March 2025
Intermediate to advanced
214 pages
5h 26m
French
Content preview from Apprentissage par renforcement pour la finance
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Chapitre 6. Trading algorithmique
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Les systèmes automatisés de négociation d'actions sont largement utilisés par les principales sociétés d'investissement. Alors que certains d'entre eux sont simplement des moyens d'automatiser l'exécution d'ordres d'achat ou de vente particuliers émis par un gestionnaire de fonds humain, d'autres poursuivent des stratégies de négociation compliquées qui s'adaptent à l'évolution des conditions du marché.
Bostrom (2014)
Les géants de la finance tels que Goldman Sachs et un grand nombre des plus grands fonds spéculatifs sont tous en train de basculer sur des systèmes pilotés par l'IA qui peuvent prévoir les tendances du marché et effectuer des transactions mieux que les humains.
Maney (2017)
Au chapitre 3, l'agent Deep Learning (DQL) apprend à prédire la direction future du mouvement du prix d'un instrument financier. Nous appelons cela un jeu de prédiction financière. Il est naturel d'interpréter le jeu de prédiction comme un agent DQL apprenant à négocier algorithmiquement sur les marchés financiers. La prédiction d'un mouvement à la hausse peut être interprétée comme la prise d'une position longue sur l'instrument financier en question. De même, la prédiction d'un mouvement à la baisse est interprétée comme la prise d'une position courte. Au fil du temps, les prédictions peuvent également impliquer le maintien ...
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