Learning-to-forecast experiment. A simulation approach with genetic algorithm
Metadata
Show full item recordcomunitat-uji-handle:10234/158176
comunitat-uji-handle2:10234/71324
comunitat-uji-handle3:10234/111700
comunitat-uji-handle4:
TFG-TFMMetadata
Title
Learning-to-forecast experiment. A simulation approach with genetic algorithmAuthor (s)
Tutor/Supervisor; University.Department
Jiménez Fernández, Eduardo; Universitat Jaume I. Departament d'EconomiaDate
2018-07-12Publisher
Universitat Jaume IAbstract
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. [-]
Subject
Description
Treball Final de Grau en Economia. Codi: EC1049. Curs acadèmic: 2017/2018
Type
info:eu-repo/semantics/bachelorThesisRights
info:eu-repo/semantics/openAccess
This item appears in the folowing collection(s)
- Grau en Economia [289]
The following license files are associated with this item: