IDEAS home Printed from https://ideas.repec.org/a/eee/ecmode/v64y2017icp567-588.html
   My bibliography  Save this article

Assessing efficiency and investment opportunities in commodities: A time series and portfolio simulations approach

Author

Listed:
  • Jawadi, Fredj
  • Ftiti, Zied
  • Hdia, Mouna

Abstract

This paper investigates the informational efficiency hypothesis in the short and long term for four major commodity markets (oil, gas, electricity, and coal) from January 1997 to January 2016. Unlike previous studies, we provide a more concise comparative analysis by focusing on different classes of commodities for a large sample, including 5 developed and 3 emerging regions and covering 46 countries. We apply different parametric and non-parametric econometric tests. Our study provides two interesting findings. First, we show that commodity markets are informationally inefficient in the short term. Our portfolio simulations highlight that commodities might provide “good” investment opportunities, but those opportunities vary according to commodity class and regions. Second, we show that most commodity markets become informationally efficient in the long term, thereby reducing investors' interest for the duration. Thus, commodity markets might be used to hedge investor’s portfolios, particularly for speculators and chartists in the short term, while these investments might not be appealing in these markets in the long term.

Suggested Citation

  • Jawadi, Fredj & Ftiti, Zied & Hdia, Mouna, 2017. "Assessing efficiency and investment opportunities in commodities: A time series and portfolio simulations approach," Economic Modelling, Elsevier, vol. 64(C), pages 567-588.
  • Handle: RePEc:eee:ecmode:v:64:y:2017:i:c:p:567-588
    DOI: 10.1016/j.econmod.2017.04.021
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0264999316307143
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Hosseinzadeh, Ahmad & Smyth, Russell & Valadkhani, Abbas & Le, Viet, 2016. "Analyzing the efficiency performance of major Australian mining companies using bootstrap data envelopment analysis," Economic Modelling, Elsevier, vol. 57(C), pages 26-35.
    2. Hooi Hooi Lean & Russell Smyth, 2015. "Testing for weak-form efficiency of crude palm oil spot and future markets: new evidence from a GARCH unit root test with multiple structural breaks," Applied Economics, Taylor & Francis Journals, vol. 47(16), pages 1710-1721, April.
    3. Stefan Reitz & Frank Westerhoff, 2007. "Commodity price cycles and heterogeneous speculators: a STAR–GARCH model," Empirical Economics, Springer, vol. 33(2), pages 231-244, September.
    4. Kumar Narayan, Paresh & Narayan, Seema & Popp, Stephan, 2010. "Energy consumption at the state level: The unit root null hypothesis from Australia," Applied Energy, Elsevier, vol. 87(6), pages 1953-1962, June.
    5. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    6. Andrew W. Lo, A. Craig MacKinlay, 1988. "Stock Market Prices do not Follow Random Walks: Evidence from a Simple Specification Test," Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 41-66.
    7. Campbell, John Y & Shiller, Robert J, 1987. "Cointegration and Tests of Present Value Models," Journal of Political Economy, University of Chicago Press, vol. 95(5), pages 1062-1088, October.
    8. Maslyuk, Svetlana & Smyth, Russell, 2008. "Unit root properties of crude oil spot and futures prices," Energy Policy, Elsevier, vol. 36(7), pages 2591-2600, July.
    9. Grossman, Sanford J & Stiglitz, Joseph E, 1980. "On the Impossibility of Informationally Efficient Markets," American Economic Review, American Economic Association, vol. 70(3), pages 393-408, June.
    10. Shiller, Robert J, 1981. "Do Stock Prices Move Too Much to be Justified by Subsequent Changes in Dividends?," American Economic Review, American Economic Association, vol. 71(3), pages 421-436, June.
    11. Hsieh, David A, 1991. " Chaos and Nonlinear Dynamics: Application to Financial Markets," Journal of Finance, American Finance Association, vol. 46(5), pages 1839-1877, December.
    12. Beck, T.H.L., 2006. "Creating an efficient financial system : Challenges in a global economy," Other publications TiSEM fa839175-173f-4972-a0e7-e, Tilburg University, School of Economics and Management.
    13. Beck, Thorsten & Rahman, Md. Habibur, 2006. "Creating a more efficient financial system : challenges for Bangladesh," Policy Research Working Paper Series 3938, The World Bank.
    14. Fredj Jawadi & Georges Prat, 2012. "Arbitrage Costs and Nonlinear Stock Price Adjustment in the G7 Countries," Post-Print hal-01385801, HAL.
    15. Gao, Lin & Süss, Stephan, 2015. "Market sentiment in commodity futures returns," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 84-103.
    16. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    17. Kounetas, Kostas & Tsekouras, Kostas, 2010. "Are the Energy Efficiency Technologies efficient?," Economic Modelling, Elsevier, vol. 27(1), pages 274-283, January.
    18. Neil Kellard & Paul Newbold & Tony Rayner & Christine Ennew, 1999. "The relative efficiency of commodity futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 19(4), pages 413-432, June.
    19. Lee, Chien-Chiang & Lee, Jun-De, 2009. "Energy prices, multiple structural breaks, and efficient market hypothesis," Applied Energy, Elsevier, vol. 86(4), pages 466-479, April.
    20. Gebre-Mariam, Yohannes Kebede, 2011. "Testing for unit roots, causality, cointegration, and efficiency: The case of the northwest US natural gas market," Energy, Elsevier, vol. 36(5), pages 3489-3500.
    21. Ozdemir, Zeynel Abidin & Gokmenoglu, Korhan & Ekinci, Cagdas, 2013. "Persistence in crude oil spot and futures prices," Energy, Elsevier, vol. 59(C), pages 29-37.
    22. Presno, María José & Landajo, Manuel & Fernández, Paula, 2014. "Non-renewable resource prices: A robust evaluation from the stationarity perspective," Resource and Energy Economics, Elsevier, vol. 36(2), pages 394-416.
    23. Fredj Jawadi & Georges Prat, 2012. "Arbitrage costs and nonlinear adjustment in the G7 stock markets," Applied Economics, Taylor & Francis Journals, vol. 44(12), pages 1561-1582, April.
    24. H. Holly Wang & Bingfan Ke, 2005. "Efficiency tests of agricultural commodity futures markets in China," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 49(2), pages 125-141, June.
    25. Brock, William & Lakonishok, Josef & LeBaron, Blake, 1992. " Simple Technical Trading Rules and the Stochastic Properties of Stock Returns," Journal of Finance, American Finance Association, vol. 47(5), pages 1731-1764, December.
    26. Cochrane, John H, 1988. "How Big Is the Random Walk in GNP?," Journal of Political Economy, University of Chicago Press, vol. 96(5), pages 893-920, October.
    27. Fredj Jawadi & Nabila Jawadi & Abdoulkarim Idi Cheffou, 2015. "Are Islamic stock markets efficient? A time-series analysis," Applied Economics, Taylor & Francis Journals, vol. 47(16), pages 1686-1697, April.
    28. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. repec:eee:ecmode:v:70:y:2018:i:c:p:97-114 is not listed on IDEAS

    More about this item

    Keywords

    C10; G14; Informational efficiency; Commodity markets; Hedging; Portfolio simulations; Time series;

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

    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:eee:ecmode:v:64:y:2017:i:c:p:567-588. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/locate/inca/30411 .

    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.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.