Data Science for Financial Econometrics (1st ed. 2021) (Studies in Computational Intelligence #898)

By: Vladik Kreinovich and Nguyen Ngoc Thach and Nguyen Duc Trung

Sign Up Now! Already a Member? Log In
You must be logged into Bookshare to access this title. Learn about membership options, or view our freely available titles.

Synopsis: This book offers an overview of state-of-the-art econometric techniques, with a special emphasis on financial econometrics. There is a major need for such techniques, since the traditional way of designing mathematical models – based on researchers’ insights – can no longer keep pace with the ever-increasing data flow. To catch up, many application areas have begun relying on data science, i.e., on techniques for extracting models from data, such as data mining, machine learning, and innovative statistics. In terms of capitalizing on data science, many application areas are way ahead of economics. To close this gap, the book provides examples of how data science techniques can be used in economics. Corresponding techniques range from almost traditional statistics to promising novel ideas such as quantum econometrics. Given its scope, the book will appeal to students and researchers interested in state-of-the-art developments, and to practitioners interested in using data science techniques.

Book Quality:: Publisher Quality
ISBN-13:: 9783030488536
Related ISBNs:: 9783030488529
Publisher:: Springer International Publishing
Date of Addition:: 11/14/20
Copyrighted By:: Springer
Adult content:: No
Language:: English
Has Image Descriptions:: No
Categories:: Nonfiction, Computers and Internet, Business and Finance, Technology
Submitted By:: Bookshare Staff
Usage Restrictions:: This is a copyrighted book.
Edited by:: Nguyen Ngoc Thach
Edited by:: Vladik Kreinovich
Edited by:: Nguyen Duc Trung