Metaheuristics optimization of financial trading strategies for single asset trading

Derdour, Abdeslem

dc.contributor.author	Derdour, Abdeslem
dc.contributor.other	Tadjine, M., Directeur de thèse
dc.date.accessioned	2023-10-30T08:05:53Z
dc.date.available	2023-10-30T08:05:53Z
dc.date.issued	2023
dc.identifier.other	EP00697
dc.identifier.uri	http://repository.enp.edu.dz/jspui/handle/123456789/10943
dc.description	Mémoire de Projet de Fin d’Études : Automatique: Alger, École Nationale Polytechnique : 2023	fr_FR
dc.description.abstract	The study focused on optimizing technical trading systems using metaheuristic techniques, such as Particle Swarm Optimization and Multi-Objective Evolutionary Algorithms. The results indicate that these methods significantly enhance the performance and robustness of the trading systems. Traditional training approaches were found to be susceptible to overfitting, a concern that was mitigated through WalkForward Optimization. The choice of the objective function was highlighted as crucial in improving system robustness. It is recommended that practitioners carefully select the objective functionand optimization method for designing and evaluating technical trading systems.	fr_FR
dc.language.iso	en	fr_FR
dc.subject	Low Frequency Technical Trading Systems (LFTTS)	fr_FR
dc.subject	Walk Forward Optimization (WFO)	fr_FR
dc.subject	Crypto-currencies	fr_FR
dc.subject	Particle Swarm Optimizer (PSO)	fr_FR
dc.subject	Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D)	fr_FR
dc.title	Metaheuristics optimization of financial trading strategies for single asset trading	fr_FR
dc.type	Thesis	fr_FR