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Estimating value at risk of portfolio by conditional copula-GARCH method

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Cited by:

  1. Shim Jeungbo & Lee Seung-Hwan, 2017. "Dependency between Risks and the Insurer’s Economic Capital: A Copula-based GARCH Model," Asia-Pacific Journal of Risk and Insurance, De Gruyter, vol. 11(1), pages 1-29, January.
  2. Stanislav Anatolyev & Vladimir Pyrlik, 2021. "Shrinkage for Gaussian and t Copulas in Ultra-High Dimensions," CERGE-EI Working Papers wp699, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
  3. Leh-Chyan So & Jun-Yang Yu, 2015. "IMPROVED DETECTION OF RARE-EVENT RISK OF A PORTFOLIO WITH U.S. REITs," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 10(02), pages 1-25, December.
  4. Mawuli Segnon & Mark Trede, 2018. "Forecasting market risk of portfolios: copula-Markov switching multifractal approach," The European Journal of Finance, Taylor & Francis Journals, vol. 24(14), pages 1123-1143, September.
  5. Sahamkhadam, Maziar & Stephan, Andreas & Östermark, Ralf, 2018. "Portfolio optimization based on GARCH-EVT-Copula forecasting models," International Journal of Forecasting, Elsevier, vol. 34(3), pages 497-506.
  6. Karmakar, Madhusudan, 2017. "Dependence structure and portfolio risk in Indian foreign exchange market: A GARCH-EVT-Copula approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 64(C), pages 275-291.
  7. Marius Lux & Wolfgang Karl Hardle & Stefan Lessmann, 2020. "Data driven value-at-risk forecasting using a SVR-GARCH-KDE hybrid," Papers 2009.06910, arXiv.org.
  8. Ales Kresta & Tomas Tichy, 2012. "International Equity Portfolio Risk Modeling: The Case of the NIG Model and Ordinary Copula Functions," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 62(2), pages 141-161, May.
  9. Swanepoel, J.W.H. & Allison, J.S., 2013. "Some new results on the empirical copula estimator with applications," Statistics & Probability Letters, Elsevier, vol. 83(7), pages 1731-1739.
  10. Li, Feng & Kang, Yanfei, 2018. "Improving forecasting performance using covariate-dependent copula models," International Journal of Forecasting, Elsevier, vol. 34(3), pages 456-476.
  11. Han, Yingying & Gong, Pu & Zhou, Xiang, 2016. "Correlations and risk contagion between mixed assets and mixed-asset portfolio VaR measurements in a dynamic view: An application based on time varying copula models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 940-953.
  12. Tian, Maoxi & Ji, Hao, 2022. "GARCH copula quantile regression model for risk spillover analysis," Finance Research Letters, Elsevier, vol. 44(C).
  13. 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.
  14. Mirela NICHITA, 2015. "An Overview On State Of Knowledge Of Risk And Risk Management In Economics Fields," SEA - Practical Application of Science, Romanian Foundation for Business Intelligence, Editorial Department, issue 7, pages 423-430, April.
  15. Jinyu Zhang & Kang Gao & Yong Li & Qiaosen Zhang, 2022. "Maximum Likelihood Estimation Methods for Copula Models," Computational Economics, Springer;Society for Computational Economics, vol. 60(1), pages 99-124, June.
  16. Koike, Takaaki & Hofert, Marius, 2021. "Modality for scenario analysis and maximum likelihood allocation," Insurance: Mathematics and Economics, Elsevier, vol. 97(C), pages 24-43.
  17. Zhu, Hui-Ming & Li, Rong & Li, Sufang, 2014. "Modelling dynamic dependence between crude oil prices and Asia-Pacific stock market returns," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 208-223.
  18. Wenming Shi & Kevin X. Li & Zhongzhi Yang & Ganggang Wang, 2017. "Time-varying copula models in the shipping derivatives market," Empirical Economics, Springer, vol. 53(3), pages 1039-1058, November.
  19. Muteba Mwamba, John & Mokwena, Paula, 2013. "International diversification and dependence structure of equity portfolios during market crashes: the Archimedean copula approach," MPRA Paper 64384, University Library of Munich, Germany.
  20. Ahmet Akca & Ethem Çanakoğlu, 2021. "Adaptive stochastic risk estimation of firm operating profit," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 48(3), pages 463-504, September.
  21. Bony Josaphat & Khreshna Syuhada, 2020. "Dependent Conditional Value-at-Risk for Aggregate Risk Models," Papers 2009.02904, arXiv.org.
  22. Gijbels, Irène & Herrmann, Klaus, 2014. "On the distribution of sums of random variables with copula-induced dependence," Insurance: Mathematics and Economics, Elsevier, vol. 59(C), pages 27-44.
  23. Quanrui Song & Jianxu Liu & Songsak Sriboonchitta, 2019. "Risk Measurement of Stock Markets in BRICS, G7, and G20: Vine Copulas versus Factor Copulas," Mathematics, MDPI, vol. 7(3), pages 1-16, March.
