Data Science for Economics and Finance: Methodologies and Applications
暫譯: 經濟與金融的數據科學：方法論與應用
Consoli, Sergio, Reforgiato Recupero, Diego, Saisana, Michaela
- 出版商: Springer
- 出版日期: 2021-06-10
- 售價: $2,230
- 貴賓價: 9.5 折 $2,119
- 語言: 英文
- 頁數: 355
- 裝訂: Quality Paper - also called trade paper
- ISBN: 3030668932
- ISBN-13: 9783030668938
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相關分類:
經濟學 Economy、Data Science
海外代購書籍(需單獨結帳)
相關主題
商品描述
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.
商品描述(中文翻譯)
這本開放存取的書籍涵蓋了數據科學的應用，包括先進的機器學習、大數據分析、語義網技術、自然語言處理、社交媒體分析、時間序列分析等，並應用於經濟學和金融領域。此外，它展示了一些成功的先進數據科學解決方案的應用，這些解決方案用於從數據中提取新知識，以改善經濟預測模型。
本書首先介紹了數據科學技術在經濟學和金融中的應用，接著有十三章展示特定數據科學方法論的成功案例，涉及與經濟分析相關的新型大數據來源和技術的特定主題（例如社交媒體和新聞）；利用監督式/非監督式（深度）機器學習的大數據模型；使用自然語言處理來建立經濟和金融指標；以及通過時間序列分析進行經濟變數的預測和即時預測。
這本書對所有參與數位和數據密集型經濟學和金融研究的利益相關者都具有重要意義，幫助他們理解主要的機會和挑戰，熟悉最新的方法論發現，並學習如何使用和評估新工具和框架的性能。它主要針對利用數據科學技術的數據科學家和商業分析師，同時也將成為相關學科和課程的研究生的有用資源。總體而言，讀者將學習現代且有效的數據科學解決方案，以創造經濟和金融應用的具體創新。
作者簡介
Diego Reforgiato Recupero is an Associate Professor at the Department of Mathematics and Computer Science of the University of Cagliari, Italy, where he is also a member of the Technical Commission for Patents and Spin-offs. His interests span from Semantic Web, graph theory, and smart grid optimization to sentiment analysis, data mining, big data, natural language processing, and human-robot interaction. He is the author of several research publications in peer-reviewed international journals, edited books, and leading conferences in these fields. He is Director of the Laboratory of Human Robot Interaction and Co-Director of the Laboratory of Artificial Intelligence and Big Data. He is also affiliated with the National Research Council of Italy (CNR) where he is a member of the Semantic Technology Laboratory and passionate about bringing the research output to the market.
Michaela Saisana is Head of the Monitoring, Indicators and Impact Evaluation Unit and she also leads the European Commission's Competence Centre on Composite Indicators and Scoreboards (COIN) at the Joint Research Centre in Italy. She has been working in the JRC since 1998, where she obtained a prize as "Best Young Scientist of the Year" in 2004 and together with her team the "JRC Policy Impact Award" for the Social Scoreboard of the European Pillar of Social Rights in 2018. Specializing on process optimization and spatial statistics, she is actively involved in promoting a sound development and responsible use of performance monitoring tools which feed into EU policy formulation and legislation in a wide range of fields.
作者簡介(中文翻譯)
Sergio Consoli 是歐洲委員會（聯合研究中心）在義大利的科學專案官，負責「大數據與經濟發展預
