IDEAS home Printed from https://ideas.repec.org/a/taf/quantf/v14y2014i9p1597-1618.html

Commodity markets through the business cycle

Author

Listed:
  • Julien Chevallier
  • Mathieu Gatumel
  • Florian Ielpo

Abstract

From 2008 to 2011, commodity markets experienced growing attention from the banking industry for various reasons: the summer 2008 oil price swing, the price surge in an ounce of gold, or sharp variations in agricultural prices. As a consequence, can we hypothesize the existence of a global connection between commodities and economic cycles? If these recent events suggest that commodity markets are strongly related to the business cycle, this evidence goes nevertheless against the widespread intuition that commodity markets are a strong source of diversification in a standard cash-bond-equity portfolio. Based on a data-set from 1990 to present, this paper investigates this issue by (i) looking at the reaction of commodity markets to economic news, and (ii) using a Markov regime-switching model to analyse economic regimes and commodity markets as an asset class.

Suggested Citation

  • Julien Chevallier & Mathieu Gatumel & Florian Ielpo, 2014. "Commodity markets through the business cycle," Quantitative Finance, Taylor & Francis Journals, vol. 14(9), pages 1597-1618, September.
    • Handle: RePEc:taf:quantf:v:14:y:2014:i:9:p:1597-1618
    DOI: 10.1080/14697688.2013.842651
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/14697688.2013.842651
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/14697688.2013.842651?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or

    for a different version of it.

    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. Aneeta Elsa Simon & Manu K.S., 2023. "Does Sentiments Impact the Returns of Commodity Derivatives? An Evidence from Multi-commodity Exchange India," Vision, , vol. 27(1), pages 79-92, February.
    2. Gatfaoui, Hayette, 2019. "Diversifying portfolios of U.S. stocks with crude oil and natural gas: A regime-dependent optimization with several risk measures," Energy Economics, Elsevier, vol. 80(C), pages 132-152.
    3. Wei Yang & Ai Han & Yongmiao Hong & Shouyang Wang, 2016. "Analysis of crisis impact on crude oil prices: a new approach with interval time series modelling," Quantitative Finance, Taylor & Francis Journals, vol. 16(12), pages 1917-1928, December.
    4. Bayaa, Yasmeen & Qadan, Mahmoud, 2024. "The shape of the Treasury yield curve and commodity prices," International Review of Financial Analysis, Elsevier, vol. 94(C).
    5. Charalampos Stasinakis & Georgios Sermpinis & Ioannis Psaradellis & Thanos Verousis, 2016. "Krill-Herd Support Vector Regression and heterogeneous autoregressive leverage: evidence from forecasting and trading commodities," Quantitative Finance, Taylor & Francis Journals, vol. 16(12), pages 1901-1915, December.
    6. Mahmoud Qadan & Gil Cohen, 2024. "Uncertainty about interest rates and crude oil prices," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-14, December.
    7. Lof, Matthijs & Nyberg, Henri, 2017. "Noncausality and the commodity currency hypothesis," Energy Economics, Elsevier, vol. 65(C), pages 424-433.
    8. Zhang, Yongmin & Ding, Shusheng, 2021. "Liquidity effects on price and return co-movements in commodity futures markets," International Review of Financial Analysis, Elsevier, vol. 76(C).
    9. Chevallier, Julien & Ielpo, Florian, 2017. "Investigating the leverage effect in commodity markets with a recursive estimation approach," Research in International Business and Finance, Elsevier, vol. 39(PB), pages 763-778.

    More about this item

    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:taf:quantf:v:14:y:2014:i:9:p:1597-1618. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RQUF20 .

    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.