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Samir Mabrouk

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First Name:Samir
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Last Name:Mabrouk
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RePEc Short-ID:pma1659
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Articles

  1. Mabrouk, Samir & Saadi, Samir, 2012. "Parametric Value-at-Risk analysis: Evidence from stock indices," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(3), pages 305-321.
  2. Aloui, Chaker & Mabrouk, Samir, 2010. "Value-at-risk estimations of energy commodities via long-memory, asymmetry and fat-tailed GARCH models," Energy Policy, Elsevier, vol. 38(5), pages 2326-2339, May.
  3. Samir Mabrouk & Chaker Aloui, 2010. "One-day-ahead value-at-risk estimations with dual long-memory models: evidence from the Tunisian stock market," International Journal of Financial Services Management, Inderscience Enterprises Ltd, vol. 4(2), pages 77-94.

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.

Articles

  1. Mabrouk, Samir & Saadi, Samir, 2012. "Parametric Value-at-Risk analysis: Evidence from stock indices," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(3), pages 305-321.

    Cited by:

    1. Laura Garcia‐Jorcano & Alfonso Novales, 2021. "Volatility specifications versus probability distributions in VaR forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(2), pages 189-212, March.
    2. Kurita, Takamitsu, 2014. "Dynamic characteristics of the daily yen–dollar exchange rate," Research in International Business and Finance, Elsevier, vol. 30(C), pages 72-82.
    3. Onder Buberkoku, 2018. "Examining the Value-at-risk Performance of Fractionally Integrated GARCH Models: Evidence from Energy Commodities," International Journal of Economics and Financial Issues, Econjournals, vol. 8(3), pages 36-50.
    4. Lingbing Feng & Yanlin Shi, 2017. "A simulation study on the distributions of disturbances in the GARCH model," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1355503-135, January.
    5. Chkili, Walid & Hammoudeh, Shawkat & Nguyen, Duc Khuong, 2014. "Volatility forecasting and risk management for commodity markets in the presence of asymmetry and long memory," Energy Economics, Elsevier, vol. 41(C), pages 1-18.
    6. Muhammad Sheraz & Imran Nasir, 2021. "Information-Theoretic Measures and Modeling Stock Market Volatility: A Comparative Approach," Risks, MDPI, vol. 9(5), pages 1-20, May.
    7. Bagher Adabi & Mohsen Mehrara & Shapour Mohammadi, 2015. "Evaluation Approaches of Value at Risk for Tehran Stock Exchange," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 19(1), pages 41-62, Winter.
    8. Righi, Marcelo Brutti & Ceretta, Paulo Sergio, 2015. "A comparison of Expected Shortfall estimation models," Journal of Economics and Business, Elsevier, vol. 78(C), pages 14-47.
    9. Aloui, Chaker & Hamida, Hela ben, 2014. "Modelling and forecasting value at risk and expected shortfall for GCC stock markets: Do long memory, structural breaks, asymmetry, and fat-tails matter?," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 349-380.
    10. Toktam Valizadeh & Saeid Rezakhah & Ferdous Mohammadi Basatini, 2021. "On time‐varying amplitude HGARCH model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2538-2547, April.
    11. Ibrahim Ergen, 2015. "Two-step methods in VaR prediction and the importance of fat tails," Quantitative Finance, Taylor & Francis Journals, vol. 15(6), pages 1013-1030, June.
    12. Chkili, Walid & Aloui, Chaker & Nguyen, Duc Khuong, 2014. "Instabilities in the relationships and hedging strategies between crude oil and US stock markets: Do long memory and asymmetry matter?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 33(C), pages 354-366.
    13. Sherzod N. Tashpulatov, 2021. "The Impact of Regulatory Reforms on Demand Weighted Average Prices," Mathematics, MDPI, vol. 9(10), pages 1-15, May.
    14. Shi, Yanlin & Feng, Lingbing, 2016. "A discussion on the innovation distribution of the Markov regime-switching GARCH model," Economic Modelling, Elsevier, vol. 53(C), pages 278-288.
    15. Tong Liu & Yanlin Shi, 2022. "Innovation of the Component GARCH Model: Simulation Evidence and Application on the Chinese Stock Market," Mathematics, MDPI, vol. 10(11), pages 1-18, June.
    16. Manel Youssef & Lotfi Belkacem & Khaled Mokni, 2015. "Extreme Value Theory and long-memory-GARCH Framework: Application to Stock Market," International Journal of Economics and Empirical Research (IJEER), The Economics and Social Development Organization (TESDO), vol. 3(8), pages 371-388, August.
    17. James Ming Chen, 2018. "On Exactitude in Financial Regulation: Value-at-Risk, Expected Shortfall, and Expectiles," Risks, MDPI, vol. 6(2), pages 1-28, June.
    18. Chkili, Walid & Ben Rejeb, Aymen & Arfaoui, Mongi, 2021. "Does bitcoin provide hedge to Islamic stock markets for pre- and during COVID-19 outbreak? A comparative analysis with gold," Resources Policy, Elsevier, vol. 74(C).

