Predicting Oil Price Trends During Conflict With Hybrid Machine Learning Techniques DOI Creative Commons
Hicham BOUSSATTA, Marouane CHIHAB, Mohamed Chiny

и другие.

Applied Computational Intelligence and Soft Computing, Год журнала: 2025, Номер 2025(1)

Опубликована: Янв. 1, 2025

The ongoing conflict between Russia and Ukraine has introduced significant volatility into the global oil markets, highlighting need for robust forecasting models to understand anticipate price fluctuations during such geopolitical events. This study presents a comprehensive hybrid modeling approach predict prices in context of across three distinct periods: before war, immediate aftermath conflict. Using advanced machine learning techniques, we developed system combining Random Forest, ElasticNet, K‐Nearest Neighbors, Gradient Boosting, Support Vector Regressor models. These were integrated through Voting enhance prediction accuracy. Our analysis revealed varying levels predictive performance different periods. Prior showed strong capabilities, evidenced by low mean‐squared error (MSE) values high coefficients determination ( R 2 ). However, struggled capture extreme volatility, resulting significantly increased MSE negative values. Predictions demonstrated improvements, with reduction positive values, indicating return relatively more stable market conditions. Notably, data from both war periods could further improve accuracy, as it would reduce impact conflict’s on model performance. results emphasize challenges instability underscore importance approaches adapt rapidly changing dynamics.

Язык: Английский

Does geopolitical risk matter in carbon and crude oil markets from a multi-timescale perspective? DOI
Xuejiao Ma,

Ting Yu,

Qi–Chuan Jiang

и другие.

Journal of Environmental Management, Год журнала: 2023, Номер 346, С. 119021 - 119021

Опубликована: Сен. 20, 2023

Язык: Английский

Процитировано

23

Does the Russia-Ukraine conflict affect gasoline prices? DOI
Xin Meng,

Yanni Yu

Energy Economics, Год журнала: 2023, Номер 128, С. 107113 - 107113

Опубликована: Окт. 21, 2023

Язык: Английский

Процитировано

19

Extreme risk spillovers between SC, WTI and Brent crude oil futures-Evidence from Time-varying Granger causality test DOI
Xiaohang Ren, Yue He,

Chuanwang Liu

и другие.

Energy, Год журнала: 2025, Номер unknown, С. 135495 - 135495

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

1

Dynamic spillovers between natural gas and BRICS stock markets during health and political crises DOI

Mellouli Dhoha,

Wael Dammak, Hind Alnafisah

и другие.

Eurasian economic review, Год журнала: 2024, Номер 14(2), С. 453 - 485

Опубликована: Фев. 16, 2024

Язык: Английский

Процитировано

6

From black gold to financial fallout: Analyzing extreme risk spillovers in oil-exporting nations DOI
Ilyes Abid, Ramzi Benkraiem, Héla Mzoughi

и другие.

Journal of International Financial Markets Institutions and Money, Год журнала: 2024, Номер 91, С. 101948 - 101948

Опубликована: Янв. 18, 2024

Язык: Английский

Процитировано

5

Does oil spin the commodity wheel? Quantile connectedness with a common factor error structure across energy and agricultural markets DOI Creative Commons

Xiaoran Zhou,

Martin Enilov,

Mamata Parhi

и другие.

Energy Economics, Год журнала: 2024, Номер 132, С. 107468 - 107468

Опубликована: Март 15, 2024

Should investors and policy makers in agricultural markets consider oil market's incontestable impact on portfolio risk management? This paper investigates the time-varying market linkages between energy commodities presence of two important exogenous shocks, viz., COVID-19 pandemic subsequent 2022 Russia–Ukraine military conflict. We use a novel parameter vector autoregressive model with common factor error structure to estimate tail connectedness for period December 31, 2019 18, 2023. Our findings provide clear evidence asymmetry volatility evolution. determine that spillover magnitudes are much stronger across quantiles than at mean. note crude is main transmitter shocks system before onset Russia-Ukraine conflict lower distribution. While natural gas transmit both pre- post-conflict announcement periods. Furthermore, found transmission commodities. Numerous observed shift their position from transmitters receivers volatility, vice versa, due Ukraine. causality results depict patterns other has varying Commodities which conflicting countries major world exports of, such as wheat, have notably increased dependency oil. Thus, we advise policymakers seriously management monitoring policies.

Язык: Английский

Процитировано

5

Are high-income and innovative nations resilient to the Russia-Ukraine war? DOI
Vineeta Kumari,

Majdi Hassan,

Dharen Kumar Pandey

и другие.

International Review of Economics & Finance, Год журнала: 2024, Номер 93, С. 1268 - 1287

Опубликована: Апрель 3, 2024

Язык: Английский

Процитировано

5

Evidence of the internationalization of China's crude oil futures: Asymmetric linkages to global financial risks DOI
Jiaming Zhang,

Songlin Guo,

Bin Dou

и другие.

Energy Economics, Год журнала: 2023, Номер 127, С. 107083 - 107083

Опубликована: Окт. 2, 2023

Язык: Английский

Процитировано

10

Natural resources governance and geopolitical risks: A literature review and bibliometric analysis DOI

Jiangli Yu,

Shuo Wang, Wantong Yang

и другие.

Resources Policy, Год журнала: 2023, Номер 86, С. 104299 - 104299

Опубликована: Окт. 1, 2023

Язык: Английский

Процитировано

10

The impact of COVID-19 on global financial markets: A multiscale volatility spillover analysis DOI

Zishu Cheng,

Mingchen Li,

Ruhong Cui

и другие.

International Review of Financial Analysis, Год журнала: 2024, Номер 95, С. 103454 - 103454

Опубликована: Июль 18, 2024

Язык: Английский

Процитировано

4