Data Science for Financial Econometrics

Name: Data Science for Financial Econometrics
Brand: Springer Nature Switzerland AG
SKU: 9783030488529
Price: 1098.85 RON
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Autor: Nguyen Duc Trung, Vladik Kreinovich

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Editura: Springer Nature Switzerland AG

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This book offers an overview of state-of-the-art econometric techniques, with a special emphasis on...

Informații despre carte

Autor

Nguyen Duc Trung, Vladik Kreinovich

Limbă

engleză

Legare

Carte - Copertă tare

Publicat

2020

Pagini

644

EAN

9783030488529

ISBN

3030488527

Enbook ID

33397335

Editura

Springer Nature Switzerland AG

Greutate

1121

Dimensiuni

160 x 241 x 40

Descriere completă

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.

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Data Science for Financial Econometrics

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