Ahmed GHORBEL

Personal Details

First Name:	Ahmed
Middle Name:
Last Name:	Ghorbel
Suffix:
RePEc Short-ID:	pgh144
	https://www.researchgate.net/profile/Ahmed_Ghorbel/publications

Affiliation

Faculté des Sciences Économiques et de Gestion
Université de Sfax pour le Sud

Sfax, Tunisia
http://www.fsegs.rnu.tn/
RePEc:edi:fseustn (more details at EDIRC)

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

1. Ghorbel, Ahmed & Trabelsi, Abdelwahed, 2007. "Predictive Performance of Conditional Extreme Value Theory and Conventional Methods in Value at Risk Estimation," MPRA Paper 3963, University Library of Munich, Germany.

   Cited by:

   1. Nguyen, Cuong C. & Bhatti, M. Ishaq, 2012. "Copula model dependency between oil prices and stock markets: Evidence from China and Vietnam," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(4), pages 758-773.
   2. Bhatti, M. Ishaq & Nguyen, Cuong C., 2012. "Diversification evidence from international equity markets using extreme values and stochastic copulas," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(3), pages 622-646.

Articles

1. Faiza Hamdi & Ahmed Ghorbel & Faouzi Masmoudi & Lionel Dupont, 2018. "Optimization of a supply portfolio in the context of supply chain risk management: literature review," Journal of Intelligent Manufacturing, Springer, vol. 29(4), pages 763-788, April.

   Cited by:

   1. Brusset, Xavier & Ivanov, Dmitry & Jebali, Aida & La Torre, Davide & Repetto, Marco, 2023. "A dynamic approach to supply chain reconfiguration and ripple effect analysis in an epidemic," International Journal of Production Economics, Elsevier, vol. 263(C).
   2. Farheen Naz & Anil Kumar & Abhijit Majumdar & Rohit Agrawal, 2022. "Is artificial intelligence an enabler of supply chain resiliency post COVID-19? An exploratory state-of-the-art review for future research," Operations Management Research, Springer, vol. 15(1), pages 378-398, June.
   3. Alikhani, Reza & Torabi, S. Ali & Altay, Nezih, 2019. "Strategic supplier selection under sustainability and risk criteria," International Journal of Production Economics, Elsevier, vol. 208(C), pages 69-82.
   4. Haiyun, Cui & Zhixiong, Huang & Yüksel, Serhat & Dinçer, Hasan, 2021. "Analysis of the innovation strategies for green supply chain management in the energy industry using the QFD-based hybrid interval valued intuitionistic fuzzy decision approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
   5. Meike Schroeder & Sebastian Lodemann, 2021. "A Systematic Investigation of the Integration of Machine Learning into Supply Chain Risk Management," Logistics, MDPI, vol. 5(3), pages 1-17, September.
   6. Tadeusz Sawik, 2018. "Selection of a dynamic supply portfolio under delay and disruption risks," International Journal of Production Research, Taylor & Francis Journals, vol. 56(1-2), pages 760-782, January.
      • Tadeusz Sawik, 2018. "Selection of a dynamic supply portfolio under delay and disruption risks," 2018 Papers psa1077, Job Market Papers.
   7. Mateo Ramos-Merino & Juan M. Santos-Gago & Luis M. Álvarez-Sabucedo, 2021. "Fuzzy traceability: using domain knowledge information to estimate the followed route of process instances in non-exhaustive monitoring environments," Journal of Intelligent Manufacturing, Springer, vol. 32(8), pages 2235-2255, December.
   8. Efpraxia D. Zamani & Conn Smyth & Samrat Gupta & Denis Dennehy, 2023. "Artificial intelligence and big data analytics for supply chain resilience: a systematic literature review," Annals of Operations Research, Springer, vol. 327(2), pages 605-632, August.
   9. Chih-Hung Hsu & An-Yuan Chang & Ting-Yi Zhang & Wei-Da Lin & Wan-Ling Liu, 2021. "Deploying Resilience Enablers to Mitigate Risks in Sustainable Fashion Supply Chains," Sustainability, MDPI, vol. 13(5), pages 1-24, March.
   10. Yang, Miying & Fu, Mingtao & Zhang, Zihan, 2021. "The adoption of digital technologies in supply chains: Drivers, process and impact," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
   11. Jagriti Singh & Krishan Kumar Pandey & Anil Kumar & Farheen Naz & Sunil Luthra, 2023. "Drivers, barriers and practices of net zero economy: An exploratory knowledge based supply chain multi-stakeholder perspective framework," Operations Management Research, Springer, vol. 16(3), pages 1059-1090, September.
   12. Radoslav Delina & Renata Olejarova & Petr Doucek, 2023. "Effect of a new potential supplier on business to business negotiations performance: evidence-based analysis," Electronic Commerce Research, Springer, vol. 23(3), pages 1941-1970, September.
   13. Imranul Hoque & Mohammad B. Rana, 2020. "Buyer–supplier relationships from the perspective of working environment and organisational performance: review and research agenda," Management Review Quarterly, Springer, vol. 70(1), pages 1-50, February.
   14. Xiaoyang Liu & Yuanyuan Zhou & Song Gao, 2022. "Intellectual Structure in Supply Chain Risk Management from 2000 to 2022: A Review Based on Text Mining Approach," Sustainability, MDPI, vol. 14(23), pages 1-24, December.
   15. Merve Er Kara & Seniye Ümit Oktay Fırat, 2018. "Supplier Risk Assessment Based on Best-Worst Method and K-Means Clustering: A Case Study," Sustainability, MDPI, vol. 10(4), pages 1-25, April.

