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001431075 001__ 1431075
001431075 003__ OCoLC
001431075 005__ 20230308003219.0
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001431075 019__ $$a1261771629$$a1262379459
001431075 020__ $$a9783030668914$$q(electronic bk.)
001431075 020__ $$a3030668916$$q(electronic bk.)
001431075 020__ $$z9783030668907
001431075 0247_ $$a10.1007/978-3-030-66891-4$$2doi
001431075 035__ $$aSP(OCoLC)1257416604
001431075 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dOCLCO$$dYDX$$dEBLCP$$dSFB$$dOCLCF$$dOCLCQ$$dCOM$$dOCLCO$$dOCLCQ
001431075 049__ $$aISEA
001431075 050_4 $$aHB143.5$$b.D38 2021
001431075 08204 $$a330.0285$$223
001431075 24500 $$aData science for economics and finance :$$bmethodologies and applications /$$cSergio Consoli, Diego Reforgiato Recupero, Michaela Saisana, editors.
001431075 264_1 $$aCham :$$bSpringer,$$c[2021]
001431075 264_4 $$c©2021
001431075 300__ $$a1 online resource (xiv, 355 pages) :$$billustrations (chiefly color)
001431075 336__ $$atext$$btxt$$2rdacontent
001431075 337__ $$acomputer$$bc$$2rdamedia
001431075 338__ $$aonline resource$$bcr$$2rdacarrier
001431075 504__ $$aIncludes bibliographical references.
001431075 5050_ $$aData Science Technologies in Economics and Finance: A Gentle Walk-In -- Supervised Learning for the Prediction of Firm Dynamics -- Opening the Black Box: Machine Learning Interpretability and Inference Tools with an Application to Economic Forecasting -- Machine Learning for Financial Stability -- Sharpening the Accuracy of Credit Scoring Models with Machine Learning Algorithms -- Classifying Counterparty Sector in EMIR Data -- Massive Data Analytics for Macroeconomic Nowcasting -- New Data Sources for Central Banks -- Sentiment Analysis of Financial News: Mechanics and Statistics -- Semi-supervised Text Mining for Monitoring the News About the ESG Performance of Companies -- Extraction and Representation of Financial Entities from Text -- Quantifying News Narratives to Predict Movements in Market Risk -- Do the Hype of the Benefits from Using New Data Science Tools Extend to Forecasting Extremely Volatile Assets? -- Network Analysis for Economics and Finance: An application to Firm Ownership.
001431075 5060_ $$aOpen access$$5GW5XE
001431075 520__ $$aThis 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.
001431075 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed June 23, 2021).
001431075 650_0 $$aEconomics$$xData processing.
001431075 650_0 $$aEconomic forecasting$$xData processing.
001431075 650_6 $$aÉconomie politique$$xInformatique.
001431075 650_6 $$aPrévision économique$$xInformatique.
001431075 655_0 $$aElectronic books.
001431075 7001_ $$aConsoli, Sergio,$$eeditor.
001431075 7001_ $$aReforgiato Recupero, Diego,$$eeditor.
001431075 7001_ $$aSaisana, Michaela,$$eeditor.
001431075 7760_ $$z3030668908
001431075 852__ $$bebk
001431075 85640 $$3Springer Nature$$uhttps://link.springer.com/10.1007/978-3-030-66891-4$$zOnline Access$$91397441.2
001431075 909CO $$ooai:library.usi.edu:1431075$$pGLOBAL_SET
001431075 980__ $$aBIB
001431075 980__ $$aEBOOK
001431075 982__ $$aEbook
001431075 983__ $$aOnline
001431075 994__ $$a92$$bISE