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.
Vladik Kreinovich & Nguyen Ngoc Thach
Data Science for Financial Econometrics [EPUB ebook]
Data Science for Financial Econometrics [EPUB ebook]
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Idioma Inglés ● Formato EPUB ● ISBN 9783030488536 ● Editor Vladik Kreinovich & Nguyen Ngoc Thach ● Editorial Springer International Publishing ● Publicado 2020 ● Descargable 3 veces ● Divisa EUR ● ID 8032851 ● Protección de copia Adobe DRM
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