Edited by Thomas Walker · Frederick Davis Tyler Schwartz Big Data in Finance Opportunities and Challenges of Financial Digitalization Big Data in Finance · · Thomas Walker Frederick Davis Tyler Schwartz Editors Big Data in Finance Opportunities and Challenges of Financial Digitalization Editors Thomas Walker Frederick Davis Department of Finance Department of Finance Concordia University Concordia University Montreal, QC, Canada Montreal, QC, Canada Tyler Schwartz Department of Finance Concordia University Montreal, QC, Canada ISBN 978-3-031-12239-2 ISBN 978-3-031-12240-8 (eBook) https://doi.org/10.1007/978-3-031-12240-8 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and informa- tion in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Palgrave Macmillan imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland Preface Our global society is becoming increasingly data centric. The use of large, detailed datasets has revolutionized many fields, including— among others—medicine, biology, manufacturing, sports, marketing, and finance. With advances in how data can be collected and stored, a new phenomenon has emerged: big data. In simple terms, big data can be understood as a large amount of data that can be analyzed to understand past patterns better or predict future outcomes. This book examines the technical aspects of recent innovations surrounding big data in finance, as well as the benefits and risks associated with these developments. More- over, the book sheds light on the ethical and privacy issues associated with big data, as well as the environmental footprint of collecting, storing, and analyzing big datasets. The book features contributions from the international community of scholars and practitioners who work at the interface of artificial intelli- gence, big data, and finance. The authors review and critically analyze new developments at the intersection of big data and finance, and provide different perspectives on their impact on the financial sector and the way it operates. The book serves as a technical guide of these devel- opments, exploring the theory and mechanisms behind the algorithms using big data, and exploring their use in a finance context. The contrib- utors explain and demonstrate the predictive capabilities of big data in finance using different model types such as supervised, unsupervised, and semi-supervised learning. Moreover, because big data in finance has many v vi PREFACE applications that extend beyond financial institutions, the book features contributions that explore possible policy and sustainability-oriented solu- tions and implications of the use of big data in finance. Montreal, Canada Thomas Walker Montreal, Canada Frederick Davis Montreal, Canada Tyler Schwartz Acknowledgments We acknowledge the financial support provided through the Jacques Ménard—BMO Centre for Capital Markets at Concordia University. In addition, we appreciate the excellent copy-editing and editorial assistance we received from Gabrielle Machnik-Kekesi, Victoria Kelly, Charlotte Frank, and Maya Michaeli. vii Contents Introduction Big Data in Finance: An Overview 3 Thomas Walker, Frederick Davis, and Tyler Schwartz Big Data in the Financial Markets Alternative Data 13 Vincent Grégoire and Noah Jepson An Algorithmic Trading Strategy to Balance Profitability and Risk 35 Guillermo Peña High-Frequency Trading and Market Efficiency in the Moroccan Stock Market 55 El Mehdi Ferrouhi and Ibrahim Bouabdallaoui Ensemble Models Using Symbolic Regression and Genetic Programming for Uncertainty Estimation in ESG and Alternative Investments 69 Percy Venegas, Isabel Britez, and Fernand Gobet ix x CONTENTS Big Data in Financial Services Consumer Credit Assessments in the Age of Big Data 95 Lynnette Purda and Cecilia Ying Robo-Advisors: A Big Data Challenge 115 Federico Severino and Sébastien Thierry Bitcoin: Future or Fad? 133 Daniel Tut Culture, Digital Assets, and the Economy: A Trans-National Perspective 159 John Fan Zhang, Zehuang Xu, Yi Peng, Wujin Yang, and Haorou Zhao Case Studies and Applications Islamic Finance in Canada Powered by Big Data: A Case Study 187 Imran Abdool and Mustafa Abdool Assessing the Carbon Footprint of Cryptoassets: Evidence from a Bivariate VAR Model 207 Hany Fahmy A Data-Informed Approach to Financial Literacy Enhancement Using Cognitive and Behavioral Analytics 231 Prasanta Bhattacharya, Kum Seong Wan, Boon Kiat Quek, Waseem Bak’r Hameed, and Sivanithy Rathananthan Index 265 Notes on Contributors Abdool Imran is the President of consultancy Blue Krystal Technologies and Business Insights. Currently, he lectures at the University of Western Ontario Richard Ivey School of Business. During the 2007/2007 Finan- cial Crisis, Imran also served in the Assistant Deputy Minister’s Office for Financial Sector Policy of the Government of Canada’s Department of Finance. Imran’s commentaries on the economy and finance has appeared in Canada’s national media such as the Globe and Mail, the CBC, and the Toronto Star. Abdool Mustafa is a Machine Learning Engineer at Airbnb, one of the largest travel accommodations platforms in the world. His work involves designing and implementing novel recommender and search systems for Airbnb products. Academic papers authored by Mustafa and his team have appeared in the SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). Mustafa holds a graduate degree in Computer Science, with a specialization in Artificial Intelligence from Stanford University. Bhattacharya Prasanta is a research scientist and innovation lead with the Social and Cognitive Computing department at the A*STAR Insti- tute of High Performance Computing. He also serves as adjunct Assistant Professor at the National University of Singapore (NUS) Business School. Prasanta holds a Ph.D. in Information Systems from the Department of Information Systems and Analytics, NUS, where he studied network science with a special focus on predictive and inferential methods in large xi