The Essentials of Machine Learning in Finance and Accounting

Mohammad Zoynul Abedin, M. Kabir Hassan (University of New Orleans, USA), Petr Hajek , Mohammed Mohi Uddin

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English

Routledge
21 June 2021

Economic statistics; Economic forecasting; Applied mathematics; Machine learning

Series: Routledge Advanced Texts in Economics and Finance

This book introduces machine learning in finance and illustrates how we can use computational tools in numerical finance in real-world context. These computational techniques are particularly useful in financial risk management, corporate bankruptcy prediction, stock price prediction, and portfolio management. The book also offers practical and managerial implications of financial and managerial decision support systems and how these systems capture vast amount of financial data.

Business risk and uncertainty are two of the toughest challenges in the financial industry. This book will be a useful guide to the use of machine learning in forecasting, modeling, trading, risk management, economics, credit risk, and portfolio management.

Edited by: Mohammad Zoynul Abedin, M. Kabir Hassan (University of New Orleans, USA), Petr Hajek, Mohammed Mohi Uddin
Imprint: Routledge
Country of Publication: United Kingdom
Dimensions: Height: 246mm, Width: 174mm,
Weight: 739g
ISBN: 9780367480837
ISBN 10: 0367480832
Series: Routledge Advanced Texts in Economics and Finance
Pages: 234
Publication Date: 21 June 2021
Audience: College/higher education , Further / Higher Education , Further / Higher Education
Format: Hardback
Publisher's Status: Active

Mohammad Zoynul Abedin is an associate professor of Finance at the Hajee Mohammad Danesh Science and Technology University, Bangladesh. Dr. Abedin continuously publishes academic papers in refereed journals. Moreover, Dr. Abedin served as an ad hoc reviewer for many academic journals. His research interest includes data analytics and business intelligence. M. Kabir Hassan is a professor of Finance at the University of New Orleans, USA. Prof. Hassan has over 350 papers (225 SCOPUS, 108 SSCI, 58 ESCI, 227 ABDC, 161 ABS) published as book chapters and in top refereed academic journals. According to an article published in Journal of Finance, the number of publications would put Prof. Hassan in the top 1% of peers who continue to publish one refereed article per year over a long period of time. Petr Hajek is currently an associate professor with the Institute of System Engineering and Informatics, University of Pardubice, Czech Republic. He is the author or co-author of four books and more than 60 articles in leading journals. His current research interests include business decision making, soft computing, text mining, and knowledge-based systems. Mohammed Mohi Uddin is an assistant professor of Accounting at the University of Illinois Springfield, USA. His primary research interests concern accountability, performance management, corporate social responsibility, and accounting data analytics. Dr. Uddin published scholarly articles in reputable academic and practitioners’ journals.

Reviews for The Essentials of Machine Learning in Finance and Accounting

This book will serve as a valuable source for the digital transformation of the financial industry. Dr. Zamir Iqbal, VP Finance and Chief Financial Officer (CFO), Islamic Development Bank (IsDB) An essential resource for financial accounting managers and students of financial management. Professor Mehmet Huseyin Bilgin, Istanbul Medeniyet University, Turkey A comprehensive coverage of emerging intelligent technologies in finance. Professor Ohaness Paskelian, University of Houston-Downtown, USA