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Predicting future Brent oil price on global markets

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F75081431%3A_____%2F20%3A00001969" target="_blank" >RIV/75081431:_____/20:00001969 - isvavai.cz</a>

  • Result on the web

    <a href="https://actamont.tuke.sk/pdf/2020/n3/10vochozka.pdf" target="_blank" >https://actamont.tuke.sk/pdf/2020/n3/10vochozka.pdf</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.46544/AMS.v25i3.10" target="_blank" >10.46544/AMS.v25i3.10</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Predicting future Brent oil price on global markets

  • Original language description

    The high volatility of oil prices is a cause of prediction complexity, especially in times of crisis or during the current coronavirus pandemic. In this paper, a special and promising type of artificial neural network – LSTM (Long Short-Term Memory) is used for predicting oil prices. The paper's objective is to predict the development of Brent oil prices' daily values to 30 June 2021. For this purpose, available data for the period from the end of June 1988 to the end of November 2020 is used.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database

  • CEP classification

  • OECD FORD branch

    50200 - Economics and Business

Result continuities

  • Project

  • Continuities

    N - Vyzkumna aktivita podporovana z neverejnych zdroju

Others

  • Publication year

    2020

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Acta Montanistica Slovaca

  • ISSN

    1335-1788

  • e-ISSN

  • Volume of the periodical

    25

  • Issue of the periodical within the volume

    3

  • Country of publishing house

    SK - SLOVAKIA

  • Number of pages

    18

  • Pages from-to

    375-392

  • UT code for WoS article

  • EID of the result in the Scopus database

    2-s2.0-85101093270