AI for finance

By:

Tsang, Edward P. K

Material type: Text

TextSeries: AI for EverythingPublication details: CRC Press Boca Raton 2023Description: xx, 105 pISBN:

9781032384436

Subject(s):

DDC classification:

332.028563 TSA

Summary: Finance students and practitioners may ask: can machines learn everything? 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. Including original research, the book explains the impact of ignoring computation in classical economics; examines the relationship between computing and finance and points out potential misunderstandings between economists and computer scientists; and introduces Directional Change and explains how this can be used. To finance students and practitioners, this book will explain the promise of AI, as well as its limitations. It will cover knowledge representation, modelling, simulation and machine learning, explaining the principles 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. Trading depth for readability, AI for Finance will help readers decide whether to invest more time into the subject. (https://www.routledge.com/AI-for-Finance/Tsang/p/book/9781032384436?srsltid=AfmBOopL4iBoVMSo9Jv5_KrZDw-gYbn8whaK9iq9d98cCR6cP9ViMd1N)

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Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Book	Indian Institute of Management LRC General Stacks	Finance & Accounting	332.028563 TSA (Browse shelf(Opens below))	1	Available		007053

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Table of content:
Acknowledgements

Preface

Introduction

1. AI-Finance Synergy

2. Machine Learning Knows No Boundaries?

3.Machine Learning in Finance

4. Modelling, Simulation and Machine Learning

5. Portfolio Optimization

6. Financial Data: Beyond Time Series

7. Over the Horizon

Bibliographical Remarks

Bibliography

Index
[https://www.routledge.com/AI-for-Finance/Tsang/p/book/9781032384436?srsltid=AfmBOopL4iBoVMSo9Jv5_KrZDw-gYbn8whaK9iq9d98cCR6cP9ViMd1N]

Finance students and practitioners may ask: can machines learn everything? 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.

Including original research, the book explains the impact of ignoring computation in classical economics; examines the relationship between computing and finance and points out potential misunderstandings between economists and computer scientists; and introduces Directional Change and explains how this can be used.

To finance students and practitioners, this book will explain the promise of AI, as well as its limitations. It will cover knowledge representation, modelling, simulation and machine learning, explaining the principles 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. Trading depth for readability, AI for Finance will help readers decide whether to invest more time into the subject.
(https://www.routledge.com/AI-for-Finance/Tsang/p/book/9781032384436?srsltid=AfmBOopL4iBoVMSo9Jv5_KrZDw-gYbn8whaK9iq9d98cCR6cP9ViMd1N)

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