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Forecasting of dependence, market, and investment risks of a global index portfolio

Author

Listed:
  • Jose Arreola Hernandez

    (Rennes SB - Rennes School of Business)

  • Mazin A.M. Al Janabi

    (ITESM - Tecnológico de Monterrey = Monterrey Institute of Technology)

Abstract

This paper undertakes an in‐sample and rolling‐window comparative analysis of dependence, market, and portfolio investment risks on a 10‐year global index portfolio of developed, emerging, and commodity markets. We draw our empirical results by fitting vine copulas (e.g., r‐vines, c‐vines, d‐vines), IGARCH(1,1) RiskMetrics value‐at‐risk (VaR), and portfolio optimization methods based on risk measures such as the variance, conditional value‐at‐risk, conditional drawdown‐at‐risk, minimizing regret (Minimax), and mean absolute deviation. The empirical results indicate that all international indices tend to correlate strongly in the negative tail of the return distribution; however, emerging markets, relative to developed and commodity markets, exhibit greater dependence, market, and portfolio investment risks. The portfolio optimization shows a clear preference towards the gold commodity for investment, while Japan and Canada are found to have the highest and lowest market risk, respectively. The vine copula analysis identifies symmetry in the dependence dynamics of the global index portfolio modeled. Large VaR diversification benefits are produced at the 95% and 99% confidence levels by the modeled international index portfolio. The empirical results may appeal to international portfolio investors and risk managers for advanced portfolio management, hedging, and risk forecasting.

Suggested Citation

  • Jose Arreola Hernandez & Mazin A.M. Al Janabi, 2019. "Forecasting of dependence, market, and investment risks of a global index portfolio," Post-Print hal-02567413, HAL.
    • Handle: RePEc:hal:journl:hal-02567413
    DOI: 10.1002/for.2641
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    2. Simbarashe Brandon MATANHIKE & Newman WADESANGO & Lovemore SITSHA, 2025. "The Impact of Gold Coin Investments on Portfolio Diversification and Risk Management in the Zimbabwean Financial Markets," CECCAR Business Review, Body of Expert and Licensed Accountants of Romania (CECCAR), vol. 6(8), pages 69-82, August.
    3. Maziar Sahamkhadam & Andreas Stephan, 2023. "Portfolio optimization based on forecasting models using vine copulas: An empirical assessment for global financial crises," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 2139-2166, December.
    4. Mengting Li & Qifa Xu & Cuixia Jiang & Yezheng Liu, 2024. "The role of long‐ and short‐run correlation networks in international portfolio selection," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(3), pages 3147-3176, July.
    5. Yanbo Zhang & Mengkun Liang & Haiying Ou, 2024. "Prediction of Precious Metal Index Based on Ensemble Learning and SHAP Interpretable Method," Computational Economics, Springer;Society for Computational Economics, vol. 64(6), pages 3243-3278, December.
    6. Zhang, Lixia & Bai, Jiancheng & Zhang, Yueyan & Cui, Can, 2023. "Global economic uncertainty and the Chinese stock market: Assessing the impacts of global indicators," Research in International Business and Finance, Elsevier, vol. 65(C).

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