2. Mohamed Fakhfekh & Ahmed Ghorbel & Nadhem Selmi & Nejib Hachicha, 2017. "Dependence between oil price volatility, Islamic and conventional Dow Jones indexes: Implication for portfolio management and hedging effectiveness," Journal of Asset Management, Palgrave Macmillan, vol. 18(1), pages 29-48, January.

   Cited by:

   1. Lahmiri, Salim & Bekiros, Stelios & Stavroyiannis, Stavros & Babalos, Vassilios, 2018. "Modelling volatility persistence under stochasticity assumptions: evidence from common and alternative investments," Chaos, Solitons & Fractals, Elsevier, vol. 114(C), pages 158-163.

3. Ahmed Ghorbel & Wajdi Hamma & Anis Jarboui, 2017. "Dependence between oil and commodities markets using time-varying Archimedean copulas and effectiveness of hedging strategies," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(9), pages 1509-1542, July.

   Cited by:

   1. Wu, Bi-Bo, 2021. "The dynamics of oil on China’s commodity sectors: What can we learn from a quantile perspective?," Journal of Commodity Markets, Elsevier, vol. 23(C).
   2. Aviral Kumar Tiwari & Micheal Kofi Boachie & Tahir Suleman & Rangan Gupta, 2020. "Structure Dependence between Oil and Agricultural Commodities Returns: The Role of Geopolitical Risks," Working Papers 202079, University of Pretoria, Department of Economics.
      • Tiwari, Aviral Kumar & Boachie, Micheal Kofi & Suleman, Muhammed Tahir & Gupta, Rangan, 2021. "Structure dependence between oil and agricultural commodities returns: The role of geopolitical risks," Energy, Elsevier, vol. 219(C).
   3. Ji, Qiang & Bouri, Elie & Roubaud, David & Shahzad, Syed Jawad Hussain, 2018. "Risk spillover between energy and agricultural commodity markets: A dependence-switching CoVaR-copula model," Energy Economics, Elsevier, vol. 75(C), pages 14-27.
   4. Aloui, Riadh & Ben Jabeur, Sami & Rezgui, Hichem & Ben Arfi, Wissal, 2023. "Geopolitical risk and commodity future returns: Fresh insights from dynamic copula conditional value-at-risk approach," Resources Policy, Elsevier, vol. 85(PB).
   5. Maitra, Debasish & Guhathakurta, Kousik & Kang, Sang Hoon, 2021. "The good, the bad and the ugly relation between oil and commodities: An analysis of asymmetric volatility connectedness and portfolio implications," Energy Economics, Elsevier, vol. 94(C).
   6. Pal, Debdatta & Mitra, Subrata K., 2019. "Correlation dynamics of crude oil with agricultural commodities: A comparison between energy and food crops," Economic Modelling, Elsevier, vol. 82(C), pages 453-466.
   7. Naeem, Muhammad Abubakr & Bouri, Elie & Costa, Mabel D. & Naifar, Nader & Shahzad, Syed Jawad Hussain, 2021. "Energy markets and green bonds: A tail dependence analysis with time-varying optimal copulas and portfolio implications," Resources Policy, Elsevier, vol. 74(C).
   8. Wajdi Hamma & Ahmed Ghorbel & Anis Jarboui, 2021. "Hedging Islamic and conventional stock markets with other financial assets: comparison between competing DCC models on hedging effectiveness," Journal of Asset Management, Palgrave Macmillan, vol. 22(3), pages 179-199, May.
   9. Jain, Prachi & Maitra, Debasish, 2023. "Risk implications of dependence in the commodities: A copula-based analysis," Global Finance Journal, Elsevier, vol. 57(C).

4. Ghorbel, Ahmed & Trabelsi, Abdelwahed, 2014. "Energy portfolio risk management using time-varying extreme value copula methods," Economic Modelling, Elsevier, vol. 38(C), pages 470-485.

   Cited by:

