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{ "item_title" : "Machine Learning Models in Quantitative Finance", "item_author" : [" Reactive Publishing", "Danny Munrow", "Vincent Bisette "], "item_description" : "Reactive PublishingMachine 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 workflowsFinance moves fast. So should your models.", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/9/79/828/000/9798280005969_b.jpg", "price_data" : { "retail_price" : "42.99", "online_price" : "42.99", "our_price" : "42.99", "club_price" : "42.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Machine Learning Models in Quantitative Finance|Reactive Publishing

Machine Learning Models in Quantitative Finance : A Practical Guide to Forecasting, Pricing, and Signal Generation

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Overview

Reactive PublishingMachine 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.

This item is Non-Returnable

Details

  • ISBN-13: 9798280005969
  • ISBN-10: 9798280005969
  • Publisher: Independently Published
  • Publish Date: April 2025
  • Dimensions: 9 x 6 x 1.22 inches
  • Shipping Weight: 1.29 pounds
  • Page Count: 490

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