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The role of news-based sentiment in forecasting crude oil price during the Covid-19 pandemic

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F25%3A39923436" target="_blank" >RIV/00216275:25410/25:39923436 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1007/s10479-024-05821-z" target="_blank" >https://doi.org/10.1007/s10479-024-05821-z</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/s10479-024-05821-z" target="_blank" >10.1007/s10479-024-05821-z</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    The role of news-based sentiment in forecasting crude oil price during the Covid-19 pandemic

  • Original language description

    During the Covid-19 pandemic, news-based sentiment emerged as a factor linked to crude oil prices in the literature. However, the question remained as to whether this sentiment could be used to more accurately predict crude oil prices. To assess the effect of news-based sentiment on forecasting crude oil prices, five models based on state-of-the-art machine learning methods were compared; they were taken from the literature on crude oil forecasting. Results are reported for each method for the period of the Covid-19 pandemic and also for the years from 1990 to the beginning of the pandemic. This allowed for the examination of the role of news-based sentiment during different periods of economic development and crisis. Across the machine learning methods, a significant effect of news-based sentiment was observed in terms of its predictive performance during the Covid-19 period, in contrast to previous periods, including the financial crisis of 2008-2009.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    50206 - Finance

Result continuities

  • Project

    <a href="/en/project/GA22-22586S" target="_blank" >GA22-22586S: Aspect-based sentiment analysis of financial texts for predicting corporate financial performance</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2025

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Annals of Operations Research

  • ISSN

    0254-5330

  • e-ISSN

    1572-9338

  • Volume of the periodical

    345

  • Issue of the periodical within the volume

    2-3

  • Country of publishing house

    NL - THE KINGDOM OF THE NETHERLANDS

  • Number of pages

    24

  • Pages from-to

    861-884

  • UT code for WoS article

    001147645000003

  • EID of the result in the Scopus database

    2-s2.0-85183052555