INDIVIDUAL EXPECTATIONS AND AGGREGATE BEHAVIOR IN LEARNING-TO-FORECAST EXPERIMENTS

Models with heterogeneous interacting agents explain macro phenomena through interactions at the micro level. We propose genetic algorithms as a model for individual expectations to explain aggregate market phenomena. The model explains all stylized facts observed in aggregate price fluctuations and...

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Bibliographic Details
Published inMacroeconomic dynamics Vol. 17; no. 2; pp. 373 - 401
Main Authors Hommes, Cars, Lux, Thomas
Format Journal Article
LanguageEnglish
Published New York, USA Cambridge University Press 01.03.2013
Cambridge Univ. Press
Subjects
Analysis
Behavior
Economic theory
Economics
Erwartungsbildung
Evolutionärer Algorithmus
Experiments
Forecasting
Genetic algorithms
Human subjects
Laboratories
Learning
Lernprozess
Macroeconomics
Preis
Prognoseverfahren
Rationality
Sample variance
Simulation
Studies
Test
Theorie
Volatility
Learning
Experimental Economics
Heterogeneous Expectations
Genetic Algorithms
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Summary:Models with heterogeneous interacting agents explain macro phenomena through interactions at the micro level. We propose genetic algorithms as a model for individual expectations to explain aggregate market phenomena. The model explains all stylized facts observed in aggregate price fluctuations and individual forecasting behaviour in recent learning-to-forecast laboratory experiments with human subjects (Hommes et al. 2007), simultaneously and across different treatments.
Bibliography:SourceType-Scholarly Journals-1
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ISSN:1365-1005
1469-8056
DOI:10.1017/S1365100511000162