Using Artificial Neural Networks for Timeseries Smoothing and Forecasting (Hardcover)

Jaromir Vrbka

ISBN 10: 3030756483 / ISBN 13: 9783030756482

Published by Springer Nature Switzerland AG, Cham, 2021

About this Item

Hardcover. The aim of this publication is to identify and apply suitable methods for analysing and predicting the time series of gold prices, together with acquainting the reader with the history and characteristics of the methods and with the time series issues in general. Both statistical and econometric methods, and especially artificial intelligence methods, are used in the case studies. The publication presents both traditional and innovative methods on the theoretical level, always accompanied by a case study, i.e. their specific use in practice. Furthermore, a comprehensive comparative analysis of the individual methods is provided. The book is intended for readers from the ranks of academic staff, students of universities of economics, but also the scientists and practitioners dealing with the time series prediction. From the point of view of practical application, it could provide useful information for speculators and traders on financial markets, especially the commodity markets. The aim of this publication is to identify and apply suitable methods for analysing and predicting the time series of gold prices, together with acquainting the reader with the history and characteristics of the methods and with the time series issues in general. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Seller Inventory # 9783030756482

Bibliographic Details

• Title: Using Artificial Neural Networks for Timeseries Smoothing and Forecasting (Hardcover)
• Publisher: Springer Nature Switzerland AG, Cham
• Publication Date: 2021
• Language: English
• ISBN 10: 3030756483
• ISBN 13: 9783030756482
• Binding: Hardcover
• Condition: new

About this title

Synopsis

The aim of this publication is to identify and apply suitable methods for analysing and predicting the time series of gold prices, together with acquainting the reader with the history and characteristics of the methods and with the time series issues in general. Both statistical and econometric methods, and especially artificial intelligence methods, are used in the case studies. The publication presents both traditional and innovative methods on the theoretical level, always accompanied by a case study, i.e. their specific use in practice. Furthermore, a comprehensive comparative analysis of the individual methods is provided. The book is intended for readers from the ranks of academic staff, students of universities of economics, but also the scientists and practitioners dealing with the time series prediction. From the point of view of practical application, it could provide useful information for speculators and traders on financial markets, especially the commodity markets.