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Artificial intelligence and beyond for finance / editors, Marco Corazza ... [et al.].

Contributor(s): Material type: TextSeries: Transformations in banking, finance and regulation ; vol. 15.Publication details: London : World Scientific Publishing Europe, c2024.Description: 1 online resource (xxix, 398 p.)ISBN:
  • 9781800615212
  • 1800615213
Subject(s): Genre/Form: DDC classification:
  • 332.0285 23
LOC classification:
  • HG4515.5
Online resources:
Contents:
Machine learning in portfolio decisions -- Natural language processing and stock returns -- Portfolio allocation and reinforcement learning -- Explainable artificial intelligence in risk management: a framework -- How can sentiment analysis contribute to financial markets and services? -- Quantum fintech -- Tail dependence of eurozone bond yields and sovereign CDS spreads -- Stylized facts of decentralized finance (DeFi) -- Effective systems for bot detection and real-time stock market predictions -- Reinforcement machine learning optimization algorithms for the computation of downside risk and investable portfolios in post 2007-2009 financial meltdown -- Deep learning in insurance: an incremental deep learning approach for pricing prediction strategy in the insurance industry.
Summary: "We wrote this book to help financial experts and investors to understand the state of the art of artificial intelligence and machine learning in finance. But first, what is artificial intelligence? The foundations of artificial intelligence lie in the human desire to automate. Often this desire has had foundations in grand civilization-defining visions or economic needs, such as the Antikythera mechanism, circa 200 BCE. Considered to be the oldest known example of an analog computer, it is thought that the mechanism automated the prediction of the positions of the sun, the moon, and the planets to assist in navigation. No matter the specific industry or application, AI has become a new engine of growth. Both finance and banking have been leveraging AI technologies and algorithms, applying them to automate routine tasks, procedures and forecasting, thereby improving overall customer experience. The topics covered in this book make it an invaluable resource for academics, researchers, policymakers, and practitioners alike who want to understand how AI has affected the banking and financial industries and how it will continue to change them in the years to come"-- Publisher's website.
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Electronic Books CUTN Central Library 332.0285 (Browse shelf(Opens below)) Link to resource Available EB04930

Includes bibliographical references and index.

Machine learning in portfolio decisions -- Natural language processing and stock returns -- Portfolio allocation and reinforcement learning -- Explainable artificial intelligence in risk management: a framework -- How can sentiment analysis contribute to financial markets and services? -- Quantum fintech -- Tail dependence of eurozone bond yields and sovereign CDS spreads -- Stylized facts of decentralized finance (DeFi) -- Effective systems for bot detection and real-time stock market predictions -- Reinforcement machine learning optimization algorithms for the computation of downside risk and investable portfolios in post 2007-2009 financial meltdown -- Deep learning in insurance: an incremental deep learning approach for pricing prediction strategy in the insurance industry.

"We wrote this book to help financial experts and investors to understand the state of the art of artificial intelligence and machine learning in finance. But first, what is artificial intelligence? The foundations of artificial intelligence lie in the human desire to automate. Often this desire has had foundations in grand civilization-defining visions or economic needs, such as the Antikythera mechanism, circa 200 BCE. Considered to be the oldest known example of an analog computer, it is thought that the mechanism automated the prediction of the positions of the sun, the moon, and the planets to assist in navigation. No matter the specific industry or application, AI has become a new engine of growth. Both finance and banking have been leveraging AI technologies and algorithms, applying them to automate routine tasks, procedures and forecasting, thereby improving overall customer experience. The topics covered in this book make it an invaluable resource for academics, researchers, policymakers, and practitioners alike who want to understand how AI has affected the banking and financial industries and how it will continue to change them in the years to come"-- Publisher's website.

Mode of access: World Wide Web.

System requirements: Adobe Acrobat Reader.

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