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Using Artificial Neural Networks for Timeseries Smoothing and Forecasting

Case Studies in Economics

  • Book
  • © 2021

Overview

Authors:
  1. Jaromír Vrbka

    1. Institute of Technology and Business in České Budějovice, České Budějovice, Czech Republic

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  • Gives a survey of artificial neural networks that are suitable for timeseries smoothing and forecasting
  • Offers case studies that can help the users (students, financial experts etc.) to understand the way of using artificial networks, its advantages and disadvantages
  • The results of the case studies are compared with classic statistic methods including the way of calculation, accuracy of results and their limitations

Part of the book series: Studies in Computational Intelligence (SCI, volume 979)

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Table of contents (5 chapters)

  1. Front Matter

    Pages i-x
    Download chapter PDF

  2. Time Series and Their Importance to the Economy

    • Jaromír Vrbka
    Pages 1-5

  3. Econometrics—Selected Models

    • Jaromír Vrbka
    Pages 7-33

  4. Artificial Neural Networks—Selected Models

    • Jaromír Vrbka
    Pages 35-136

  5. Comparison of Different Methods

    • Jaromír Vrbka
    Pages 137-186

  6. Conclusion

    • Jaromír Vrbka
    Pages 187-189
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Keywords

About this book

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.

Authors and Affiliations

  • Institute of Technology and Business in České Budějovice, České Budějovice, Czech Republic

    Jaromír Vrbka

Bibliographic Information

  • Book Title: Using Artificial Neural Networks for Timeseries Smoothing and Forecasting

  • Book Subtitle: Case Studies in Economics

  • Authors: Jaromír Vrbka

  • Series Title: Studies in Computational Intelligence

  • DOI: https://doi.org/10.1007/978-3-030-75649-9

  • Publisher: Springer Cham

  • eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021

  • Hardcover ISBN: 978-3-030-75648-2Published: 05 September 2021

  • Softcover ISBN: 978-3-030-75651-2Published: 06 September 2022

  • eBook ISBN: 978-3-030-75649-9Published: 04 September 2021

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: X, 189

  • Number of Illustrations: 19 b/w illustrations, 166 illustrations in colour

  • Topics: Computational Intelligence, Artificial Intelligence

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