  2. Aloui, Chaker & Mabrouk, Samir, 2010. "Value-at-risk estimations of energy commodities via long-memory, asymmetry and fat-tailed GARCH models," Energy Policy, Elsevier, vol. 38(5), pages 2326-2339, May.

    Cited by:

    1. Mohamed Chikhi & Anne Peguin-Feissolle & Michel Terraza, 2013. "SEMIFARMA-HYGARCH Modeling of Dow Jones Return Persistence," Post-Print hal-01499630, HAL.
    2. Lyu, Yongjian & Wang, Peng & Wei, Yu & Ke, Rui, 2017. "Forecasting the VaR of crude oil market: Do alternative distributions help?," Energy Economics, Elsevier, vol. 66(C), pages 523-534.
    3. Demiralay, Sercan & Ulusoy, Veysel, 2014. "Value-at-risk Predictions of Precious Metals with Long Memory Volatility Models," MPRA Paper 53229, University Library of Munich, Germany.
    4. Wang, Yudong & Wu, Chongfeng, 2012. "Forecasting energy market volatility using GARCH models: Can multivariate models beat univariate models?," Energy Economics, Elsevier, vol. 34(6), pages 2167-2181.
    5. Aloui, Chaker & Hammoudeh, Shawkat & Hamida, Hela ben, 2015. "Global factors driving structural changes in the co-movement between sharia stocks and sukuk in the Gulf Cooperation Council countries," The North American Journal of Economics and Finance, Elsevier, vol. 31(C), pages 311-329.
    6. Wei, Yu & Wang, Yudong & Huang, Dengshi, 2010. "Forecasting crude oil market volatility: Further evidence using GARCH-class models," Energy Economics, Elsevier, vol. 32(6), pages 1477-1484, November.
    7. Auer, Benjamin R., 2015. "Does the choice of performance measure influence the evaluation of commodity investments?," International Review of Financial Analysis, Elsevier, vol. 38(C), pages 142-150.
    8. Laporta, Alessandro G. & Merlo, Luca & Petrella, Lea, 2018. "Selection of Value at Risk Models for Energy Commodities," Energy Economics, Elsevier, vol. 74(C), pages 628-643.
    9. Hammoudeh, Shawkat & Araújo Santos, Paulo & Al-Hassan, Abdullah, 2013. "Downside risk management and VaR-based optimal portfolios for precious metals, oil and stocks," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 318-334.
    10. Fernandes, Leonardo H.S. & Araújo, Fernando H.A., 2020. "Taxonomy of commodities assets via complexity-entropy causality plane," Chaos, Solitons & Fractals, Elsevier, vol. 137(C).
    11. Zouheir Mighri & Raouf Jaziri, 2023. "Long-Memory, Asymmetry and Fat-Tailed GARCH Models in Value-at-Risk Estimation: Empirical Evidence from the Global Real Estate Markets," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 21(1), pages 41-97, March.
    12. Ding, Yishan, 2018. "A novel decompose-ensemble methodology with AIC-ANN approach for crude oil forecasting," Energy, Elsevier, vol. 154(C), pages 328-336.
    13. Lin, Ling & Jiang, Yong & Xiao, Helu & Zhou, Zhongbao, 2020. "Crude oil price forecasting based on a novel hybrid long memory GARCH-M and wavelet analysis model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 543(C).
    14. Med Imen Gallali & Raggad Zahraa, 2012. "Evaluation of VaR models' forecasting performance: the case of oil markets," International Journal of Financial Services Management, Inderscience Enterprises Ltd, vol. 5(3), pages 197-215.
    15. 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.
    16. Demiralay, Sercan & Ulusoy, Veysel, 2014. "Non-linear volatility dynamics and risk management of precious metals," The North American Journal of Economics and Finance, Elsevier, vol. 30(C), pages 183-202.
    17. Herrera, Rodrigo & Rodriguez, Alejandro & Pino, Gabriel, 2017. "Modeling and forecasting extreme commodity prices: A Markov-Switching based extreme value model," Energy Economics, Elsevier, vol. 63(C), pages 129-143.
    18. Hayette Gatfaoui, 2015. "Pricing the (European) option to switch between two energy sources: An application to crude oil and natural gas," Post-Print hal-01563015, HAL.
