Reactive Publishing
Machine Learning Models in Quantitative Finance: A Practical Guide to Forecasting, Pricing, and Signal Generation
By Vincent Bisette
Unlock the power of machine learning in financial markets, without needing a PhD in data science.
This hands-on guide delivers a focused, tactical approach to integrating machine learning into quantitative finance. Designed for analysts, traders, and finance professionals, this book demystifies the process of applying ML to real-world financial data for forecasting, pricing models, and signal generation.
Inside, you’ll discover:
Practical ML models tailored for time series, options pricing, and strategy development
Step-by-step implementation using Python and Excel
Techniques to engineer features, reduce overfitting, and optimize model performance
Case studies on using random forests, XGBoost, and neural networks for alpha generation
How to build ML pipelines that integrate seamlessly with existing quant workflows
Finance moves fast. So should your models.
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-9798280005969
Quantité disponible : Plus de 20 disponibles
Vendeur : Grand Eagle Retail, Bensenville, IL, Etats-Unis
Paperback. Etat : new. Paperback. Reactive Publishing Machine Learning Models in Quantitative Finance: A Practical Guide to Forecasting, Pricing, and Signal GenerationBy Vincent BisetteUnlock the power of machine learning in financial markets-without needing a PhD in data science.This hands-on guide delivers a focused, tactical approach to integrating machine learning into quantitative finance. Designed for analysts, traders, and finance professionals, this book demystifies the process of applying ML to real-world financial data for forecasting, pricing models, and signal generation.Inside, you'll discover: Practical ML models tailored for time series, options pricing, and strategy developmentStep-by-step implementation using Python and ExcelTechniques to engineer features, reduce overfitting, and optimize model performanceCase studies on using random forests, XGBoost, and neural networks for alpha generationHow to build ML pipelines that integrate seamlessly with existing quant workflowsYou won't find generic theory or fluff-just battle-tested tools and frameworks that work in volatile markets. Whether you're building your first predictive model or fine-tuning your algo trading stack, this book gives you the edge.Finance moves fast. So should your models. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9798280005969
Quantité disponible : 1 disponible(s)
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 L2-9798280005969
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 L2-9798280005969
Quantité disponible : Plus de 20 disponibles
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
Etat : New. In. N° de réf. du vendeur ria9798280005969_new
Quantité disponible : Plus de 20 disponibles
Vendeur : CitiRetail, Stevenage, Royaume-Uni
Paperback. Etat : new. Paperback. Reactive Publishing Machine Learning Models in Quantitative Finance: A Practical Guide to Forecasting, Pricing, and Signal GenerationBy Vincent BisetteUnlock the power of machine learning in financial markets-without needing a PhD in data science.This hands-on guide delivers a focused, tactical approach to integrating machine learning into quantitative finance. Designed for analysts, traders, and finance professionals, this book demystifies the process of applying ML to real-world financial data for forecasting, pricing models, and signal generation.Inside, you'll discover: Practical ML models tailored for time series, options pricing, and strategy developmentStep-by-step implementation using Python and ExcelTechniques to engineer features, reduce overfitting, and optimize model performanceCase studies on using random forests, XGBoost, and neural networks for alpha generationHow to build ML pipelines that integrate seamlessly with existing quant workflowsYou won't find generic theory or fluff-just battle-tested tools and frameworks that work in volatile markets. Whether you're building your first predictive model or fine-tuning your algo trading stack, this book gives you the edge.Finance moves fast. So should your models. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9798280005969
Quantité disponible : 1 disponible(s)
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Taschenbuch. Etat : Neu. Neuware - Reactive Publishing Machine Learning Models in Quantitative Finance: A Practical Guide to Forecasting, Pricing, and Signal GenerationBy Vincent BisetteUnlock the power of machine learning in financial markets, without needing a PhD in data science.This hands-on guide delivers a focused, tactical approach to integrating machine learning into quantitative finance. Designed for analysts, traders, and finance professionals, this book demystifies the process of applying ML to real-world financial data for forecasting, pricing models, and signal generation.Inside, you'll discover: - Practical ML models tailored for time series, options pricing, and strategy development- Step-by-step implementation using Python and Excel- Techniques to engineer features, reduce overfitting, and optimize model performance- Case studies on using random forests, XGBoost, and neural networks for alpha generation- How to build ML pipelines that integrate seamlessly with existing quant workflowsFinance moves fast. So should your models. N° de réf. du vendeur 9798280005969
Quantité disponible : 2 disponible(s)