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Disaggregating the correlation under bearish and bullish markets: A Quantile-quantile approach

Author

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  • Syed jawad hussain Shahzad

    (Montpellier Business School, Montpellier, France)

  • Saba Ameer

    (COMSATS Institute of Information and Technology, Virtual Campus Islamabad, Pakistan)

  • Muhammad Shahbaz

    (Montpellier Business School, Montpellier, France)

Abstract

We disaggregate the correlation between S&P 500, U.S. bond, oil, commodities and gold returns under bearish and bullish market states. In doing so, we apply a novel quantile-on-quantile (QQ) approach, on the monthly data from January 1982 to December 2015, to construct correlation estimates between the quantile of S&P 500 and quantile of other markets. This approach captures the dependence between the distributions of U.S. stock return and other markets and uncovers two nuance features. First, higher dependence of U.S. bond and Gold with U.S. stock market returns is found when the U.S. stock market is bullish (i.e. at upper U.S. return quantiles). Second, higher dependence of U.S. commodities and oil with U.S. stock market returns exists when the U.S. stock market is bearish (i.e. at lower U.S. return quantiles). Finally, the relationship between U.S equities and other investment markets is asymmetric.

Suggested Citation

  • Syed jawad hussain Shahzad & Saba Ameer & Muhammad Shahbaz, 2016. "Disaggregating the correlation under bearish and bullish markets: A Quantile-quantile approach," Economics Bulletin, AccessEcon, vol. 36(4), pages 2465-2473.
    • Handle: RePEc:ebl:ecbull:eb-16-00683
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    Cited by:

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    2. Hussain Shahzad, Syed Jawad & Raza, Naveed & Shahbaz, Muhammad & Ali, Azwadi, 2017. "Dependence of stock markets with gold and bonds under bullish and bearish market states," Resources Policy, Elsevier, vol. 52(C), pages 308-319.
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    More about this item

    Keywords

    Stock markets; commodities; quantile regression; risk management;
    All these keywords.

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets

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