  24. Wang Ruihua & Wang Hongjun, 2020. "Correlation Analysis of Stock Market and Fund Market Based on M-Copula-EGARCH-M-GED Model," Journal of Systems Science and Information, De Gruyter, vol. 8(3), pages 240-252, June.
  25. Takaaki Koike & Marius Hofert, 2020. "Modality for Scenario Analysis and Maximum Likelihood Allocation," Papers 2005.02950, arXiv.org, revised Nov 2020.
  26. Huang, Hung-Hsi & Lin, Shin-Hung & Wang, Ching-Ping & Chiu, Chia-Yung, 2014. "Adjusting MV-efficient portfolio frontier bias for skewed and non-mesokurtic returns," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 59-83.
  27. Tian, Maoxi & Alshater, Muneer M. & Yoon, Seong-Min, 2022. "Dynamic risk spillovers from oil to stock markets: Fresh evidence from GARCH copula quantile regression-based CoVaR model," Energy Economics, Elsevier, vol. 115(C).
  28. Yu, Xing & Zhang, Wei Guo & Liu, Yong Jun & Wang, Xinxin & Wang, Chao, 2020. "Hedging the exchange rate risk for international portfolios," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 173(C), pages 85-104.
  29. Kaijian He & Kin Keung Lai & Guocheng Xiang, 2012. "Portfolio Value at Risk Estimate for Crude Oil Markets: A Multivariate Wavelet Denoising Approach," Energies, MDPI, vol. 5(4), pages 1-26, April.
  30. Liu, Xiang-dong & Pan, Fei & Cai, Wen-li & Peng, Rui, 2020. "Correlation and risk measurement modeling: A Markov-switching mixed Clayton copula approach," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
  31. Berger, Theo, 2016. "On the isolated impact of copulas on risk measurement: Asimulation study," Economic Modelling, Elsevier, vol. 58(C), pages 475-481.
  32. He, Kaijian & Wang, Lijun & Zou, Yingchao & Lai, Kin Keung, 2014. "Value at risk estimation with entropy-based wavelet analysis in exchange markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 408(C), pages 62-71.
  33. Chakraborty, Sandip & Kakani, Ram Kumar & Sampath, Aravind, 2022. "Portfolio risk and stress across the business cycle," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
  34. Aleš Kresta, 2015. "Application of Performance Ratios in Portfolio Optimization," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 63(6), pages 1969-1977.
  35. Mokni, Khaled & Mansouri, Faysal, 2017. "Conditional dependence between international stock markets: A long memory GARCH-copula model approach," Journal of Multinational Financial Management, Elsevier, vol. 42, pages 116-131.
  36. Marius Galabe Sampid & Haslifah M Hasim & Hongsheng Dai, 2018. "Refining value-at-risk estimates using a Bayesian Markov-switching GJR-GARCH copula-EVT model," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-33, June.
  37. Nader Trabelsi & Aviral Kumar Tiwari, 2019. "Market-Risk Optimization among the Developed and Emerging Markets with CVaR Measure and Copula Simulation," Risks, MDPI, vol. 7(3), pages 1-20, July.
  38. Tian, Maoxi & Guo, Fei & Niu, Rong, 2022. "Risk spillover analysis of China’s financial sectors based on a new GARCH copula quantile regression model," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
  39. Anatolyev, Stanislav & Pyrlik, Vladimir, 2022. "Copula shrinkage and portfolio allocation in ultra-high dimensions," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
  40. Zhang, Bangzheng & Wei, Yu & Yu, Jiang & Lai, Xiaodong & Peng, Zhenfeng, 2014. "Forecasting VaR and ES of stock index portfolio: A Vine copula method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 112-124.
  41. Joel Hinaunye Eita & Charles Raoul Tchuinkam Djemo, 2022. "Quantifying Foreign Exchange Risk in the Selected Listed Sectors of the Johannesburg Stock Exchange: An SV-EVT Pairwise Copula Approach," IJFS, MDPI, vol. 10(2), pages 1-29, April.
  42. Aristeidis, Samitas & Elias, Kampouris, 2018. "Empirical analysis of market reactions to the UK’s referendum results – How strong will Brexit be?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 53(C), pages 263-286.
  43. Tahani S. Alotaibi & Luciana Dalla Valle & Matthew J. Craven, 2022. "The Worst Case GARCH-Copula CVaR Approach for Portfolio Optimisation: Evidence from Financial Markets," JRFM, MDPI, vol. 15(10), pages 1-14, October.
  44. Chunliang Deng & Xingfa Zhang & Yuan Li & Qiang Xiong, 2020. "Garch Model Test Using High-Frequency Data," Mathematics, MDPI, vol. 8(11), pages 1-17, November.
  45. EnDer Su, 2018. "Measuring contagion risk in high volatility state among Taiwanese major banks," Risk Management, Palgrave Macmillan, vol. 20(3), pages 185-241, August.
  46. Berger, T. & Missong, M., 2014. "Financial crisis, Value-at-Risk forecasts and the puzzle of dependency modeling," International Review of Financial Analysis, Elsevier, vol. 33(C), pages 33-38.
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