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Portfolio optimization based on GARCH-EVT-Copula forecasting models

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Cited by:

  1. Wang, Bo & Xiao, Yang, 2023. "Risk spillovers from China's and the US stock markets during high-volatility periods: Evidence from East Asianstock markets," International Review of Financial Analysis, Elsevier, vol. 86(C).
  2. Díaz, Antonio & Esparcia, Carlos, 2021. "Dynamic optimal portfolio choice under time-varying risk aversion," International Economics, Elsevier, vol. 166(C), pages 1-22.
  3. Yang Zhao & Charalampos Stasinakis & Georgios Sermpinis & Filipa Da Silva Fernandes, 2019. "Revisiting Fama–French factors' predictability with Bayesian modelling and copula‐based portfolio optimization," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(4), pages 1443-1463, October.
  4. Cheng Peng & Young Shin Kim & Stefan Mittnik, 2022. "Portfolio Optimization on Multivariate Regime-Switching GARCH Model with Normal Tempered Stable Innovation," JRFM, MDPI, vol. 15(5), pages 1-23, May.
  5. Gaete, Michael & Herrera, Rodrigo, 2023. "Diversification benefits of commodities in portfolio allocation: A dynamic factor copula approach," Journal of Commodity Markets, Elsevier, vol. 32(C).
  6. John Weirstrass Muteba Mwamba & Sutene Mwambetania Mwambi, 2021. "Assessing Market Risk in BRICS and Oil Markets: An Application of Markov Switching and Vine Copula," IJFS, MDPI, vol. 9(2), pages 1-22, May.
  7. Esparcia, Carlos & Jareño, Francisco & Umar, Zaghum, 2022. "Revisiting the safe haven role of Gold across time and frequencies during the COVID-19 pandemic," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).
  8. Xue Deng & Ying Liang, 2023. "Robust Portfolio Optimization Based on Semi-Parametric ARMA-TGARCH-EVT Model with Mixed Copula Using WCVaR," Computational Economics, Springer;Society for Computational Economics, vol. 61(1), pages 267-294, January.
  9. Vidal-Llana, Xenxo & Guillén, Montserrat, 2022. "Cross-sectional quantile regression for estimating conditional VaR of returns during periods of high volatility," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
  10. Zhi, Bangdong & Wang, Xiaojun & Xu, Fangming, 2022. "Managing inventory financing in a volatile market: A novel data-driven copula model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 165(C).
  11. Zhi, Bangdong & Wang, Xiaojun & Xu, Fangming, 2020. "Impawn rate optimisation in inventory financing: A canonical vine copula-based approach," International Journal of Production Economics, Elsevier, vol. 227(C).
  12. Dodo Natatou Moutari & Hassane Abba Mallam & Diakarya Barro & Bisso Saley, 2021. "Dependence Modeling and Risk Assessment of a Financial Portfolio with ARMA-APARCH-EVT models based on HACs," Papers 2105.09473, arXiv.org.
  13. Maziar Sahamkhadam, 2021. "Dynamic copula-based expectile portfolios," Journal of Asset Management, Palgrave Macmillan, vol. 22(3), pages 209-223, May.
  14. Zhu, Pengfei & Tang, Yong & Wei, Yu & Dai, Yimin, 2019. "Portfolio strategy of International crude oil markets: A study based on multiwavelet denoising-integration MF-DCCA method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
  15. Wang, Haiying & Yuan, Ying & Li, Yiou & Wang, Xunhong, 2021. "Financial contagion and contagion channels in the forex market: A new approach via the dynamic mixture copula-extreme value theory," Economic Modelling, Elsevier, vol. 94(C), pages 401-414.
  16. Akhtaruzzaman, Md & Banerjee, Ameet Kumar & Boubaker, Sabri & Moussa, Faten, 2023. "Does green improve portfolio optimisation?," Energy Economics, Elsevier, vol. 124(C).
  17. Rewat Khanthaporn, 2022. "Analysis of Nonlinear Comovement of Benchmark Thai Government Bond Yields," PIER Discussion Papers 183, Puey Ungphakorn Institute for Economic Research.
  18. Fen Li & Zhehao Huang & Junhao Zhong & Khaldoon Albitar, 2020. "Do Tense Geopolitical Factors Drive Crude Oil Prices?," Energies, MDPI, vol. 13(16), pages 1-20, August.
  19. Sahamkhadam, Maziar & Stephan, Andreas & Östermark, Ralf, 2022. "Copula-based Black–Litterman portfolio optimization," European Journal of Operational Research, Elsevier, vol. 297(3), pages 1055-1070.
  20. Davide Lauria & W. Brent Lindquist & Svetlozar T. Rachev, 2023. "Enhancing CVaR portfolio optimisation performance with GAM factor models," Papers 2401.00188, arXiv.org.
  21. Xiao, Yang, 2020. "The risk spillovers from the Chinese stock market to major East Asian stock markets: A MSGARCH-EVT-copula approach," International Review of Economics & Finance, Elsevier, vol. 65(C), pages 173-186.
  22. Hanif, Waqas & Areola Hernandez, Jose & Troster, Victor & Kang, Sang Hoon & Yoon, Seong-Min, 2022. "Nonlinear dependence and spillovers between cryptocurrency and global/regional equity markets," Pacific-Basin Finance Journal, Elsevier, vol. 74(C).
  23. Maziar Sahamkhadam & Andreas Stephan, 2019. "Portfolio optimization based on forecasting models using vine copulas: An empirical assessment for the financial crisis," Papers 1912.10328, arXiv.org.
  24. Zhang, Xiaoming & Zhang, Tong & Lee, Chien-Chiang, 2022. "The path of financial risk spillover in the stock market based on the R-vine-Copula model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
  25. 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.
  26. Fuentes, Fernanda & Herrera, Rodrigo & Clements, Adam, 2023. "Forecasting extreme financial risk: A score-driven approach," International Journal of Forecasting, Elsevier, vol. 39(2), pages 720-735.
  27. Díaz, Antonio & Esparcia, Carlos & López, Raquel, 2022. "The diversifying role of socially responsible investments during the COVID-19 crisis: A risk management and portfolio performance analysis," Economic Analysis and Policy, Elsevier, vol. 75(C), pages 39-60.
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