in Practice; Peter Gomber and Kai Zimmermann; 11. Computational Spatiotemporal Modeling of Southern California Home Prices; Mak Kaboudan; 12. Business Applications of Fuzzy Logic; Petr Dostal and Chia-Yang Lin; 13. Modeling of Desirable Socio-economic Networks; Akira Namatame and Takanori Komatsu; 14. ComputationalModels of Financial Networks, Risk and Regulatory Policies; Kimmo Soramaki; 15. From Minority Games to$-Games; Jorgen Vitting Andersen; 16. An Overview and Evaluation of The CAT Market Design Competition; Tim Miller, Jinzhong Niu, Martin Chapman, and Peter McBurney; 17. Agent-Based Macroeconomic Modeling and Policy Analysis: The Eurace@Unibi Model; Herbert Dawid, Simon Gemkow, Philipp Harting, Sander van der Hoog, and Michael Neugart; 18. Agent-Based Models for Economic Policy Design: Two Illustrative Examples; Frank Westerhoff and Reiner Franke; 19. Computational Economic Modeling of Migration; Anna Klabunde; 20. Computational Industrial Economics - A Generative Approach to Dynamic Analysis in Industrial Organization; Myong-Hun Chang; 21. Agent-Based Modeling for Financial Markets; Giulia Iori and James Porter; 22. Agent-Based Models of the Labor Market; Michael Neugart and Matteo Richiardi; 23. The Emerging Standard Neurobiological Model of Decision Making: Strengths, Weaknesses, and Future Directions; Shih-Wei Wu and Paul W. Glimcher; 24. The Epistemology of Simulation, Computation and Dynamics in Economics; K. Vela Velupillai; Index

About the author: 

Shu-Heng Chen is a Distinguished Professor in the Department of Economics, Vice-President, Director of the AI-ECON Research Center, and the organizer of Experimental Economics Laboratory at National Chengchi University.; Mak Kaboudan is a former Professor of Economics and Statistics at the University of Redlands' School of Business.; Ye-Rong Du is a Postdoctoral research fellow at AI-ECON Research Center, National Chengchi University.

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