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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Detalles Bibliográficos
Otros Autores:	Consoli, Sergio (Editor), Consoli, Sergio. editor (editor), Reforgiato Recupero, Diego. editor, Saisana, Michaela. editor
Formato:	Libro electrónico
Idioma:	Inglés
Publicado:	Cham : Springer Nature 2021 2021.
Edición:	1st ed. 2021.
Materias:	Data mining. Machine learning. Management information systems. Big data. Application software. Information storage and retrieval. Data Mining and Knowledge Discovery. Machine Learning. Business Information Systems. Big Data/Analytics. Computer Appl. in Administrative Data Processing. Information Storage and Retrieval. Data Mining and Knowledge Discovery Machine Learning Business Information Systems Big Data/Analytics Computer Appl. in Administrative Data Processing Information Storage and Retrieval IT in Business Computer and Information Systems Applications Open Access Data Mining Big Data Data Analytics Decision Support Systems Semantics and Reasoning Expert systems / knowledge-based systems Business mathematics & systems Public administration Information technology: general issues Information retrieval Data warehousing
Ver en Biblioteca Universitat Ramon Llull:	https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009654066306719

Tabla de Contenidos:

Data 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.

Data Science for Economics and Finance Methodologies and Applications

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