VOCHOZKA, Marek. Comparison of neural networks and regression time series in estimating the development of the afternoon price of palladium on the New York Stock Exchange. Trends Economics and Management. Brno: Fakulta podnikatelská Vysokého učení technického v Brně, vol. 30, No 3, p. 73-83. ISSN 1802-8527. 2017.
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Basic information
Original name Comparison of neural networks and regression time series in estimating the development of the afternoon price of palladium on the New York Stock Exchange
Name in Czech Komparace neuronových sítí a regresních časových řad při odhadu vývoje odpoledních cen palladia na Newyorské burze
Authors VOCHOZKA, Marek.
Edition Trends Economics and Management, Brno, Fakulta podnikatelská Vysokého učení technického v Brně, 2017, 1802-8527.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 50200 5.2 Economics and Business
Country of publisher Czech Republic
Confidentiality degree is not subject to a state or trade secret
Organization unit Institute of Technology and Business in České Budějovice
Keywords (in Czech) palladium; umělé neuronové sítě; regresní časové řady; predikce; vícevrstvé perceptronové sítě
Keywords in English palladium; artificial neural networks; regression time series; prediction; multilayer perceptron network
Tags ERIH, FKT, RIV17
Changed by Changed by: Mgr. Blanka Mikšíková, učo 22534. Changed: 18/4/2018 08:18.
Abstract
The aim of the paper is to perform a regression analysis of the development of afternoon platinum prices on the New York Stock Exchange using neural networks and a simple linear regression. The partial aim is to compare these two methods and determine the most suitable ones for predicting the future development of afternoon platinum prices on the New York Stock Exchange. The analysis is made on the data on afternoon platinum prices in a time period exceeding 10 years. The result is a prediction of afternoon platinum prices and the fact that neural networks are more suitable than simple linear regression for this prediction.
Abstract (in Czech)
The aim of the paper is to perform a regression analysis of the development of afternoon platinum prices on the New York Stock Exchange using neural networks and a simple linear regression. The partial aim is to compare these two methods and determine the most suitable ones for predicting the future development of afternoon platinum prices on the New York Stock Exchange. The analysis is made on the data on afternoon platinum prices in a time period exceeding 10 years. The result is a prediction of afternoon platinum prices and the fact that neural networks are more suitable than simple linear regression for this prediction.
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