Big data in finance : opportunities and challenges of financial digitalization / Thomas Walker, Frederick Davis, Tyler Schwartz, editors.
Walker, Thomas (Thomas J.), editor.; Davis, Frederick, editor.; Schwartz, Tyler (Data scientist), editor.
2022
HG173 .B54 2022eb
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Title Big data in finance : opportunities and challenges of financial digitalization / Thomas Walker, Frederick Davis, Tyler Schwartz, editors.
ISBN 9783031122408 (electronic bk.)
3031122402 (electronic bk.)
9783031122392
3031122399
DOI https://doi.org/10.1007/978-3-031-12240-8
Published Cham : Palgrave Macmillan, [2022]
Copyright ©2022
Language English
Description 1 online resource (xxv, 272 pages : illustrations (some color))
Other Standard Identifiers 10.1007/978-3-031-12240-8 doi
Call Number HG173 .B54 2022eb
Dewey Decimal Classification 332.028557
Summary This edited book explores the unique risks, opportunities, challenges, and societal implications associated with big data developments within the field of finance. While the general use of big data has been the subject of frequent discussions, this book will take a more focused look at big data applications in the financial sector. With contributions from researchers, practitioners, and entrepreneurs involved at the forefront of big data in finance, the book discusses technological and business-inspired breakthroughs in the field. The contributions offer technical insights into the different applications presented and highlight how these new developments may impact and contribute to the evolution of the financial sector. Additionally, the book presents several case studies that examine practical applications of big data in finance. In exploring the readiness of financial institutions to adapt to new developments in the big data/artificial intelligence space and assessing different implementation strategies and policy solutions, the book will be of interest to academics, practitioners, and regulators who work in this field. Thomas Walker is a Full Professor of Finance and the Concordia University Research Chair in Emerging Risk Management at Concordia University, Montreal, Canada. Prior to academia, he worked for several years in the German consulting and industrial sector at Mercedes Benz, Utility Consultants International, Lahmeyer International, Telenet, and KPMG Peat Marwick. Frederick Davis is an Associate Professor at the John Molson School of Business at Concordia University, Montreal, Canada. Prior to his academic career, he worked for several years in the government sector assisting communities with their economic development. His research interests include mergers and acquisitions, insider trading, big data, and other aspects of corporate finance. Tyler Schwartz holds an MSc degree in Data Science and Business Analytics from HEC Montreal. He has served as a research assistant in the Department of Finance at Concordia University for over four years and is the co-author of an edited book collection on climate change adaptation as well as working papers on social impact bonds and the Sustainable Development Goals (SDGs).
Note Includes index.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed October 19, 2022).
Added Author Walker, Thomas (Thomas J.), editor.
Davis, Frederick, editor.
Schwartz, Tyler (Data scientist), editor.
Available in Other Form Print version: 9783031122392
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Part I. Introduction
Big Data in Finance: An Overview
Part II. Big Data in the Financial Markets
Alternative Data
An Algorithmic Trading Strategy to Balance Profitability and Risk
High-Frequency Trading and Market efficiency in the Moroccan Stock Market
Ensemble Models Using Symbolic Regression and Genetic Programming for Uncertainty Estimation in ESG and Alternative Investments
Part III. Big Data in Financial Services
Consumer Credit Assessments in the Age of Big Data
Robo-Advisors: A Big Data Challenge
Bitcoin: Future or Fad?
Culture, Digital Assets, and the Economy: A Trans-National Perspective
Part IV. Case Studies and Applications
Islamic Finance in Canada Powered by Big Data: A Case Study
Assessing the Carbon Footprint of Cryptoassets: Evidence from a Bivariate VAR Model
A Data-Informed Approach to Financial Literacy Enhancement Using Cognitive and Behavioral Analytics.

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