Data science for economics and finance : methodologies and applications

This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some succ...

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Podrobná bibliografia
Hlavní autori: Consoli, Sergio, Reforgiato Recupero, Diego, Saisana, Michaela
Médium: E-kniha Kniha
Jazyk:English
Vydavateľské údaje: Cham Springer 2021
Springer Nature
Springer International Publishing AG
European Commission
Vydanie:1
Predmet:
Artificial intelligence
Big Data
Big Data/Analytics
Business
Business and Management
Business Information Systems
Business mathematics & systems
Business mathematics and systems
Computer and Information Systems Applications
Computer Appl. in Administrative Data Processing
Computer science
Computer Technology
Computing and Information Technology
Data Analytics
Data Mining
Data Mining and Knowledge Discovery
Data warehousing
Decision Support Systems
Economics, Finance, Business and Management
Expert systems / knowledge-based systems
Information retrieval
Information Storage and Retrieval
Information technology: general issues
IT in Business
Machine Learning
Management
Nonfiction
Open Access
Politics and government
Public administration
Semantics and Reasoning
Society and Social Sciences
ISBN:3030668932, 9783030668938, 9783030668914, 3030668916, 9783030668907, 3030668908
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Popis
Shrnutí:This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models. The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis. This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications.
Bibliografia:"Open access"--Cover
Includes bibliographical references
Electronic reproduction. Dordrecht: Springer, 2021. Requires the Libby app or a modern web browser.
ISBN:3030668932
9783030668938
9783030668914
3030668916
9783030668907
3030668908
DOI:10.1007/978-3-030-66891-4