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Value at Risk Analysis of Gold Price Returns Using Extreme Value Theory

Author

Listed:
  • Kittiya Chaithep

    (Chiang Mai University)

  • Songsak Sriboonchitta

    (Chiang Mai University)

  • Chukiat Chaiboonsri

    (Chiang Mai University)

  • Pathairat Pastpipatkul

    (Chiang Mai University)

Abstract

There are many approaches to evaluate the return. However, Extreme Value Theory is the right method to analysis Value at Risk of Gold Price Return. The method is covered tothe block maxima and the Peak over Thresholds modeling. This study uses a daily gold price in US dollar over the period of January 1, 1985 to August 31, 2011.The purpose is to evaluate a value at risk of the daily gold price return. It is very useful to manage a risk allocation in portfolio. Moreover, the paper is included to the return level forecasting in the next 20-years.

Suggested Citation

  • Kittiya Chaithep & Songsak Sriboonchitta & Chukiat Chaiboonsri & Pathairat Pastpipatkul, 2012. "Value at Risk Analysis of Gold Price Returns Using Extreme Value Theory," The Empirical Econometrics and Quantitative Economics Letters, Faculty of Economics, Chiang Mai University, vol. 1(4), pages 151-168, December.
    • Handle: RePEc:chi:journl:v:1:y:2012:i:4:p:151-168
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    References listed on IDEAS

    as
    1. Gencay, Ramazan & Selcuk, Faruk, 2004. "Extreme value theory and Value-at-Risk: Relative performance in emerging markets," International Journal of Forecasting, Elsevier, vol. 20(2), pages 287-303.
    2. McNeil, Alexander J. & Frey, Rudiger, 2000. "Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach," Journal of Empirical Finance, Elsevier, vol. 7(3-4), pages 271-300, November.
    3. repec:czx:journl:v:19:y:2012:i:29:id:185 is not listed on IDEAS
    4. Turan G. Bali, 2003. "An Extreme Value Approach to Estimating Volatility and Value at Risk," The Journal of Business, University of Chicago Press, vol. 76(1), pages 83-108, January.
    5. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
    6. McNeil, Alexander J., 1997. "Estimating the Tails of Loss Severity Distributions Using Extreme Value Theory," ASTIN Bulletin, Cambridge University Press, vol. 27(1), pages 117-137, May.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Zhang, Zijing & Zhang, Hong-Kun, 2016. "The dynamics of precious metal markets VaR: A GARCHEVT approach," Journal of Commodity Markets, Elsevier, vol. 4(1), pages 14-27.
    2. Hela Mzoughi & Faysal Mansouri, 2013. "Computing risk measures for non-normal asset returns using Copula theory," The Empirical Econometrics and Quantitative Economics Letters, Faculty of Economics, Chiang Mai University, vol. 2(1), pages 59-70, March.
    3. Ilhami KARAHANOGLU, 2020. "The VaR comparison of the fresh investment toolBITCOIN with other conventional investment tools, gold, stock exchange (BIST100) and foreign currencies (EUR/USD VS TRL)," Eastern Journal of European Studies, Centre for European Studies, Alexandru Ioan Cuza University, vol. 11, pages 160-181, December.

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