logo

EbookBell.com

Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.

Please read the tutorial at this link:  https://ebookbell.com/faq 


We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.


For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.

EbookBell Team

Data Science For Financial Econometrics Nguyen Ngoc Thach Vladik Kreinovich

  • SKU: BELL-30712038
Data Science For Financial Econometrics Nguyen Ngoc Thach Vladik Kreinovich
$ 31.00 $ 45.00 (-31%)

5.0

30 reviews

Data Science For Financial Econometrics Nguyen Ngoc Thach Vladik Kreinovich instant download after payment.

Publisher: Springer
File Extension: PDF
File size: 12.68 MB
Pages: 633
Author: Nguyen Ngoc Thach, Vladik Kreinovich, Nguyen Duc Trung
ISBN: 9783030488529, 9783030488536, 3030488527, 3030488535
Language: English
Year: 2020

Product desciption

Data Science For Financial Econometrics Nguyen Ngoc Thach Vladik Kreinovich by Nguyen Ngoc Thach, Vladik Kreinovich, Nguyen Duc Trung 9783030488529, 9783030488536, 3030488527, 3030488535 instant download after payment.

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.

Related Products