109 related articles for article (PubMed ID: 37361516)
1. Forecasting crude oil prices in the COVID-19 era: Can machine learn better?
Tian G; Peng Y; Meng Y
Energy Econ; 2023 Sep; 125():106788. PubMed ID: 37361516
[TBL] [Abstract][Full Text] [Related]
2. Do Gas Price and Uncertainty Indices Forecast Crude Oil Prices? Fresh Evidence Through XGBoost Modeling.
Tissaoui K; Zaghdoudi T; Hakimi A; Nsaibi M
Comput Econ; 2022 Sep; ():1-25. PubMed ID: 36157277
[TBL] [Abstract][Full Text] [Related]
3. Prediction of crude oil prices in COVID-19 outbreak using real data.
Öztunç Kaymak Ö; Kaymak Y
Chaos Solitons Fractals; 2022 May; 158():111990. PubMed ID: 35291221
[TBL] [Abstract][Full Text] [Related]
4. Volatility forecasting of crude oil futures based on a genetic algorithm regularization online extreme learning machine with a forgetting factor: The role of news during the COVID-19 pandemic.
Weng F; Zhang H; Yang C
Resour Policy; 2021 Oct; 73():102148. PubMed ID: 34539033
[TBL] [Abstract][Full Text] [Related]
5. Crude oil prices and volatility prediction by a hybrid model based on kernel extreme learning machine.
Niu H; Zhao Y
Math Biosci Eng; 2021 Sep; 18(6):8096-8122. PubMed ID: 34814291
[TBL] [Abstract][Full Text] [Related]
6. A CEEMD-ARIMA-SVM model with structural breaks to forecast the crude oil prices linked with extreme events.
Cheng Y; Yi J; Yang X; Lai KK; Seco L
Soft comput; 2022; 26(17):8537-8551. PubMed ID: 35818583
[TBL] [Abstract][Full Text] [Related]
7. Point and interval prediction of crude oil futures prices based on chaos theory and multiobjective slime mold algorithm.
Sun W; Chen H; Liu F; Wang Y
Ann Oper Res; 2022 Jun; ():1-31. PubMed ID: 35755829
[TBL] [Abstract][Full Text] [Related]
8. Oil prices volatility and economic performance during COVID-19 and financial crises of 2007-2008.
Yu Y; Guo S; Chang X
Resour Policy; 2022 Mar; 75():102531. PubMed ID: 34961804
[TBL] [Abstract][Full Text] [Related]
9. The effect of green energy, global environmental indexes, and stock markets in predicting oil price crashes: Evidence from explainable machine learning.
Ben Jabeur S; Khalfaoui R; Ben Arfi W
J Environ Manage; 2021 Nov; 298():113511. PubMed ID: 34392096
[TBL] [Abstract][Full Text] [Related]
10. The impact of COVID-19 news, panic and media coverage on the oil and gold prices: An ARDL approach.
Atri H; Kouki S; Gallali MI
Resour Policy; 2021 Aug; 72():102061. PubMed ID: 34725531
[TBL] [Abstract][Full Text] [Related]
11. The effects and reacts of COVID-19 pandemic and international oil price on energy, economy, and environment in China.
Jia Z; Wen S; Lin B
Appl Energy; 2021 Nov; 302():117612. PubMed ID: 35496936
[TBL] [Abstract][Full Text] [Related]
12. Forecasting carbon emissions future prices using the machine learning methods.
Shahzad U; Sengupta T; Rao A; Cui L
Ann Oper Res; 2023 Feb; ():1-32. PubMed ID: 36777411
[TBL] [Abstract][Full Text] [Related]
13. Forecasting the realized variance of oil-price returns: a disaggregated analysis of the role of uncertainty and geopolitical risk.
Gupta R; Pierdzioch C
Environ Sci Pollut Res Int; 2022 Jul; 29(34):52070-52082. PubMed ID: 35257343
[TBL] [Abstract][Full Text] [Related]
14. The role of cryptocurrencies in predicting oil prices pre and during COVID-19 pandemic using machine learning.
Ibrahim BA; Elamer AA; Abdou HA
Ann Oper Res; 2022 Oct; ():1-44. PubMed ID: 36320866
[TBL] [Abstract][Full Text] [Related]
15. The Russia-Saudi Arabia oil price war during the COVID-19 pandemic.
Ma RR; Xiong T; Bao Y
Energy Econ; 2021 Oct; 102():105517. PubMed ID: 34898736
[TBL] [Abstract][Full Text] [Related]
16. Carbon trading and COVID-19: a hybrid machine learning approach for international carbon price forecasting.
Zhang X; Li Z; Zhao Y; Wang L
Ann Oper Res; 2023 Apr; ():1-29. PubMed ID: 37361057
[TBL] [Abstract][Full Text] [Related]
17. Risk perception and oil and gasoline markets under COVID-19.
Ahundjanov BB; Akhundjanov SB; Okhunjanov BB
J Econ Bus; 2021; 115():105979. PubMed ID: 33518846
[TBL] [Abstract][Full Text] [Related]
18. Forecasting oil commodity spot price in a data-rich environment.
Boubaker S; Liu Z; Zhang Y
Ann Oper Res; 2022 Oct; ():1-18. PubMed ID: 36217322
[TBL] [Abstract][Full Text] [Related]
19. A novel hybrid approach to forecast crude oil futures using intraday data.
Manickavasagam J; Visalakshmi S; Apergis N
Technol Forecast Soc Change; 2020 Sep; 158():120126. PubMed ID: 32518424
[TBL] [Abstract][Full Text] [Related]
20. Probabilistic carbon price prediction with quantile temporal convolutional network considering uncertain factors.
Cao Y; Zha D; Wang Q; Wen L
J Environ Manage; 2023 Sep; 342():118137. PubMed ID: 37178463
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]