    19. Onder Buberkoku, 2018. "Examining the Value-at-risk Performance of Fractionally Integrated GARCH Models: Evidence from Energy Commodities," International Journal of Economics and Financial Issues, Econjournals, vol. 8(3), pages 36-50.
    20. Haider Ali & Faheem Aslam & Paulo Ferreira, 2021. "Modeling Dynamic Multifractal Efficiency of US Electricity Market," Energies, MDPI, vol. 14(19), pages 1-16, September.
    21. 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.
    22. Chkili, Walid & Aloui, Chaker & Nguyen, Duc Khuong, 2012. "Asymmetric effects and long memory in dynamic volatility relationships between stock returns and exchange rates," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(4), pages 738-757.
    23. Lin, Ling & Zhou, Zhongbao & Jiang, Yong & Ou, Yangchen, 2021. "Risk spillovers and hedge strategies between global crude oil markets and stock markets: Do regime switching processes combining long memory and asymmetry matter?," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    24. Kang, Sang Hoon & Yoon, Seong-Min, 2013. "Modeling and forecasting the volatility of petroleum futures prices," Energy Economics, Elsevier, vol. 36(C), pages 354-362.
    25. Cochran, Steven J. & Mansur, Iqbal & Odusami, Babatunde, 2012. "Volatility persistence in metal returns: A FIGARCH approach," Journal of Economics and Business, Elsevier, vol. 64(4), pages 287-305.
    26. 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.
    27. Mila Andreani & Vincenzo Candila & Giacomo Morelli & Lea Petrella, 2021. "Multivariate Analysis of Energy Commodities during the COVID-19 Pandemic: Evidence from a Mixed-Frequency Approach," Risks, MDPI, vol. 9(8), pages 1-20, August.
    28. Shen, Yifan & Shi, Xunpeng & Variam, Hari Malamakkavu Padinjare, 2018. "Risk transmission mechanism between energy markets: A VAR for VaR approach," Energy Economics, Elsevier, vol. 75(C), pages 377-388.
    29. Marius Lux & Wolfgang Karl Härdle & Stefan Lessmann, 2020. "Data driven value-at-risk forecasting using a SVR-GARCH-KDE hybrid," Computational Statistics, Springer, vol. 35(3), pages 947-981, September.
    30. Patra, Saswat, 2021. "Revisiting value-at-risk and expected shortfall in oil markets under structural breaks: The role of fat-tailed distributions," Energy Economics, Elsevier, vol. 101(C).
    31. Zolotko, Mikhail & Okhrin, Ostap, 2014. "Modelling the general dependence between commodity forward curves," Energy Economics, Elsevier, vol. 43(C), pages 284-296.
    32. Mason, Charles F. & Wilmot, Neil A., 2020. "Jumps in the convenience yield of crude oil," Resource and Energy Economics, Elsevier, vol. 60(C).
    33. Halkos, George & Tsirivis, Apostolos, 2019. "Using Value-at-Risk for effective energy portfolio risk management," MPRA Paper 91674, University Library of Munich, Germany.
    34. Maitra, Debasish & Rehman, Mobeen Ur & Dash, Saumya Ranjan & Kang, Sang Hoon, 2021. "Oil price volatility and the logistics industry: Dynamic connectedness with portfolio implications," Energy Economics, Elsevier, vol. 102(C).
    35. Garcia-Jorcano, Laura & Sanchis-Marco, Lidia, 2022. "Spillover effects between commodity and stock markets: A SDSES approach," Resources Policy, Elsevier, vol. 79(C).
    36. Chkili, Walid & Hammoudeh, Shawkat & Nguyen, Duc Khuong, 2014. "Volatility forecasting and risk management for commodity markets in the presence of asymmetry and long memory," Energy Economics, Elsevier, vol. 41(C), pages 1-18.
    37. Julia S. Mehlitz & Benjamin R. Auer, 2021. "Time‐varying dynamics of expected shortfall in commodity futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(6), pages 895-925, June.
    38. Samet Gunay & Audil Rashid Khaki, 2018. "Best Fitting Fat Tail Distribution for the Volatilities of Energy Futures: Gev, Gat and Stable Distributions in GARCH and APARCH Models," JRFM, MDPI, vol. 11(2), pages 1-19, June.
