Analysis and forecasting of financial time series : selected cases / Jaydip Sen.

Format:

Book

Author/Creator:

Sen, Jaydip, author.

Language:

English

Subjects (All):

Finance--Statistical methods.

Finance.

Time-series analysis--Computer programs.

Time-series analysis.

Physical Description:

1 online resource (404 pages)

Place of Publication:

Newcastle-upon-Tyne, England : Cambridge Scholars Publishing, [2022]

Summary:

This book brings together real-world cases illustrating how to analyse volatile financial time series in order to provide a better understanding of their past behavior and robust forecasting of their future behavioural patterns. Using time series data from diverse financial sectors, it shows how the concepts and techniques of statistical analysis, machine learning, and deep learning are applied to build robust predictive models, as well as the ways in which these models can be used for forecasting the future prices of stocks and constructing profitable portfolios of investments. All the concepts and methods used in the book have been implemented using Python and R languages on TensorFlow and Keras frameworks. The volume will be particularly useful for advanced postgraduate and doctoral students of finance, economics, econometrics, statistics, data science, computer science, and information technology.

Contents:

Intro

Dedication

Table of Contents

List of Figures

List of Tables

About the Author

Preface

Chapter 1

Chapter 2

Chapter 3

Chapter 4

Chapter 5

Chapter 6

Index.

Notes:

Includes index.

Description based on print version record.

Other Format:

Print version: Sen, Jaydip Analysis and Forecasting of Financial Time Series

ISBN:

9781527588851