Learning-to-forecast experiment. A simulation approach with genetic algorithm
Metadatos
Mostrar el registro completo del ítemcomunitat-uji-handle:10234/158176
comunitat-uji-handle2:10234/71324
comunitat-uji-handle3:10234/111700
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TFG-TFMMetadatos
Título
Learning-to-forecast experiment. A simulation approach with genetic algorithmAutoría
Tutor/Supervisor; Universidad.Departamento
Jiménez Fernández, Eduardo; Universitat Jaume I. Departament d'EconomiaFecha de publicación
2018-07-12Editor
Universitat Jaume IResumen
In this work, A Genetic Algorithm (GA) is used to study the behavior in a Learning to Forecast Experiment in which short-term expectations have been elicited. In particular, by using the results from a previous ... [+]
In this work, A Genetic Algorithm (GA) is used to study the behavior in a Learning to Forecast Experiment in which short-term expectations have been elicited. In particular, by using the results from a previous experiment with human subjects, the same market is simulated implementing GA. After the training process, the simulation with GAs is able to produce similar results compared to the experiment with human subjects in markets with both negative and positive feedbacks. In addition, simulations in the long-run, i.e. considering 100 and 1000 periods, show a market convergence to the fundamental price of the market and the stability of the GA agents’ predictions. We tested how the simulated price reacts by introducing 3 shocks. Finally, the algorithm is also tested in market shocks. The sudden change in the market conditions shows the capability of the algorithm to rapidly adapt and answer to this changes in order to return to the equilibrium conditions. [-]
Palabras clave / Materias
Descripción
Treball Final de Grau en Economia. Codi: EC1049. Curs acadèmic: 2017/2018
Tipo de documento
info:eu-repo/semantics/bachelorThesisDerechos de acceso
info:eu-repo/semantics/openAccess
Aparece en las colecciones
- Grau en Economia [292]
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