    39. Liyuan Chen & Paola Zerilli & Christopher F Baum, 2018. "Leverage effects and stochastic volatility in spot oil returns: A Bayesian approach with VaR and CVaR applications," Boston College Working Papers in Economics 953, Boston College Department of Economics.
    40. Fernandes, Leonardo H.S. & de Araújo, Fernando H.A. & Silva, Igor E.M., 2020. "The (in)efficiency of NYMEX energy futures: A multifractal analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(C).
    41. Jim Hanly, 2017. "Managing Energy Price Risk using Futures Contracts: A Comparative Analysis," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    42. Wei Kuang, 2022. "Oil tail-risk forecasts: from financial crisis to COVID-19," Risk Management, Palgrave Macmillan, vol. 24(4), pages 420-460, December.
    43. Zhi-Fu Mi & Yi-Ming Wei & Bao-Jun Tang & Rong-Gang Cong & Hao Yu & Hong Cao & Dabo Guan, 2017. "Risk assessment of oil price from static and dynamic modelling approaches," Applied Economics, Taylor & Francis Journals, vol. 49(9), pages 929-939, February.
    44. František Čech & Jozef Baruník, 2019. "Panel quantile regressions for estimating and predicting the value‐at‐risk of commodities," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(9), pages 1167-1189, September.
    45. Wang, Yudong & Wu, Chongfeng & Wei, Yu, 2011. "Can GARCH-class models capture long memory in WTI crude oil markets?," Economic Modelling, Elsevier, vol. 28(3), pages 921-927, May.
    46. Bagher Adabi & Mohsen Mehrara & Shapour Mohammadi, 2015. "Evaluation Approaches of Value at Risk for Tehran Stock Exchange," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 19(1), pages 41-62, Winter.
    47. Walid Chkili, 2015. "Gold–oil prices co-movements and portfolio diversification implications," Economics Bulletin, AccessEcon, vol. 35(4), pages 2832-2845.
    48. Wang, Yudong & Liu, Li & Ma, Feng & Wu, Chongfeng, 2016. "What the investors need to know about forecasting oil futures return volatility," Energy Economics, Elsevier, vol. 57(C), pages 128-139.
    49. Walid Chkili, 2021. "Modeling Bitcoin price volatility: long memory vs Markov switching," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 11(3), pages 433-448, September.
    50. Onder Buberkoku, 2019. "Do Long-memory GARCH-type-Value-at-Risk Models Outperform None-and Semi-parametric Value-at-Risk Models?," International Journal of Energy Economics and Policy, Econjournals, vol. 9(2), pages 199-215.
    51. Delavari, Majid & Gandali Alikhani, Nadiya & Naderi, Esmaeil, 2013. "Does long memory matter in forecasting oil price volatility?," MPRA Paper 46356, University Library of Munich, Germany.
    52. Joëts, Marc, 2014. "Energy price transmissions during extreme movements," Economic Modelling, Elsevier, vol. 40(C), pages 392-399.
    53. Miroslava Zavadska & Lucía Morales & Joseph Coughlan, 2018. "The Lead–Lag Relationship between Oil Futures and Spot Prices—A Literature Review," IJFS, MDPI, vol. 6(4), pages 1-22, October.
    54. Aloui, Chaker & Hamida, Hela ben, 2014. "Modelling and forecasting value at risk and expected shortfall for GCC stock markets: Do long memory, structural breaks, asymmetry, and fat-tails matter?," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 349-380.
    55. Delavari, Majid & Gandali Alikhani, Nadiya, 2012. "The Effect of Crude Oil Price on the Methanol price," MPRA Paper 49727, University Library of Munich, Germany.
    56. Saralees Nadarajah & Emmanuel Afuecheta & Stephen Chan, 2015. "GARCH modeling of five popular commodities," Empirical Economics, Springer, vol. 48(4), pages 1691-1712, June.
    57. Lin, Boqiang & Wesseh, Presley K., 2013. "What causes price volatility and regime shifts in the natural gas market," Energy, Elsevier, vol. 55(C), pages 553-563.
    58. Abdullah Sultan Al Shammre & Benaissa Chidmi, 2023. "Oil Price Forecasting Using FRED Data: A Comparison between Some Alternative Models," Energies, MDPI, vol. 16(11), pages 1-24, May.
