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"Generative AI for Finance: Building Agents for Research and Trading" Generative AI is rapidly reshaping how financial institutions research markets, build strategies, and execute trades. This book is written for quantitative researchers, data scientists, technologists, and forward-looking portfolio managers who want to move beyond toy demos and build robust agentic systems for real-world finance. Blending practical engineering with rigorous quantitative thinking, it shows how to turn large language models into reliable collaborators for idea generation, analysis, and decision support. You will learn how to construct end-to-end pipelines that feed high-quality market and textual data into transformers, retrieval systems, and agent frameworks. Core topics include prompt design for financial tasks, retrieval-augmented generation over filings and news, and orchestration patterns that let agents reason, plan, and call tools such as risk engines, databases, and execution venues. The book also develops skills in evaluation, backtesting, and MLOps so that research and trading agents are measurable, debuggable, and governable rather than opaque black boxes. The text assumes comfort with Python and basic statistics but reviews the essentials of quantitative finance, machine learning, and reinforcement learning as needed. Examples emphasize production-grade design-covering performance engineering, compliance, security, and model risk-making this a practical guide for building agentic AI systems that can survive contact with real markets and real regulators.
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Generative AI for Finance: Building Agents for Research and Trading
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Paperback. Zustand: new. Paperback. "Generative AI for Finance: Building Agents for Research and Trading"Generative AI is rapidly reshaping how financial institutions research markets, build strategies, and execute trades. This book is written for quantitative researchers, data scientists, technologists, and forward-looking portfolio managers who want to move beyond toy demos and build robust agentic systems for real-world finance. Blending practical engineering with rigorous quantitative thinking, it shows how to turn large language models into reliable collaborators for idea generation, analysis, and decision support.You will learn how to construct end-to-end pipelines that feed high-quality market and textual data into transformers, retrieval systems, and agent frameworks. Core topics include prompt design for financial tasks, retrieval-augmented generation over filings and news, and orchestration patterns that let agents reason, plan, and call tools such as risk engines, databases, and execution venues. The book also develops skills in evaluation, backtesting, and MLOps so that research and trading agents are measurable, debuggable, and governable rather than opaque black boxes.The text assumes comfort with Python and basic statistics but reviews the essentials of quantitative finance, machine learning, and reinforcement learning as needed. Examples emphasize production-grade design-covering performance engineering, compliance, security, and model risk-making this a practical guide for building agentic AI systems that can survive contact with real markets and real regulators. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Bestandsnummer des Verkäufers 9798896652342
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 'Generative AI for Finance: Building Agents for Research and Trading'Generative AI is rapidly reshaping how financial institutions research markets, build strategies, and execute trades. This book is written for quantitative researchers, data scientists, technologists, and forward-looking portfolio managers who want to move beyond toy demos and build robust agentic systems for real-world finance. Blending practical engineering with rigorous quantitative thinking, it shows how to turn large language models into reliable collaborators for idea generation, analysis, and decision support.You will learn how to construct end-to-end pipelines that feed high-quality market and textual data into transformers, retrieval systems, and agent frameworks. Core topics include prompt design for financial tasks, retrieval-augmented generation over filings and news, and orchestration patterns that let agents reason, plan, and call tools such as risk engines, databases, and execution venues. The book also develops skills in evaluation, backtesting, and MLOps so that research and trading agents are measurable, debuggable, and governable rather than opaque black boxes.The text assumes comfort with Python and basic statistics but reviews the essentials of quantitative finance, machine learning, and reinforcement learning as needed. Examples emphasize production-grade design-covering performance engineering, compliance, security, and model risk-making this a practical guide for building agentic AI systems that can survive contact with real markets and real regulators. Bestandsnummer des Verkäufers 9798896652342
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Taschenbuch. Zustand: Neu. Generative AI for Finance | Building Agents for Research and Trading | Victor Trex | Taschenbuch | Englisch | 2025 | NobleTrex Press | EAN 9798896652342 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. Bestandsnummer des Verkäufers 135842025
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