Valuation of American options using machine learning: beyond Longstaff–Schwartz and hybrid models

This work explores the potential of different machine learning (ML) algorithms in the valuation of American options (Aos), contrasting them with the Longstaff–Schwartz (L–S) model. To carry out this research, the algorithms K-Nearest Neighbors (KNN), Random Forest (RF), Multi-Layer Perceptron (MLP)...

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Autori principali:	Maria Vivas-Redondo, María Coronado-Vaca, Esther Vaquero-Lafuente
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Emerald Publishing 2025-05-01
Serie:	Seonmul yeongu
Soggetti:	American options valuation Machine learning Longstaff-Schwartz Predictive analytics KNN (K-Nearest Neighbors) RF (Random Forest) MLP (Multi-Layer Perceptron) CNN (Convolutional Neural Network)
Accesso online:	https://www.emerald.com/jdqs/article-pdf/33/3/170/10357630/jdqs-11-2024-0044en.pdf
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