Data science for financial econometrics / Nguyen Ngoc Thach, Vladik Kreinovich, Nguyen Duc Trung, editors.
Ngoc Thach, Nguyen, editor.; Kreinovich, Vladik, editor.; Duc Trung, Nguyen, editor.
2021
HG106 .D28 2021eb
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Title Data science for financial econometrics / Nguyen Ngoc Thach, Vladik Kreinovich, Nguyen Duc Trung, editors.
ISBN 9783030488536 (electronic bk.)
3030488535 (electronic bk.)
9783030488529
DOI https://doi.org/10.1007/978-3-030-48853-6
Published Cham : Springer, [2021]
Copyright ©2021
Language English
Description 1 online resource (x, 622 pages)
Item Number 10.1007/978-3-030-48853-6 doi
Call Number HG106 .D28 2021eb
Dewey Decimal Classification 330.01/5195
620.00285
Summary 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.
Access Note Access limited to authorized users.
Digital File Characteristics PDF
text file
Source of Description Description based on print version record.
Added Author Ngoc Thach, Nguyen, editor.
Kreinovich, Vladik, editor.
Duc Trung, Nguyen, editor.
Series Studies in computational intelligence ; v. 898.
Available in Other Form Data Science for Financial Econometrics.
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