Data Science for Financial Econometrics
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ISBN 10: 3030488527 ISBN 13: 9783030488529
Published by Springer, 2020
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2020. Hardcover. . . . . . Books ship from the US and Ireland. Seller Inventory # V9783030488529
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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.
From the Back Cover:
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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Bibliographic Details
Title: Data Science for Financial Econometrics
Publisher: Springer
Publication Date: 2020
Binding: Hardcover
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Data Science for Financial Econometrics
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Data Science for Financial Econometrics (Studies in Computational Intelligence, 898)
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Data Science for Financial Econometrics
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Data Science for Financial Econometrics (Studies in Computational Intelligence, 898)
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Data Science for Financial Econometrics (Hardcover)
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ISBN 10: 3030488527
ISBN 13: 9783030488529
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Hardcover. Condition: new. Hardcover. 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. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9783030488529
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Data Science for Financial Econometrics
ISBN 10: 3030488527
ISBN 13: 9783030488529
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Buch. Condition: Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 644 pp. Englisch. Seller Inventory # 9783030488529
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Data Science for Financial Econometrics
Published by
Springer International Publishing, 2020
ISBN 10: 3030488527
ISBN 13: 9783030488529
New
Hardcover
Seller: AHA-BUCH GmbH, Einbeck, Germany
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Seller Inventory # 9783030488529
Quantity: 1 available