   1. Mohamed Fakhfekh & Ahmed Ghorbel & Nadhem Selmi & Nejib Hachicha, 2017. "Dependence between oil price volatility, Islamic and conventional Dow Jones indexes: Implication for portfolio management and hedging effectiveness," Journal of Asset Management, Palgrave Macmillan, vol. 18(1), pages 29-48, January.
   2. Narayan, Paresh Kumar & Phan, Dinh Hoang Bach & Thuraisamy, Kannan & Westerlund, Joakim, 2016. "Price discovery and asset pricing," Pacific-Basin Finance Journal, Elsevier, vol. 40(PA), pages 224-235.
   3. Guo, Yanfeng & Wen, Xiaoqian & Wu, Yanrui & Guo, Xiumei, 2016. "How is China's coke price related with the world oil price? The role of extreme movements," Economic Modelling, Elsevier, vol. 58(C), pages 22-33.
   4. Batten, Jonathan A. & Kinateder, Harald & Szilagyi, Peter G. & Wagner, Niklas F., 2019. "Time-varying energy and stock market integration in Asia," Energy Economics, Elsevier, vol. 80(C), pages 777-792.
   5. Mobeen Ur Rehman, 2020. "Dynamic correlation pattern amongst alternative energy market for diversification opportunities," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 9(1), pages 1-24, December.
   6. Nguyen, Cuong & Bhatti, M. Ishaq & Komorníková, Magda & Komorník, Jozef, 2016. "Gold price and stock markets nexus under mixed-copulas," Economic Modelling, Elsevier, vol. 58(C), pages 283-292.
   7. Aepli, Matthias D. & Füss, Roland & Henriksen, Tom Erik S. & Paraschiv, Florentina, 2017. "Modeling the multivariate dynamic dependence structure of commodity futures portfolios," Journal of Commodity Markets, Elsevier, vol. 6(C), pages 66-87.
   8. Fousekis, Panos & Grigoriadis, Vasilis, 2017. "Price co-movement and the crack spread in the US futures markets," Journal of Commodity Markets, Elsevier, vol. 7(C), pages 57-71.
   9. Wei, Zhaohao & Chai, Jian & Dong, Jichang & Lu, Quanying, 2022. "Understanding the linkage-dependence structure between oil and gas markets: A new perspective," Energy, Elsevier, vol. 257(C).
   10. Ra l De Jes s Guti rrez & Lidia E. Carvajal Guti rrez & Oswaldo Garcia Salgado, 2023. "Value at Risk and Expected Shortfall Estimation for Mexico s Isthmus Crude Oil Using Long-Memory GARCH-EVT Combined Approaches," International Journal of Energy Economics and Policy, Econjournals, vol. 13(4), pages 467-480, July.
   11. Batten, Jonathan A. & Kinateder, Harald & Szilagyi, Peter G. & Wagner, Niklas F., 2017. "Can stock market investors hedge energy risk? Evidence from Asia," Energy Economics, Elsevier, vol. 66(C), pages 559-570.
   12. Peng, Wei & Hu, Shichao & Chen, Wang & Zeng, Yu-feng & Yang, Lu, 2019. "Modeling the joint dynamic value at risk of the volatility index, oil price, and exchange rate," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 137-149.
   13. Massimiliano Caporin & Chia-Lin Chang & Michael McAleer, 2016. "Are the S&P 500 Index and Crude Oil, Natural Gas and Ethanol Futures related for Intra-Day Data?," Tinbergen Institute Discussion Papers 16-006/III, Tinbergen Institute.
       • Caporin, M. & Chang, C-L. & McAleer, M.J., 2016. "Are the S&P 500 Index and Crude Oil, Natural Gas and Ethanol Futures Related for Intra-Day Data?," Econometric Institute Research Papers EI2016-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
       • Massimiliano Caporin & Chia-Lin Chang & Michael McAleer, 2016. "Are the S&P 500 Index and Crude Oil, Natural Gas and Ethanol Futures Related for Intra-Day Data?," Documentos de Trabajo del ICAE 2016-01, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
       • Caporin, Massimiliano & Chang, Chia-Lin & McAleer, Michael, 2019. "Are the S&P 500 index and crude oil, natural gas and ethanol futures related for intra-day data?," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 50-70.
