Using Artificial Neural Networks for Timeseries Smoothing and Forecasting
Case Studies in Economics
Seiten
2022
|
1st ed. 2021
Springer International Publishing (Verlag)
978-3-030-75651-2 (ISBN)
Springer International Publishing (Verlag)
978-3-030-75651-2 (ISBN)
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.
Time series and their importance to the economy.- Econometrics - selected models.- Artificial neural networks - selected models.- Comparison of different methods.- Conclusion.
Erscheinungsdatum | 07.09.2022 |
---|---|
Reihe/Serie | Studies in Computational Intelligence |
Zusatzinfo | X, 189 p. 185 illus., 166 illus. in color. |
Verlagsort | Cham |
Sprache | englisch |
Maße | 155 x 235 mm |
Gewicht | 314 g |
Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
Technik | |
Schlagworte | Artificial Neural Networks • Forecasting • Statistic Methods • Timeseries • Timeseries Smoothing |
ISBN-10 | 3-030-75651-3 / 3030756513 |
ISBN-13 | 978-3-030-75651-2 / 9783030756512 |
Zustand | Neuware |
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