Data Science for Financial Econometrics

by Nguyễn Ngọc Thạch (editor), Vladik Kreinovich (editor), Nguyen Duc Trung (editor)

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.  

1046 pages, Kindle Edition

Published November 13, 2020

About the author

Nguyễn Ngọc Thạch (bút danh khác: Jade), là tác giả trẻ được cộng đồng mạng quan tâm khi chọn những mảng đề tài gai góc, gây nhiều tranh cãi trong xã hội như đồng tính, mại dâm, chuyển giới. Mặc dù đang làm việc trong lĩnh vực marketing, viết lách chỉ như một cuộc dạo chơi đầy ngẫu hứng, nhưng với giọng văn trần thực, không hoa mỹ mà vẫn giàu cảm xúc, các tác phẩm của Thạch viết ra vẫn luôn được đông đảo độc giả đón nhận.