
The Essentials of Machine Learning in Finance and Accounting
Description
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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.
Reviews / Votes
"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
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Persons
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.
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