Data Science for Financial Econometrics Hardback
Edited by Nguyen Ngoc Thach, Vladik Kreinovich, Nguyen Duc Trung
Part of the Studies in Computational Intelligence series
Hardback
Description
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.
Information
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Out of stock
- Format:Hardback
- Pages:633 pages, 71 Illustrations, color; 20 Illustrations, black and white; X, 633 p. 91 illus., 71 illus
- Publisher:Springer Nature Switzerland AG
- Publication Date:14/11/2020
- Category:
- ISBN:9783030488529
Information
-
Out of stock
- Format:Hardback
- Pages:633 pages, 71 Illustrations, color; 20 Illustrations, black and white; X, 633 p. 91 illus., 71 illus
- Publisher:Springer Nature Switzerland AG
- Publication Date:14/11/2020
- Category:
- ISBN:9783030488529
