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

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.

Copyright:

2021

Book Details

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