Using Artificial Neural Networks for Timeseries Smoothing and Forecasting: Case Studies in Economics: 979 (Studies in Computational Intelligence, 979) - Image 1

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Springer Using Artificial Neural Networks for Timeseries Smoothing and Forecasting: Case Studies in Economics: 979 (Studies in Computational Intelligence, 979)

Name: Using Artificial Neural Networks for Timeseries Smoothing and Forecasting: Case Studies in Economics: 979 (Studies in Computational Intelligence, 979)
Brand: Springer
Price: 93.26 GBP
Availability: InStock

Econometrics

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Description

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. From the Back Cover 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.

Product Specifications

Brand: Springer
Format: hardcover
ASIN: 3030756483
Category: Books > Subjects > Business, Finance & Law > Economics > Econometrics
Domain: Amazon UK
Release Date: 05 September 2021
Listed Since: 06 April 2021

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Springer Using Artificial Neural Networks for Timeseries Smoothing and Forecasting: Case Studies in Economics: 979 (Studies in Computational Intelligence, 979)

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