Copper and Aluminium as Economically Imperfect Substitutes, Production and Price Development

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26510%2F22%3APU145328" target="_blank" >RIV/00216305:26510/22:PU145328 - isvavai.cz</a>

Alternative codes found

RIV/75081431:_____/22:00002371

Result on the web

<a href="https://actamont.tuke.sk/pdf/2022/n2/14bartos.pdf" target="_blank" >https://actamont.tuke.sk/pdf/2022/n2/14bartos.pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.46544/AMS.v27i2.14" target="_blank" >10.46544/AMS.v27i2.14</a>

Result language

angličtina

Original language name

Copper and Aluminium as Economically Imperfect Substitutes, Production and Price Development

Original language description

Copper and aluminium prices have long been influenced mainly by non-renewable resources and the industry's widespread use of copper and aluminium for their desired properties. Metal commodities are irreplaceable for the industry of developed countries, and their shortage in the covid times also increases the price and consequently the price of products made from them. As copper ore stocks continue to decline, suitable substitutes should be sought. The paper discusses the potential of copper substitution by aluminium and subsequently the development of prices and production of copper and aluminium, including a prediction about the future development. Research data were obtained from Market. business insider (2021) and Investing.com (2022) converted to time series. The price is shown in US dollars per tonne and the production value in millions of tonnes. Development data were processed using artificial intelligence and recurrent neural networks, including the Long Short Term Memory layer. Neural networks, as such, have great potential to predict these types of time series. The annual copper and aluminium production data were processed using a regression function. Neural networks could not be used due to the smaller data range. The results show that the 1NN30L neural network with an LSTM layer and considered a 30-day delay is the most suitable network for forecasting future copper prices, and the 3NN30L neural network with an LSTM layer and considered a 30-day delay is the most suitable network for forecasting future aluminium prices. The forecast has confirmed that the price of copper will fall at the end of 2021, and the trend will be constant in the next planned period. Aluminium will also fall sharply at the end of 2021; at the beginning of 2022, the price level is predicted to rise to that of 30 October 2021, and thereinafter the trend will be almost constant. Research has confirmed that copper and aluminium may be imperfect substitutes in some respect, but they c

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

20701 - Environmental and geological engineering, geotechnics

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2022

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Acta Montanistica Slovaca

ISSN

1335-1788

e-ISSN

1339-3103

Volume of the periodical

27

Issue of the periodical within the volume

2

Country of publishing house

SK - SLOVAKIA

Number of pages

17

Pages from-to

462-478

UT code for WoS article

000834987800013

EID of the result in the Scopus database

2-s2.0-85135301476