Simple Forecasting Heuristics that Make us Smart: Evidence from Different Market Experiments
| Autor: | Mikhail Anufriev, Tomasz Makarewicz, Cars Hommes |
|---|---|
| Přispěvatelé: | Faculteit Economie en Bedrijfskunde, Equilibrium, Expectations & Dynamics / CeNDEF (ASE, FEB), Behavioural Economics, Quantitative Economics (ASE, FEB) |
| Rok vydání: | 2018 |
| Předmět: |
Economics
business.industry Heuristic Computer science 05 social sciences Aggregate behavior Machine learning computer.software_genre Empirical distribution function Set (abstract data type) Simple (abstract algebra) 0502 economics and business Genetic algorithm Market environment Artificial intelligence 050207 economics Heuristics business General Economics Econometrics and Finance computer 050205 econometrics |
| Zdroj: | Journal of the European Economic Association, 17(5), 1538-1584. Wiley-Blackwell |
| ISSN: | 1542-4774 1542-4766 |
| DOI: | 10.1093/jeea/jvy028 |
| Popis: | In this paper we address the question of how individuals form expectations and invent, reinforce, and update their forecasting rules in a complex world. We do so by fitting a novel, parsimonious, and empirically validated genetic algorithm learning model with explicit heterogeneity in expectations to a set of laboratory experiments. Agents use simple linear first order price forecasting rules, adapting them to the complex evolving market environment with a Genetic Algorithm optimization procedure. The novelties are: (1) a parsimonious experimental foundation of individual forecasting behavior; (2) explanation of individual and aggregate behavior in three different experimental settings, (3) improved one- and 50-period ahead forecasting of experiments, and (4) characterization of the mean, median, and empirical distribution of forecasting heuristics. The median of the distribution of GA forecasting heuristics can be used in designing or validating simple Heuristic Switching Models. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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