   14. Chen, Chen & Liu, Dinghao & Xian, Liang & Pan, Lin & Wang, Lihua & Yang, Min & Quan, Li, 2020. "Best-case scenario robust portfolio for energy stock market," Energy, Elsevier, vol. 213(C).
   15. He, Kaijian & Liu, Youjin & Yu, Lean & Lai, Kin Keung, 2016. "Multiscale dependence analysis and portfolio risk modeling for precious metal markets," Resources Policy, Elsevier, vol. 50(C), pages 224-233.
   16. Spyridon D. Mourtas & Vasilios N. Katsikis, 2022. "V-Shaped BAS: Applications on Large Portfolios Selection Problem," Computational Economics, Springer;Society for Computational Economics, vol. 60(4), pages 1353-1373, December.
   17. Ahmed Ghorbel & Wajdi Hamma & Anis Jarboui, 2017. "Dependence between oil and commodities markets using time-varying Archimedean copulas and effectiveness of hedging strategies," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(9), pages 1509-1542, July.
   18. Fousekis, Panos, 2017. "Price co-movement and the hedger's value-at-risk in the futures markets for coffee," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 0(Issue 1), January.
   19. Paraschiv, Florentina & Mudry, Pierre-Antoine & Andries, Alin Marius, 2015. "Stress-testing for portfolios of commodity futures," Economic Modelling, Elsevier, vol. 50(C), pages 9-18.
   20. Longwu Liang & Zhen Bo Wang & Dong Luo & Ying Wei & Jingwen Sun, 2020. "Synergy effects and it’s influencing factors of China’s high technological innovation and regional economy," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-25, May.
   21. Mubenga-Tshitaka, Jean-Luc & Muteba Mwamba, John W. & Dikgang, Johane & Gelo, Dambala, 2021. "Risk spillover between climate variables and the agricultural commodity market in East Africa," EconStor Preprints 243160, ZBW - Leibniz Information Centre for Economics.
   22. Nguyen, Cuong & Ishaq Bhatti, M. & Henry, Darren, 2017. "Are Vietnam and Chinese stock markets out of the US contagion effect in extreme events?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 480(C), pages 10-21.
   23. Fernandes, Mário Correia & Dias, José Carlos & Nunes, João Pedro Vidal, 2021. "Modeling energy prices under energy transition: A novel stochastic-copula approach," Economic Modelling, Elsevier, vol. 105(C).
   24. Albulescu, Claudiu Tiberiu & Aubin, Christian & Goyeau, Daniel & Tiwari, Aviral Kumar, 2018. "Extreme co-movements and dependencies among major international exchange rates: A copula approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 56-69.
   25. Toan Luu Duc Huynh, 2019. "Spillover Risks on Cryptocurrency Markets: A Look from VAR-SVAR Granger Causality and Student’s-t Copulas," JRFM, MDPI, vol. 12(2), pages 1-19, April.
   26. Emmanuel Afuecheta & Saralees Nadarajah & Stephen Chan, 2021. "A Statistical Analysis of Global Economies Using Time Varying Copulas," Computational Economics, Springer;Society for Computational Economics, vol. 58(4), pages 1167-1194, December.
   27. Zou, Yingchao & Yu, Lean & Tso, Geoffrey K.F. & He, Kaijian, 2020. "Risk forecasting in the crude oil market: A multiscale Convolutional Neural Network approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).
   28. Antonio Díaz & Gonzalo García-Donato & Andrés Mora-Valencia, 2019. "Quantifying Risk in Traditional Energy and Sustainable Investments," Sustainability, MDPI, vol. 11(3), pages 1-22, January.
   29. Ahmed Jeribi & Mohamed Fakhfekh, 2021. "Portfolio management and dependence structure between cryptocurrencies and traditional assets: evidence from FIEGARCH-EVT-Copula," Journal of Asset Management, Palgrave Macmillan, vol. 22(3), pages 224-239, May.
   30. Chai, Shanglei & Zhou, P., 2018. "The Minimum-CVaR strategy with semi-parametric estimation in carbon market hedging problems," Energy Economics, Elsevier, vol. 76(C), pages 64-75.

