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AI for finance / Edward P.K. Tsang.

By:

Tsang, Edward [author.]

Material type:

TextSeries: AI for everythingPublisher: Boca Raton : CRC Press, 2023Edition: First editionDescription: 1 online resource : illustrationsContent type:

text

Media type:

computer

Carrier type:

online resource

ISBN:

9781003348474
1003348475
9781000878523
100087852X
9781000878578
1000878570

Subject(s):

Additional physical formats: Print version:: AI for financeLOC classification:

HG4515.5

Online resources:

EBSCOhost

Contents:

AI-finance synergy -- Machine learning knows no boundaries? -- Machine learning in finance -- Modelling, simulation and machine learning -- Portfolio optimization -- Financial data: beyond time series -- Over the horizon.

Summary: "Finance students and practitioners may ask: Can machines learn everything? Where could AI help me? Computing students or practitioners may ask: which of my skills could contribute to finance? Where in finance should I pay attention? This book aims to answer these questions. No prior knowledge is expected in AI or finance. To finance students and practitioners, this book will explain the promise of AI and its limitations. It will cover knowledge representation, modelling, simulation and machine learning. It will explain the principle of how they work. To computing students and practitioners, this book will introduce the financial applications in which AI has made an impact. This includes algorithmic trading, forecasting, risk analysis portfolio optimization and other less well-known areas in finance. This book trades depth for readability. It aims to help readers to decide whether to invest more time into the subject. This book contains original research. For example, it explains the impact of ignoring computation in classical economics. It explains the relationship between computing and finance and points out potential misunderstandings between economists and computer scientists. It introduces Directional Change and explains how it can be used"-- Provided by publisher.

Item type: List(s) this item appears in: Titluri cărți electronice EBSCO 2025 (340 titluri)

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EBSCOhost "EBSCO evaluates our products based on the Web Content Accessibility Guidelines (WCAG) and the related Section 508 and EN 301 549 regulations in the US and EU. Most EBSCO products are substantially conformant with WCAG 2.2 level AA." Source: https://connect.ebsco.com/s/article/EBSCO-VPATs?language=en_US. Last accessed April 22, 2025.

Online resource; title from PDF title page (EBSCO, viewed May 3, 2023).

Includes bibliographical references and index.

"Finance students and practitioners may ask: Can machines learn everything? Where could AI help me? Computing students or practitioners may ask: which of my skills could contribute to finance? Where in finance should I pay attention? This book aims to answer these questions. No prior knowledge is expected in AI or finance. To finance students and practitioners, this book will explain the promise of AI and its limitations. It will cover knowledge representation, modelling, simulation and machine learning. It will explain the principle of how they work. To computing students and practitioners, this book will introduce the financial applications in which AI has made an impact. This includes algorithmic trading, forecasting, risk analysis portfolio optimization and other less well-known areas in finance. This book trades depth for readability. It aims to help readers to decide whether to invest more time into the subject. This book contains original research. For example, it explains the impact of ignoring computation in classical economics. It explains the relationship between computing and finance and points out potential misunderstandings between economists and computer scientists. It introduces Directional Change and explains how it can be used"-- Provided by publisher.

Edward P. K. Tsang is a retired professor and a freelance consultant. With a first degree in finance and a PhD in AI, he has broad interests in constraint satisfaction, optimization, AI and finance.

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