Complexity and Artificial Markets

In recent years, agent-based simulation has become a widely accepted tool when dealing with complexity in economics and other social sciences. The contributions presented in this book apply agent-based methods to derive results from complex models related to market mechanisms, evolution, decision ma...

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Bibliographic Details
Other Authors: Schredelseker, Klaus (Editor), Hauser, Florian (Editor)
Format: eBook
Language:English
Published: Berlin, Heidelberg Springer Berlin Heidelberg 2008, 2008
Edition:1st ed. 2008
Series:Lecture Notes in Economics and Mathematical Systems
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
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505 0 |a Market Mechanisms -- Zero-Intelligence Trading Without Resampling -- Understanding the Price Dynamics of a Real Market Using Simulations: The Dutch Auction of the Pescara Wholesale Fish Market -- Market Behavior Under Zero-Intelligence Trading and Price Awareness -- Evolution and Decision Making -- Evolutionary Switching between Forecasting Heuristics: An Explanation of an Asset-Pricing Experiment -- Prospect Theory Behavioral Assumptions in an Artificial Financial Economy -- Computing the Evolution of Walrasian Behaviour -- Multidimensional Evolving Opinion for Sustainable Consumption Decision -- Information Economics -- Local Interaction, Incomplete Information and Properties of Asset Prices -- Long-Term Orientation in Trade -- Agent-Based Experimental Economics in Signaling Games -- Methodological Issues -- Why do we need Ontology for Agent-Based Models? -- Production and Finance in EURACE -- Serious Games for Economists -- Invited Speakers -- Computational Evolution -- Artificial Markets: Rationality and Organisation 
653 |a Complex Systems 
653 |a Computer Application in Social and Behavioral Sciences 
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653 |a System theory 
653 |a Quantitative Economics 
653 |a Mathematical physics 
653 |a Econometrics 
653 |a Theoretical, Mathematical and Computational Physics 
700 1 |a Hauser, Florian  |e [editor] 
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520 |a In recent years, agent-based simulation has become a widely accepted tool when dealing with complexity in economics and other social sciences. The contributions presented in this book apply agent-based methods to derive results from complex models related to market mechanisms, evolution, decision making, and information economics. In addition, the applicability of agent-based methods to complex problems in economics is discussed from a methodological perspective. The papers presented in this collection combine approaches from economics, finance, computer science, natural sciences, philosophy, and cognitive sciences