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Risk Analysis Using Regression Quantiles: Evidence from International Equity Markets

Author

Listed:
  • Hongtao Guo
  • Miranda S. Lam
  • Guojun Wu
  • Zhijie Xiao

Abstract

In this paper we study risk management based on the quantile regression. Unlike the traditional VaR estimation methods, the quantile regression approach allows for a general treatment on the error distribution and is robust to distributions with heavy tails. We estimate the VaRs of five international equity indexes based on AR-ARCH model via quantile regressions. The empirical application show that the quantile regression based method is well suited to handle negative skewness and heavy tails in stock return time series.

Suggested Citation

  • Hongtao Guo & Miranda S. Lam & Guojun Wu & Zhijie Xiao, 2013. "Risk Analysis Using Regression Quantiles: Evidence from International Equity Markets," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 7(2), pages 1-15.
    • Handle: RePEc:ibf:ijbfre:v:7:y:2013:i:2:p:1-15
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Value at Risk; International Equities; Quantile Regression; Risk Analysis;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General

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