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Are soft commodities markets affected by the Halloween effect?

Author

Listed:
  • Monika Krawiec
  • Anna Górska

    (Institute of Economics and Finance, Warsaw University of Life Sciences, Warsaw, Poland)

Abstract

Within the last three decades commodity markets, including soft commodities markets, have become more and more like financial markets. As a result, prices of commodities may exhibit similar patterns or anomalies as those observed in the behaviour of different financial assets. Their existence may cast doubts on the competitiveness and efficiency of commodity markets. It motivates us to conduct the research presented in this paper, aimed at examining the Halloween effect in the markets of basic soft commodities (cocoa, coffee, cotton, frozen concentrated orange juice, rubber and sugar) from 1999 to 2020. This long-time span ensures the credibility of results. Apart from performing the two-sample t-test and the rank-sum Wilcoxon test, we additionally investigate the autoregressive conditional heteroskedasticity (ARCH) effect. Its presence in our data allows us to estimate generalised autoregressive conditional heteroskedasticity [GARCH (1, 1)] models with dummies representing the Halloween effect. We also investigate the impact of the January effect on the Halloween effect. Results reveal the significant Halloween effect for cotton (driven by the January effect) and the significant reverse Halloween effect for sugar. It brings implications useful to the main actors in the market. They may apply trading strategies generating satisfactory profits or providing hedging against unfavourable changes in soft commodities prices.

Suggested Citation

  • Monika Krawiec & Anna Górska, 2021. "Are soft commodities markets affected by the Halloween effect?," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 67(12), pages 491-499.
    • Handle: RePEc:caa:jnlage:v:67:y:2021:i:12:id:216-2021-agricecon
    DOI: 10.17221/216/2021-AGRICECON
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    References listed on IDEAS

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    1. Dmitry Burakov & Max Freidin & Yuriy Solovyev, 2018. "The Halloween Effect on Energy Markets: An Empirical Study," International Journal of Energy Economics and Policy, Econjournals, vol. 8(2), pages 121-126.
    2. Sabuhoro, Jean Bosco & Larue, Bruno, 1997. "The market efficiency hypothesis: The case of coffee and cocoa futures," Agricultural Economics, Blackwell, vol. 16(3), pages 171-184, August.
    3. Cherry Y. Zhang & Ben Jacobsen, 2013. "Are Monthly Seasonals Real? A Three Century Perspective," Review of Finance, European Finance Association, vol. 17(5), pages 1743-1785.
    4. Haggard, K. Stephen & Witte, H. Douglas, 2010. "The Halloween effect: Trick or treat?," International Review of Financial Analysis, Elsevier, vol. 19(5), pages 379-387, December.
    5. Kenourgios, Dimitris & Samios, Yiannis, 2021. "Halloween effect and active fund management," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 534-544.
    6. Guo, Biao & Luo, Xingguo & Zhang, Ziding, 2014. "Sell in May and Go Away: Evidence from China," Finance Research Letters, Elsevier, vol. 11(4), pages 362-368.
    7. Jean Bosco Sabuhoro & Bruno Larue, 1997. "The market efficiency hypothesis: the case of coffee and cocoa futures," Agricultural Economics, International Association of Agricultural Economists, vol. 16(3), pages 171-184, August.
    8. 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.
    9. Gordon, J. Douglas, 1985. "The Distribution of Daily Changes in Commodity Futures Prices," Technical Bulletins 156817, United States Department of Agriculture, Economic Research Service.
    10. Sven Bouman & Ben Jacobsen, 2002. "The Halloween Indicator, "Sell in May and Go Away": Another Puzzle," American Economic Review, American Economic Association, vol. 92(5), pages 1618-1635, December.
    11. Peter ARENDAS, 2017. "The Halloween effect on the agricultural commodities markets," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 63(10), pages 441-448.
    12. Maria Caporale, Guglielmo & Zakirova, Valentina, 2017. "Calendar anomalies in the Russian stock market," Russian Journal of Economics, Elsevier, vol. 3(1), pages 101-108.
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