Data Science for Economics and Finance

Data Science for Economics and Finance
Author :
Publisher : Springer Nature
Total Pages : 357
Release :
ISBN-10 : 9783030668914
ISBN-13 : 3030668916
Rating : 4/5 (916 Downloads)

Book Synopsis Data Science for Economics and Finance by : Sergio Consoli

Download or read book Data Science for Economics and Finance written by Sergio Consoli and published by Springer Nature. This book was released on 2021 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.


Data Science for Economics and Finance Related Books

Data Science for Economics and Finance
Language: en
Pages: 357
Authors: Sergio Consoli
Categories: Application software
Type: BOOK - Published: 2021 - Publisher: Springer Nature

DOWNLOAD EBOOK

This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language proce
Adventures In Financial Data Science: The Empirical Properties Of Financial And Economic Data (Second Edition)
Language: en
Pages: 512
Authors: Graham L Giller
Categories: Business & Economics
Type: BOOK - Published: 2022-06-27 - Publisher: World Scientific

DOWNLOAD EBOOK

This book provides insights into the true nature of financial and economic data, and is a practical guide on how to analyze a variety of data sources. The focus
Financial Data Analytics
Language: en
Pages: 393
Authors: Sinem Derindere Köseoğlu
Categories: Business & Economics
Type: BOOK - Published: 2022-04-25 - Publisher: Springer Nature

DOWNLOAD EBOOK

​This book presents both theory of financial data analytics, as well as comprehensive insights into the application of financial data analytics techniques in
Data Analysis for Business, Economics, and Policy
Language: en
Pages: 741
Authors: Gábor Békés
Categories: Business & Economics
Type: BOOK - Published: 2021-05-06 - Publisher: Cambridge University Press

DOWNLOAD EBOOK

A comprehensive textbook on data analysis for business, applied economics and public policy that uses case studies with real-world data.
Big Data Science in Finance
Language: en
Pages: 336
Authors: Irene Aldridge
Categories: Computers
Type: BOOK - Published: 2021-01-08 - Publisher: John Wiley & Sons

DOWNLOAD EBOOK

Explains the mathematics, theory, and methods of Big Data as applied to finance and investing Data science has fundamentally changed Wall Street—applied mathe