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

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

50206 - Finance

Projekt

<a href="/cs/project/GA22-22586S" target="_blank" >GA22-22586S: Aspektově orientovaná analýza sentimentu finančních textů pro predikci finanční výkonnosti podniku</a><br>

Návaznosti

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

Rok uplatnění

2025

Kód důvěrnosti údajů

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

Název periodika

Annals of Operations Research

ISSN

0254-5330

e-ISSN

1572-9338

Svazek periodika

345

Číslo periodika v rámci svazku

2-3

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

24

Strana od-do

861-884

Kód UT WoS článku

001147645000003

EID výsledku v databázi Scopus

2-s2.0-85183052555