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Estimating portfolio value-at-risk via dynamic conditional correlation MGARCH model - an empirical study on foreign exchange rates

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  • Yuan-Hung Hsu Ku
  • Jai Jen Wang

Abstract

This study compares efficiencies of five Generalised Autoregressive Conditional Heteroskedasticity (GARCH) models in terms of value at risk (VaR) backtesting on the number of prediction failures and the average deviation between VaR and realized return series. Unlike the previous literature which presumes constant correlation coefficients, a new model proposed by Engle (2002, the DCC model) is applied to highlight time-varying conditional correlations amongst positions, which is essential for portfolio risk management. From the empirical studies of exchange rates data including the US Dollar to British Pound, Japanese Yen and Euro Dollar, we find that the DCC model produces least prediction failures.

Suggested Citation

  • Yuan-Hung Hsu Ku & Jai Jen Wang, 2008. "Estimating portfolio value-at-risk via dynamic conditional correlation MGARCH model - an empirical study on foreign exchange rates," Applied Economics Letters, Taylor & Francis Journals, vol. 15(7), pages 533-538.
    • Handle: RePEc:taf:apeclt:v:15:y:2008:i:7:p:533-538
    DOI: 10.1080/13504850600706958
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    Citations

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    Cited by:

    1. Toyoshima, Yuki & Hamori, Shigeyuki, 2013. "Asymmetric dynamics in stock market correlations: Evidence from Japan and Singapore," Journal of Asian Economics, Elsevier, vol. 24(C), pages 117-123.
    2. Toyoshima, Yuki & Tamakoshi, Go & Hamori, Shigeyuki, 2012. "Asymmetric dynamics in correlations of treasury and swap markets: Evidence from the US market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(2), pages 381-394.
    3. 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.
    4. Md Akther Uddin & Md Hakim Ali & Mansur Masih, 2020. "Bitcoin—A hype or digital gold? Global evidence," Australian Economic Papers, Wiley Blackwell, vol. 59(3), pages 215-231, September.
    5. Md Hakim Ali & Md Akther Uddin & Md. Atiqur Rahman Khan & Blake Goud, 2021. "Faith‐based versus value‐based finance: Is there any portfolio diversification benefit between responsible and Islamic finance?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5570-5583, October.
    6. BONGA-BONGA, Lumengo & NLEYA, Lebogang, 2018. "Assessing Portfolio Market Risk in the BRICS Economies: Use of Multivariate GARCH Models," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 71(2), pages 87-128.
    7. 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.
    8. Paresh Kumar Narayan & Syed Aun R. Rizvi & Ali Sakti, 2022. "Did green debt instruments aid diversification during the COVID-19 pandemic?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-15, December.

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