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Commodity Pricing through Crises

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  • Giulio Cifarelli

Abstract

The pricing of six highly liquid futures commodity contracts is investigated using a Markov switching procedure. The data set spans an exceptionally turbulent period, characterized by a complex interplay of economic/financial and political shocks. Markov switching analysis exploits time series nonlinearity to identify the nature and the timing of the implicit changes of regime. Building on a HAM framework, we use the time varying parameterization of the transition probability estimates to link these shifts to exogenous variables. We provide in this way additional information on the co-movement of the time series and on their regime shifts, eventually conducive to herding pricing behaviour. The WTI oil futures price and DJIA stock index are used as proxies for global shocks as they turn out to be the main common drivers of the changes in regime of most futures commodity prices. Â

Suggested Citation

  • Giulio Cifarelli, 2025. "Commodity Pricing through Crises," International Journal of Finance & Banking Studies, Center for the Strategic Studies in Business and Finance, vol. 14(3), pages 31-43, July.
  • Handle: RePEc:rbs:ijfbss:v:14:y:2025:i:3:id:4057
    DOI: 10.20525/ijfbs.v14i3.4057
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    1. Brock, William A. & Hommes, Cars H., 1998. "Heterogeneous beliefs and routes to chaos in a simple asset pricing model," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1235-1274, August.
    2. 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.
    3. Omar, Ayman M.A. & Wisniewski, Tomasz Piotr & Nolte, Sandra, 2017. "Diversifying away the risk of war and cross-border political crisis," Energy Economics, Elsevier, vol. 64(C), pages 494-510.
    4. repec:bla:ecorec:v:0:y:1986:i:0:p:24-38 is not listed on IDEAS
    5. Libing Fang & Baizhu Chen & Honghai Yu & Yichuo Qian, 2018. "The importance of global economic policy uncertainty in predicting gold futures market volatility: A GARCH‐MIDAS approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(3), pages 413-422, March.
    6. Feng Ma & Xinjie Lu & Lu Wang & Julien Chevallier, 2021. "Global economic policy uncertainty and gold futures market volatility: Evidence from Markov regime‐switching GARCH‐MIDAS models," Post-Print halshs-04250272, HAL.
    7. William A. Brock & Cars H. Hommes, 2001. "A Rational Route to Randomness," Chapters, in: W. D. Dechert (ed.), Growth Theory, Nonlinear Dynamics and Economic Modelling, chapter 16, pages 402-438, Edward Elgar Publishing.
    8. Harding, Don & Pagan, Adrian, 2006. "Synchronization of cycles," Journal of Econometrics, Elsevier, vol. 132(1), pages 59-79, May.
    9. Bekaert, Geert & Harvey, Campbell R, 1995. "Time-Varying World Market Integration," Journal of Finance, American Finance Association, vol. 50(2), pages 403-444, June.
    10. Engel, Charles & Hakkio, Craig S, 1996. "The Distribution of Exchange Rates in the EMS," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 1(1), pages 55-67, January.
    11. Daniel Santabárbara, 2017. "The oil market: recent developments and outlook," Economic Bulletin, Banco de España, issue SEP.
    12. Mehmet Balcilar & Riza Demirer, 2015. "Effect of Global Shocks and Volatility on Herd Behavior in an Emerging Market: Evidence from Borsa Istanbul," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 51(1), pages 140-159, January.
    13. Filardo, Andrew J. & Gordon, Stephen F., 1998. "Business cycle durations," Journal of Econometrics, Elsevier, vol. 85(1), pages 99-123, July.
    14. Shleifer, Andrei & Vishny, Robert W, 1997. "The Limits of Arbitrage," Journal of Finance, American Finance Association, vol. 52(1), pages 35-55, March.
    15. Balcilar, Mehmet & Demirer, Rıza & Hammoudeh, Shawkat, 2014. "What drives herding in oil-rich, developing stock markets? Relative roles of own volatility and global factors," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 418-440.
    16. Marco Bazzi & Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2017. "Time-Varying Transition Probabilities for Markov Regime Switching Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(3), pages 458-478, May.
    17. Patricia Alvarez‐Plata & Mechthild Schrooten, 2006. "The Argentinean Currency Crisis: A Markov‐Switching Model Estimation," The Developing Economies, Institute of Developing Economies, vol. 44(1), pages 79-91, March.
    18. Feng Ma & Xinjie Lu & Lu Wang & Julien Chevallier, 2021. "Global economic policy uncertainty and gold futures market volatility: Evidence from Markov regime‐switching GARCH‐MIDAS models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(6), pages 1070-1085, September.
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