Reactive Publishing
Discover how to make your trading models transparent, trustworthy, and regulator-ready.
In the fast-moving world of quantitative trading, black-box machine learning models present serious challenges. Regulators demand transparency, risk managers require explanations, and successful deployment depends on understanding exactly why a model makes its predictions.
This book provides a clear, practical guide to explainable AI and interpretable machine learning techniques specifically for trading applications. You’ll learn how to implement and apply key methods such as SHAP, LIME, attention mechanisms, and model auditing to build more transparent quant strategies.
What You’ll Find Inside:
Written for quantitative traders, data scientists, and financial professionals, this book bridges the gap between advanced machine learning and the practical requirements of trading desks and compliance teams.
Whether you’re developing new strategies or working to meet evolving regulatory standards, this guide offers the technical foundation needed to create models that are both powerful and explainable.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Vendeur : California Books, Miami, FL, Etats-Unis
Etat : New. Print on Demand. N° de réf. du vendeur I-9798198684140
Quantité disponible : Plus de 20 disponibles
Vendeur : PBShop.store US, Wood Dale, IL, Etats-Unis
PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000. N° de réf. du vendeur L2-9798198684140
Quantité disponible : Plus de 20 disponibles
Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-Uni
PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000. N° de réf. du vendeur L2-9798198684140
Quantité disponible : Plus de 20 disponibles
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Taschenbuch. Etat : Neu. Neuware. N° de réf. du vendeur 9798198684140
Quantité disponible : 2 disponible(s)