Items related to LLM-Powered Quantitative Finance: A Practical Guide...
LLM-Powered Quantitative Finance: A Practical Guide to Building AI Agents for Trading and Risk Management - Softcover
Synopsis
Reactive Publishing
Discover how large language models are transforming quantitative finance in this practical guide to building intelligent AI agents.
This book explores the integration of LLMs with quantitative trading strategies, risk modeling, and decision-making systems. Readers will learn the fundamentals of designing, training, and deploying AI agents capable of analyzing market data, processing financial news and sentiment, and supporting robust risk management frameworks.
Key topics include:
• Architecting LLM-based trading agents
• Integrating real-time market data and alternative datasets
• Implementing sentiment analysis pipelines for financial decision-making
• Developing risk forecasting and portfolio management systems
• Best practices for testing, backtesting, and safely deploying autonomous AI systems in live trading environments
Whether you are a quantitative analyst, developer, or finance professional interested in the intersection of artificial intelligence and capital markets, this book provides clear explanations, code examples, and architectural patterns to help you build production-ready solutions.
Ideal for readers with basic knowledge of Python, machine learning concepts, and financial markets.
"synopsis" may belong to another edition of this title.
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LLM-Powered Quantitative Finance: A Practical Guide to Building AI Agents for Trading and Risk Management
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LLM-Powered Quantitative Finance
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LLM-Powered Quantitative Finance
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LLM-Powered Quantitative Finance (Paperback)
Print on DemandSeller: Grand Eagle Retail, Bensenville, IL, U.S.A.
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Paperback. Condition: new. Paperback. Reactive Publishing Discover how large language models are transforming quantitative finance in this practical guide to building intelligent AI agents. This book explores the integration of LLMs with quantitative trading strategies, risk modeling, and decision-making systems. Readers will learn the fundamentals of designing, training, and deploying AI agents capable of analyzing market data, processing financial news and sentiment, and supporting robust risk management frameworks. Key topics include: - Architecting LLM-based trading agents- Integrating real-time market data and alternative datasets- Implementing sentiment analysis pipelines for financial decision-making- Developing risk forecasting and portfolio management systems- Best practices for testing, backtesting, and safely deploying autonomous AI systems in live trading environments Whether you are a quantitative analyst, developer, or finance professional interested in the intersection of artificial intelligence and capital markets, this book provides clear explanations, code examples, and architectural patterns to help you build production-ready solutions. Ideal for readers with basic knowledge of Python, machine learning concepts, and financial markets. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9798184944708
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LLM-Powered Quantitative Finance (Paperback)
Print on DemandSeller: CitiRetail, Stevenage, United Kingdom
Seller rating 5 out of 5 stars
Paperback. Condition: new. Paperback. Reactive Publishing Discover how large language models are transforming quantitative finance in this practical guide to building intelligent AI agents. This book explores the integration of LLMs with quantitative trading strategies, risk modeling, and decision-making systems. Readers will learn the fundamentals of designing, training, and deploying AI agents capable of analyzing market data, processing financial news and sentiment, and supporting robust risk management frameworks. Key topics include: - Architecting LLM-based trading agents- Integrating real-time market data and alternative datasets- Implementing sentiment analysis pipelines for financial decision-making- Developing risk forecasting and portfolio management systems- Best practices for testing, backtesting, and safely deploying autonomous AI systems in live trading environments Whether you are a quantitative analyst, developer, or finance professional interested in the intersection of artificial intelligence and capital markets, this book provides clear explanations, code examples, and architectural patterns to help you build production-ready solutions. Ideal for readers with basic knowledge of Python, machine learning concepts, and financial markets. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9798184944708
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