Data Science for Financial Econometrics (Studies in Computational Intelligence, 898)

Ngoc Thach, Nguyen; Kreinovich, Vladik; Trung, Nguyen Duc

ISBN 10: 3030488527 / ISBN 13: 9783030488529

Published by Springer, 2020

About this Item

Unread, like new. Immediately dispatched from Germany. Seller Inventory # CEA-2401C-SOFA-02-2000

Bibliographic Details

Title: Data Science for Financial Econometrics (...

Publisher: Springer

Publication Date: 2020

Binding: Hardcover

Condition: As New

Edition: 1. Auflage

About this title

Synopsis:

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.