IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-02013740.html

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

Author

Listed:
  • Syed Jawad Hussain Shahzad

    (MRM - Montpellier Research in Management - UPVM - Université Paul-Valéry - Montpellier 3 - UPVD - Université de Perpignan Via Domitia - Groupe Sup de Co Montpellier (GSCM) - Montpellier Business School - UM - Université de Montpellier)

  • Saba Ameer
  • Muhammad Shahbaz

    (MRM - Montpellier Research in Management - UPVM - Université Paul-Valéry - Montpellier 3 - UPVD - Université de Perpignan Via Domitia - Groupe Sup de Co Montpellier (GSCM) - Montpellier Business School - UM - Université de Montpellier)

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," Post-Print hal-02013740, HAL.
    • Handle: RePEc:hal:journl:hal-02013740
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sui, Meng & Rengifo, Erick W. & Court, Eduardo, 2021. "Gold, inflation and exchange rate in dollarized economies – A comparative study of Turkey, Peru and the United States," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 82-99.
    2. Naeem, Muhammad Abubakr & Hasan, Mudassar & Arif, Muhammad & Balli, Faruk & Shahzad, Syed Jawad Hussain, 2020. "Time and frequency domain quantile coherence of emerging stock markets with gold and oil prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 553(C).
    3. 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.
    4. Maghyereh, Aktham & Abdoh, Hussein, 2020. "The tail dependence structure between investor sentiment and commodity markets," Resources Policy, Elsevier, vol. 68(C).
    5. Mensi, Walid & Gök, Remzi & Gemici, Eray & Vo, Xuan Vinh & Kang, Sang Hoon, 2025. "Extreme dependence, connectedness, and causality between US sector stocks and oil shocks," International Review of Economics & Finance, Elsevier, vol. 98(C).
    6. Hanif, Waqas & El Khoury, Rim & Hadhri, Sinda, 2025. "Is connectedness between commodity volatility indices and G-7 stock market returns the same across return quantiles?," Journal of Multinational Financial Management, Elsevier, vol. 79(C).
    7. Donald Lien & Zijun Wang, 2019. "Quantile information share," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(1), pages 38-55, January.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hal:journl:hal-02013740. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.