Data Science in Finance and Accounting
Language: English
Published by Springer, 2026
- Hardcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
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Add to basketItem description from seller
Druck auf Anfrage Neuware - Printed after ordering - This book brings together innovative research at the intersection of data science, machine learning, and finance. Covering a wide spectrum of topics including explainable AI, financial distress prediction, stock market forecasting, investment strategies, audit analytics, and economic modeling it showcases both theoretical developments and applied case studies from around the world.With chapters spanning predictive modeling, sentiment analysis, capital structure, IT governance, and Bayesian approaches to productivity, the book offers a multidisciplinary perspective on how data-driven tools are reshaping modern finance and accounting.This book presents a timely resource for academics, practitioners, and graduate students seeking to understand and apply data science in financial and accounting contexts.
Seller Inventory # 9783032061782
- Title
- Data Science in Finance and Accounting
- Author
- Hien Thu Thi Nguyen
- Publisher
- Springer
- Publication year
- 2026
- Condition
- Neu
- Binding
- Buch
- Language
- English
- ISBN 10
- 3032061784
- ISBN 13
- 9783032061782
- Item weight
- 744 grams
- Dimensions
- 241x160x27 mm
This book brings together innovative research at the intersection of data science, machine learning, and finance. Covering a wide spectrum of topics—including explainable AI, financial distress prediction, stock market forecasting, investment strategies, audit analytics, and economic modeling—it showcases both theoretical developments and applied case studies from around the world.
With chapters spanning predictive modeling, sentiment analysis, capital structure, IT governance, and Bayesian approaches to productivity, the book offers a multidisciplinary perspective on how data-driven tools are reshaping modern finance and accounting.
This book presents a timely resource for academics, practitioners, and graduate students seeking to understand and apply data science in financial and accounting contexts.
"Synopsis" may belong to another edition of this title.
From the Back Cover
This book brings together innovative research at the intersection of data science, machine learning, and finance. Covering a wide spectrum of topics—including explainable AI, financial distress prediction, stock market forecasting, investment strategies, audit analytics, and economic modeling—it showcases both theoretical developments and applied case studies from around the world.
With chapters spanning predictive modeling, sentiment analysis, capital structure, IT governance, and Bayesian approaches to productivity, the book offers a multidisciplinary perspective on how data-driven tools are reshaping modern finance and accounting.
This book presents a timely resource for academics, practitioners, and graduate students seeking to understand and apply data science in financial and accounting contexts.
"About the title" may belong to another edition of this title.
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