Enseignants-Chercheurs

Publications Scientifiques

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"Do Gas Price and Uncertainty Indices Forecast Crude Oil Prices? Fresh
Evidence Through XGBoost Modeling." Computational Economics ; 1-25.

 

 

• [Q2]

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"Assessing the Impact of Fossil Fuel Prices on Renewable Energy in China Using the Novel Dynamic ARDL Simulations Approach." Sustainability 14, no. 16 : 10439.

 

 

• [Q1]

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”Illiquidity, Uncertainty Indices, and COVID-19 Outbreak Conditions : Empirical Evidence from the US Financial Market.” Complexity.(3) :1-23

 

 

• [Q1]

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”Does Uncertainty Forecast Crude Oil Volatility before and during the COVID-19 Outbreak ? Fresh Evidence Using Machine Learning Models”. Energies.15(15) :5744.

 

 

• [Q1]

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A Hybrid Particle Swarm Optimization to Forecast Implied Volatility Risk”. CMC-COMPUTERS MATERIALS  & CONTINUA.73, no. 2 : 4291-4309.

 

 

• [Q2]

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''Asymmetric connectedness between oil price, coal and renewable energy consumption in China: Evidence from Fourier NARDL approach ''. Energy, 285, 129416.

• [Q1/ impact factor 9]

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''Dirty versus renewable energy consumption in China: A comparative analysis between conventional and non-conventional approaches ''. Annals of Operations Research, 1-22.

• [ABDC Rank A, Q1, impact factor 4,8]

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Threshold effect in the relationship between external debt and energy access in sub-Saharan African countries: A dynamic panel threshold specification”. Regional Science Policy & Practice, Volume 16, Issue 6, June 2024, p100024.

• [Scopus Q2/ WOS Q2; IF 1.7]

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The complex relationship between credit and liquidity risks: a linear and non linear analysis for the banking sector, Humanities and Social Sciences Communications, 11(1), 1-9. 

• [Scopus Q1/ WOS Q1 ; IF 3.7]

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Can financial inclusion enhance human development: evidence from low and middle income countries, Humanities and Social Sciences Communications, 11(1), 1-14.

• [Scopus Q1/ WOS Q1 ; IF 3.7]

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Can economic, geopoltical and energy uncertainty indices predict bitcoin energy consumption? New evidence from machine learning approach, Energoes, 17 '13), 3245.

• [Scopus Q2/ WOS IF 3]

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Testing the non linear long and short run distributional asymmetries effects of Bitcoin prices on Bitcoin energy consumption: new insights through the QNARDL model and XGBoost machine learning tool, Energies 17(12), 2810.

• [Scopus Q2/ WOS IF 3]

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Working Papers