5. Ahmed Ghorbel & Abdelwahed Trabelsi, 2013. "The impact of global financial crisis on the dependence structure of equity markets and on risk management," International Journal of Managerial and Financial Accounting, Inderscience Enterprises Ltd, vol. 5(1), pages 1-32.

   Cited by:

   1. Elisa Giacosa & Alberto Mazzoleni, 2016. "A decision model for the suitable financing for small and medium enterprises," International Journal of Managerial and Financial Accounting, Inderscience Enterprises Ltd, vol. 8(1), pages 39-74.

6. Ahmed Ghorbel & Abdelwahed Trabelsi, 2012. "Optimal dynamic hedging strategy with futures oil markets via FIEGARCH-EVT copula models," International Journal of Managerial and Financial Accounting, Inderscience Enterprises Ltd, vol. 4(1), pages 1-28.

   Cited by:

   1. Wang, Shuang & Wallace, Stein W. & Lu, Jing & Gu, Yewen, 2020. "Handling financial risks in crude oil imports: Taking into account crude oil prices as well as country and transportation risks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).
   2. Ahmed Ghorbel & Wajdi Hamma & Anis Jarboui, 2017. "Dependence between oil and commodities markets using time-varying Archimedean copulas and effectiveness of hedging strategies," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(9), pages 1509-1542, July.

More information

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Statistics

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NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 1 paper announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.

1. NEP-ECM: Econometrics (1) 2007-07-13
2. NEP-FOR: Forecasting (1) 2007-07-13
3. NEP-RMG: Risk Management (1) 2007-07-13

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