001450113 000__ 05185cam\a2200541\i\4500 001450113 001__ 1450113 001450113 003__ OCoLC 001450113 005__ 20230310004508.0 001450113 006__ m\\\\\o\\d\\\\\\\\ 001450113 007__ cr\cn\nnnunnun 001450113 008__ 221009s2022\\\\sz\a\\\\o\\\\\001\0\eng\d 001450113 019__ $$a1347026521 001450113 020__ $$a9783031122408$$q(electronic bk.) 001450113 020__ $$a3031122402$$q(electronic bk.) 001450113 020__ $$z9783031122392 001450113 020__ $$z3031122399 001450113 0247_ $$a10.1007/978-3-031-12240-8$$2doi 001450113 035__ $$aSP(OCoLC)1347020567 001450113 040__ $$aYDX$$beng$$erda$$epn$$cYDX$$dGW5XE$$dEBLCP$$dUKMGB$$dOCLCF$$dN$T$$dVLB 001450113 049__ $$aISEA 001450113 050_4 $$aHG173$$b.B54 2022eb 001450113 08204 $$a332.028557$$223/eng/20221019 001450113 24500 $$aBig data in finance :$$bopportunities and challenges of financial digitalization /$$cThomas Walker, Frederick Davis, Tyler Schwartz, editors. 001450113 264_1 $$aCham :$$bPalgrave Macmillan,$$c[2022] 001450113 264_4 $$c©2022 001450113 300__ $$a1 online resource (xxv, 272 pages : illustrations (some color)) 001450113 336__ $$atext$$btxt$$2rdacontent 001450113 337__ $$acomputer$$bc$$2rdamedia 001450113 338__ $$aonline resource$$bcr$$2rdacarrier 001450113 500__ $$aIncludes index. 001450113 50500 $$gPart I.$$tIntroduction --$$tBig Data in Finance: An Overview --$$gPart II.$$tBig Data in the Financial Markets --$$tAlternative Data --$$tAn Algorithmic Trading Strategy to Balance Profitability and Risk --$$tHigh-Frequency Trading and Market efficiency in the Moroccan Stock Market --$$tEnsemble Models Using Symbolic Regression and Genetic Programming for Uncertainty Estimation in ESG and Alternative Investments --$$gPart III.$$tBig Data in Financial Services --$$tConsumer Credit Assessments in the Age of Big Data --$$tRobo-Advisors: A Big Data Challenge --$$tBitcoin: Future or Fad? --$$tCulture, Digital Assets, and the Economy: A Trans-National Perspective --$$gPart IV.$$tCase Studies and Applications --$$tIslamic Finance in Canada Powered by Big Data: A Case Study --$$tAssessing the Carbon Footprint of Cryptoassets: Evidence from a Bivariate VAR Model --$$tA Data-Informed Approach to Financial Literacy Enhancement Using Cognitive and Behavioral Analytics. 001450113 506__ $$aAccess limited to authorized users. 001450113 520__ $$aThis 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). 001450113 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed October 19, 2022). 001450113 650_0 $$aFinance$$xData processing. 001450113 650_0 $$aBig data. 001450113 650_0 $$aFinancial services industry$$xTechnological innovations. 001450113 655_0 $$aElectronic books. 001450113 7001_ $$aWalker, Thomas$$q(Thomas J.),$$eeditor. 001450113 7001_ $$aDavis, Frederick,$$eeditor. 001450113 7001_ $$aSchwartz, Tyler$$c(Data scientist),$$eeditor. 001450113 77608 $$iPrint version:$$z3031122399$$z9783031122392$$w(OCoLC)1332780154 001450113 852__ $$bebk 001450113 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-12240-8$$zOnline Access$$91397441.1 001450113 909CO $$ooai:library.usi.edu:1450113$$pGLOBAL_SET 001450113 980__ $$aBIB 001450113 980__ $$aEBOOK 001450113 982__ $$aEbook 001450113 983__ $$aOnline 001450113 994__ $$a92$$bISE