    59. Hasanov, Akram Shavkatovich & Shaiban, Mohammed Sharaf & Al-Freedi, Ajab, 2020. "Forecasting volatility in the petroleum futures markets: A re-examination and extension," Energy Economics, Elsevier, vol. 86(C).
    60. Youssef, Manel & Belkacem, Lotfi & Mokni, Khaled, 2015. "Value-at-Risk estimation of energy commodities: A long-memory GARCH–EVT approach," Energy Economics, Elsevier, vol. 51(C), pages 99-110.
    61. Walid Mensi & Shawkat Hammoude & Seong-Min Yoon, 2014. "Structural Breaks, Dynamic Correlations, Volatility Transmission, and Hedging Strategies for International Petroleum Prices and U.S. Dollar Exchange Rate," Working Papers 884, Economic Research Forum, revised Dec 2014.
    62. Rehman, Mobeen Ur & Owusu Junior, Peterson & Ahmad, Nasir & Vo, Xuan Vinh, 2022. "Time-varying risk analysis for commodity futures," Resources Policy, Elsevier, vol. 78(C).
    63. Halkos, George E. & Tsirivis, Apostolos S., 2019. "Value-at-risk methodologies for effective energy portfolio risk management," Economic Analysis and Policy, Elsevier, vol. 62(C), pages 197-212.
    64. Daniel Velásquez-Gaviria & Andrés Mora-Valencia & Javier Perote, 2020. "A Comparison of the Risk Quantification in Traditional and Renewable Energy Markets," Energies, MDPI, vol. 13(11), pages 1-42, June.
    65. Jain, Prachi & Maitra, Debasish & Kang, Sang Hoon, 2023. "Oil price and the automobile industry: Dynamic connectedness and portfolio implications with downside risk," Energy Economics, Elsevier, vol. 119(C).
    66. Chaker Aloui, 2015. "Volatility forecasting and risk management in some MENA stock markets: a nonlinear framework," Afro-Asian Journal of Finance and Accounting, Inderscience Enterprises Ltd, vol. 5(2), pages 160-192.
    67. Chkili, Walid, 2015. "Gold-oil prices co-movements and portfolio diversification implications," MPRA Paper 68110, University Library of Munich, Germany.
    68. Muhammad Irfan Malik & Abdul Rashid, 2017. "Return And Volatility Spillover Between Sectoral Stock And Oil Price: Evidence From Pakistan Stock Exchange," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 12(02), pages 1-22, June.
    69. He, Kaijian & Lai, Kin Keung & Yen, Jerome, 2011. "Value-at-risk estimation of crude oil price using MCA based transient risk modeling approach," Energy Economics, Elsevier, vol. 33(5), pages 903-911, September.
    70. Degenhardt, Thomas & Auer, Benjamin R., 2018. "The “Sell in May” effect: A review and new empirical evidence," The North American Journal of Economics and Finance, Elsevier, vol. 43(C), pages 169-205.
    71. Kristoufek, Ladislav, 2019. "Are the crude oil markets really becoming more efficient over time? Some new evidence," Energy Economics, Elsevier, vol. 82(C), pages 253-263.
    72. Walid Chkili & Shawkat Hammoudeh & Duc Khuong Nguyen, 2013. "Long memory and asymmetry in the volatility of commodity markets and Basel Accord: choosing between models," Working Papers 2013-9, Department of Research, Ipag Business School.
    73. Su, Ender & Wong, Kai Wen, 2018. "Measuring bank downside systemic risk in Taiwan," The Quarterly Review of Economics and Finance, Elsevier, vol. 70(C), pages 172-193.
    74. Argel S. Masa & John Francis T. Diaz, 2017. "Long-memory Modelling and Forecasting of the Returns and Volatility of Exchange-traded Notes (ETNs)," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 11(1), pages 23-53, February.
    75. Lu Yang & Shigeyuki Hamori, 2020. "Forecasts of Value-at-Risk and Expected Shortfall in the Crude Oil Market: A Wavelet-Based Semiparametric Approach," Energies, MDPI, vol. 13(14), pages 1-27, July.
    76. Morelli, Giacomo, 2023. "Stochastic ordering of systemic risk in commodity markets," Energy Economics, Elsevier, vol. 117(C).
    77. 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).
    78. Pham, Son Duy & Nguyen, Thao Thac Thanh & Do, Hung Xuan, 2022. "Dynamic volatility connectedness between thermal coal futures and major cryptocurrencies: Evidence from China," Energy Economics, Elsevier, vol. 112(C).
