Data Science for Financial Econometrics

Author:   Nguyen Ngoc Thach ,  Vladik Kreinovich ,  Nguyen Duc Trung
Publisher:   Springer Nature Switzerland AG
Edition:   2021 ed.
Volume:   898
ISBN:  

9783030488529


Pages:   633
Publication Date:   14 November 2020
Format:   Hardback
Availability:   Manufactured on demand   Availability explained
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Data Science for Financial Econometrics


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Overview

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.  

Full Product Details

Author:   Nguyen Ngoc Thach ,  Vladik Kreinovich ,  Nguyen Duc Trung
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
Edition:   2021 ed.
Volume:   898
Weight:   1.124kg
ISBN:  

9783030488529


ISBN 10:   3030488527
Pages:   633
Publication Date:   14 November 2020
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

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