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Handbook of Computational Economics: Heterogeneous Agent Modeling,
Volume Four, focuses on heterogeneous agent models, emphasizing
recent advances in macroeconomics (including DSGE), finance,
empirical validation and experiments, networks and related
applications. Capturing the advances made since the publication of
Volume Two (Tesfatsion & Judd, 2006), it provides high-level
literature with sections devoted to Macroeconomics, Finance,
Empirical Validation and Experiments, Networks, and other
applications, including Innovation Diffusion in Heterogeneous
Populations, Market Design and Electricity Markets, and a final
section on Perspectives on Heterogeneity.
This special issue of the Journal of Economics and Statistics is
devoted to the use of agent-based models for economic policy
advice. It presents a collection of research papers in different
fields of applications. Special emphasis is laid on discussing the
potential and possible limitations of agent-based models for
economic policy advice. The editorial provides an overview on the
role of agent-based modeling in economic policy referring also to
the papers presented. Furthermore, it highlights the strength of
the approach, i.e., the explicit microfoundation and the modeling
of heterogenous agents. Finally, we also report on current
limitations of the method with regard to economic policy advice and
point at some areas deserving further research.
Computational finance, an exciting new cross-disciplinary
research area, draws extensively on the tools and techniques of
computer science, statistics, information systems, and financial
economics. This book covers the techniques of data mining,
knowledge discovery, genetic algorithms, neural networks,
bootstrapping, machine learning, and Monte Carlo simulation. These
methods are applied to a wide range of problems in finance,
including risk management, asset allocation, style analysis,
dynamic trading and hedging, forecasting, and option pricing. The
book is based on the sixth annual international conference
Computational Finance 1999, held at New York University's Stern
School of Business.
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