    79. Chkili, Walid & Aloui, Chaker & Nguyen, Duc Khuong, 2014. "Instabilities in the relationships and hedging strategies between crude oil and US stock markets: Do long memory and asymmetry matter?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 33(C), pages 354-366.
    80. Enrique Molina‐Muñoz & Andrés Mora‐Valencia & Javier Perote, 2021. "Backtesting expected shortfall for world stock index ETFs with extreme value theory and Gram–Charlier mixtures," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4163-4189, July.
    81. Alkathery, Mohammed A. & Chaudhuri, Kausik & Nasir, Muhammad Ali, 2022. "Implications of clean energy, oil and emissions pricing for the GCC energy sector stock," Energy Economics, Elsevier, vol. 112(C).
    82. Kostas Andriosopoulos & Nikos Nomikos, 2012. "Risk management in the energy markets and Value-at-Risk modelling: a Hybrid approach," RSCAS Working Papers 2012/47, European University Institute.
    83. Marchese, Malvina & Kyriakou, Ioannis & Tamvakis, Michael & Di Iorio, Francesca, 2020. "Forecasting crude oil and refined products volatilities and correlations: New evidence from fractionally integrated multivariate GARCH models," Energy Economics, Elsevier, vol. 88(C).
    84. Del Brio, Esther B. & Mora-Valencia, Andrés & Perote, Javier, 2020. "Risk quantification for commodity ETFs: Backtesting value-at-risk and expected shortfall," International Review of Financial Analysis, Elsevier, vol. 70(C).
    85. Wei, Yu, 2012. "Forecasting volatility of fuel oil futures in China: GARCH-type, SV or realized volatility models?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(22), pages 5546-5556.
    86. Mateusz Buczyński & Marcin Chlebus, 2021. "GARCHNet - Value-at-Risk forecasting with novel approach to GARCH models based on neural networks," Working Papers 2021-08, Faculty of Economic Sciences, University of Warsaw.
    87. Westgaard, Sjur & Fleten, Stein-Erik & Negash, Ahlmahz & Botterud, Audun & Bogaard, Katinka & Verling, Trude Haugsvaer, 2021. "Performing price scenario analysis and stress testing using quantile regression: A case study of the Californian electricity market," Energy, Elsevier, vol. 214(C).
    88. Lin, Boqiang & Wesseh, Presley K. & Appiah, Michael Owusu, 2014. "Oil price fluctuation, volatility spillover and the Ghanaian equity market: Implication for portfolio management and hedging effectiveness," Energy Economics, Elsevier, vol. 42(C), pages 172-182.
    89. Lang, Korbinian & Auer, Benjamin R., 2020. "The economic and financial properties of crude oil: A review," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    90. Carnero, M. Angeles & León, Angel & Ñíguez, Trino-Manuel, 2023. "Skewness in energy returns: estimation, testing and retain-->implications for tail risk," The Quarterly Review of Economics and Finance, Elsevier, vol. 90(C), pages 178-189.
    91. Markus Vogl, 2022. "Quantitative modelling frontiers: a literature review on the evolution in financial and risk modelling after the financial crisis (2008–2019)," SN Business & Economics, Springer, vol. 2(12), pages 1-69, December.
    92. Yingchao Zou & Kaijian He, 2022. "Forecasting Crude Oil Risk Using a Multivariate Multiscale Convolutional Neural Network Model," Mathematics, MDPI, vol. 10(14), pages 1-11, July.
    93. Klein, Tony & Walther, Thomas, 2016. "Oil price volatility forecast with mixture memory GARCH," Energy Economics, Elsevier, vol. 58(C), pages 46-58.
    94. 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.
    95. Chkili, Walid & Ben Rejeb, Aymen & Arfaoui, Mongi, 2021. "Does bitcoin provide hedge to Islamic stock markets for pre- and during COVID-19 outbreak? A comparative analysis with gold," Resources Policy, Elsevier, vol. 74(C).
    96. Hou, Aijun & Suardi, Sandy, 2012. "A nonparametric GARCH model of crude oil price return volatility," Energy Economics, Elsevier, vol. 34(2), pages 618-626.

