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Data Analytics and Ai for Quantitative Risk Assessment and Financial Computation - Softcover

 
9798369362167: Data Analytics and Ai for Quantitative Risk Assessment and Financial Computation

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"This book explores the intersection of mathematics, statistics, computer science, finance, AI, and information science"--

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Galety, Mohammad Gouse (EDT); Claver, Jimbo Henri (EDT); Sriharsha, A. V. (EDT); Vajjhala, Narasimha Rao (EDT); Natarajan, Arul Kumar (EDT)
Published by Engineering Science Reference, 2024
ISBN 13: 9798369362167
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Mohammad Gouse Galety
Published by IGI Global, Hershey, PA, 2024
ISBN 13: 9798369362167
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Paperback. Condition: new. Paperback. In today's fast-paced financial landscape, professionals face an uphill battle in effectively integrating data analytics and artificial intelligence (AI) into quantitative risk assessment and financial computation. The constantly increasing volume, velocity, and variety of data generated by digital transactions, market exchanges, and social media platforms offer unparalleled financial analysis and decision-making opportunities. However, professionals need sophisticated AI technologies and data analytics methodologies to harness this data for predictive modeling, risk assessment, and algorithmic trading. Navigating this complex terrain can be daunting, and a comprehensive guide that bridges theory and practice is necessary. Data Analytics and AI for Quantitative Risk Assessment and Financial Computation is an all-encompassing reference for finance professionals, risk managers, data scientists, and students seeking to leverage the transformative power of AI and data analytics in finance. The book encapsulates this integration's theoretical underpinnings, practical applications, challenges, and future directions, empowering readers to enhance their analytical capabilities, make informed decisions, and stay ahead in the competitive financial landscape. The book provides a structured approach that covers foundational topics in quantitative risk assessment, data analytics, and AI, providing a roadmap for professionals to navigate the complexities of integrating AI and data analytics into financial practices. The book explores specific applications and methodologies, including machine learning algorithms for economic modeling and AI-driven strategies for risk management, providing readers with practical insights and strategies for success in the AI-driven financial future. With this book as a guide, professionals can confidently embrace the power of AI and data analytics to stay ahead in the ever-evolving economic landscape. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9798369362167

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Published by Engineering Science Reference, 2024
ISBN 13: 9798369362167
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Galety, Mohammad Gouse (EDT); Claver, Jimbo Henri (EDT); Sriharsha, A. V. (EDT); Vajjhala, Narasimha Rao (EDT); Natarajan, Arul Kumar (EDT)
Published by Engineering Science Reference, 2024
ISBN 13: 9798369362167
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Galety, Mohammad Gouse (EDT); Claver, Jimbo Henri (EDT); Sriharsha, A. V. (EDT); Vajjhala, Narasimha Rao (EDT); Natarajan, Arul Kumar (EDT)
Published by Engineering Science Reference, 2024
ISBN 13: 9798369362167
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Galety, Mohammad Gouse (EDT); Claver, Jimbo Henri (EDT); Sriharsha, A. V. (EDT); Vajjhala, Narasimha Rao (EDT); Natarajan, Arul Kumar (EDT)
Published by Engineering Science Reference, 2024
ISBN 13: 9798369362167
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ISBN 13: 9798369362167
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Paperback. Condition: new. Paperback. In today's fast-paced financial landscape, professionals face an uphill battle in effectively integrating data analytics and artificial intelligence (AI) into quantitative risk assessment and financial computation. The constantly increasing volume, velocity, and variety of data generated by digital transactions, market exchanges, and social media platforms offer unparalleled financial analysis and decision-making opportunities. However, professionals need sophisticated AI technologies and data analytics methodologies to harness this data for predictive modeling, risk assessment, and algorithmic trading. Navigating this complex terrain can be daunting, and a comprehensive guide that bridges theory and practice is necessary. Data Analytics and AI for Quantitative Risk Assessment and Financial Computation is an all-encompassing reference for finance professionals, risk managers, data scientists, and students seeking to leverage the transformative power of AI and data analytics in finance. The book encapsulates this integration's theoretical underpinnings, practical applications, challenges, and future directions, empowering readers to enhance their analytical capabilities, make informed decisions, and stay ahead in the competitive financial landscape. The book provides a structured approach that covers foundational topics in quantitative risk assessment, data analytics, and AI, providing a roadmap for professionals to navigate the complexities of integrating AI and data analytics into financial practices. The book explores specific applications and methodologies, including machine learning algorithms for economic modeling and AI-driven strategies for risk management, providing readers with practical insights and strategies for success in the AI-driven financial future. With this book as a guide, professionals can confidently embrace the power of AI and data analytics to stay ahead in the ever-evolving economic landscape. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9798369362167

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Mohammad Gouse Galety
Published by IGI Global, Hershey, PA, 2024
ISBN 13: 9798369362167
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Paperback. Condition: new. Paperback. In today's fast-paced financial landscape, professionals face an uphill battle in effectively integrating data analytics and artificial intelligence (AI) into quantitative risk assessment and financial computation. The constantly increasing volume, velocity, and variety of data generated by digital transactions, market exchanges, and social media platforms offer unparalleled financial analysis and decision-making opportunities. However, professionals need sophisticated AI technologies and data analytics methodologies to harness this data for predictive modeling, risk assessment, and algorithmic trading. Navigating this complex terrain can be daunting, and a comprehensive guide that bridges theory and practice is necessary. Data Analytics and AI for Quantitative Risk Assessment and Financial Computation is an all-encompassing reference for finance professionals, risk managers, data scientists, and students seeking to leverage the transformative power of AI and data analytics in finance. The book encapsulates this integration's theoretical underpinnings, practical applications, challenges, and future directions, empowering readers to enhance their analytical capabilities, make informed decisions, and stay ahead in the competitive financial landscape. The book provides a structured approach that covers foundational topics in quantitative risk assessment, data analytics, and AI, providing a roadmap for professionals to navigate the complexities of integrating AI and data analytics into financial practices. The book explores specific applications and methodologies, including machine learning algorithms for economic modeling and AI-driven strategies for risk management, providing readers with practical insights and strategies for success in the AI-driven financial future. With this book as a guide, professionals can confidently embrace the power of AI and data analytics to stay ahead in the ever-evolving economic landscape. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9798369362167

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