March 2025
Intermediate to advanced
214 pages
5h 26m
French
Content preview from Apprentissage par renforcement pour la finance
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Partie II. Augmentation des données
La deuxième partie du livre couvre les concepts sur et les approches pour générer des données pour le Deep Learning financier :
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Le chapitre 4 met en œuvre des approches de génération de données basées sur la simulation de Monte Carlo (MCS). Une approche consiste à ajouter du bruit blanc à une série chronologique financière existante. Une autre consiste à simuler les données d'une série chronologique financière sur la base d'un modèle financier (une équation différentielle stochastique).
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Le chapitre 5 montre comment utiliser les réseaux adversaires génératifs (GAN) de l'IA, ou plus précisément de deep learning (DL), pour générer des données de séries temporelles financières qui sont cohérentes et statistiquement indiscernables de la série temporelle financière cible. Une telle série temporelle cible peut être la série de rendement historique d'une action d'une société (pense aux actions Apple) ou les cotations de change historiques (pense au taux de change EUR/USD).
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