  3. Samir Mabrouk & Chaker Aloui, 2010. "One-day-ahead value-at-risk estimations with dual long-memory models: evidence from the Tunisian stock market," International Journal of Financial Services Management, Inderscience Enterprises Ltd, vol. 4(2), pages 77-94.

    Cited by:

    1. Onder Buberkoku, 2018. "Examining the Value-at-risk Performance of Fractionally Integrated GARCH Models: Evidence from Energy Commodities," International Journal of Economics and Financial Issues, Econjournals, vol. 8(3), pages 36-50.
    2. Dilip Kumar, 2020. "Value-at-Risk in the Presence of Structural Breaks Using Unbiased Extreme Value Volatility Estimator," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(3), pages 587-610, September.
    3. Chaker Aloui & Hela BEN HAMIDA, 2015. "Estimation and Performance Assessment of Value-at-Risk and Expected Shortfall Based on Long-Memory GARCH-Class Models," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 65(1), pages 30-54, January.
    4. Bagher Adabi & Mohsen Mehrara & Shapour Mohammadi, 2015. "Evaluation Approaches of Value at Risk for Tehran Stock Exchange," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 19(1), pages 41-62, Winter.
    5. Aloui, Chaker & Hamida, Hela ben, 2014. "Modelling and forecasting value at risk and expected shortfall for GCC stock markets: Do long memory, structural breaks, asymmetry, and fat-tails matter?," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 349-380.
    6. Chaker Aloui, 2015. "Volatility forecasting and risk management in some MENA stock markets: a nonlinear framework," Afro-Asian Journal of Finance and Accounting, Inderscience Enterprises Ltd, vol. 5(2), pages 160-192.
    7. Mabrouk, Samir & Saadi, Samir, 2012. "Parametric Value-at-Risk analysis: Evidence from stock indices," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(3), pages 305-321.
    8. Dilip Kumar, 2016. "Estimating and forecasting value-at-risk using the unbiased extreme value volatility estimator," Proceedings of Economics and Finance Conferences 3205528, International Institute of Social and Economic Sciences.

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