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 frameworks. The book will be particularly useful for advanced postgraduate and doctoral students of finance, economics, econometrics, statistics, data science, computer science, and information technology.
- ISBN13 9781527583245
- Publish Date 1 June 2022
- Publish Status Active
- Publish Country GB
- Imprint Cambridge Scholars Publishing
- Edition Unabridged edition
- Format Hardcover
- Pages 365
- Language English