Machine Learning in the Analysis and Forecasting of Financial Time Series.

This book is a collection of real-world cases, illustrating how to handle challenging and volatile financial time series data for a better understanding of their past behavior and robust forecasting of their future movement. It demonstrates how the concepts and techniques of statistical, econometric...

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Библиографическая информация
Главный автор: Sen, Jaydip
Другие авторы: Mehtab, Sidra
Формат: Электронная книга
Язык:English
Публикация: Newcastle-upon-Tyne Cambridge Scholars Publishing, 2022.
Предметы:
Online-ссылка:EBSCOhost
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505 0 |a Intro -- Dedication -- Table of Contents -- List of Figures -- List of Tables -- Preface -- Chapter 1 -- Chapter 2 -- Chapter 3 -- Chapter 4 -- Chapter 5 -- Chapter 6 -- Chapter 7 -- Contributors 
520 |a This book is a collection of real-world cases, illustrating how to handle challenging and volatile financial time series data for a better understanding of their past behavior and robust forecasting of their future movement. It demonstrates how the concepts and techniques of statistical, econometric, machine learning, and deep learning are applied to build robust predictive models, and the ways in which these models can be used for constructing profitable portfolios of investments. All the concepts and methods used here have been implemented using R and Python languages on TensorFlow and Keras. 
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