Generative AI for Trading: Building Synthetic Data, Market Simulations, and Alpha Signals with LLMs and GANs: Quant Finance with Synthetic Data, GANs, and Large Language Models for Trading

Preston, James; Munrow, Danny

ISBN 13: 9798262461554

Published by Independently published, 2025

About this Item

Print on Demand.

Seller Inventory # I-9798262461554

Bibliographic Details

• Title: Generative AI for Trading: Building Synthetic Data, Market Simulations, and Alpha Signals with LLMs and GANs: Quant Finance with Synthetic Data, GANs, and Large Language Models for Trading
• Publisher: Independently published
• Publication Date: 2025
• Language: English
• ISBN 13: 9798262461554
• Binding: Soft cover
• Condition: New

About this title

Synopsis

Reactive Publishing

Harness the cutting edge of artificial intelligence to revolutionize your trading strategies.

Generative AI for Trading is a groundbreaking guide that bridges the gap between advanced machine learning models and real-world financial applications. This premium volume shows traders, quants, and AI enthusiasts how to use Generative Adversarial Networks (GANs), Large Language Models (LLMs), and synthetic data pipelines to create next-generation trading systems.

Inside, you’ll discover how to:

• Generate synthetic financial datasets to overcome data scarcity and bias.

• Build market simulations that mirror real-world complexity for robust backtesting.

• Engineer alpha-generating signals with GANs, diffusion models, and transformer-based LLMs.

• Integrate generative AI into risk management, portfolio optimization, and options trading.

• Deploy scalable Python frameworks for end-to-end trading research and automation.

With practical coding examples, step-by-step frameworks, and strategic insights, this book equips you to go beyond conventional algorithms and tap into the creative power of generative AI.

Whether you are a quant developer, algorithmic trader, or researcher, Generative AI for Trading will give you the tools to stay ahead in the evolving landscape of global markets.