Is the Halloween Effect Present on the Markets for Agricultural Commodities?
No 2/2018, June
Burakov, D. and Freidin, M. (2018) “Is the Halloween Effect Present on the Markets for Agricultural Commodities?", AGRIS on-line Papers in Economics and Informatics, Vol. 10, No. 2, pp. 23-32. ISSN 1804-1930. DOI 10.7160/aol.2018.100203.
Seasonal anomalies play an important role in the global economic system. One of the most frequently empirically observed anomalies is the Halloween effect. Halloween effect describes the anomaly on the financial markets, which is that the returns of different assets in the summer period are generally lower than the returns in the winter period. This study tests the Halloween effect on the agricultural commodities’ markets over the period from 1980 to 2016. The sample includes price series of 27 major agricultural commodities. The data show that 20 out of the 27 commodities recorded a higher average winter period than summer period returns and in 15 cases, the differences are statistically significant. The data also show that out of the 7 commodities with higher summer period returns (the “reverse Halloween effect”) only in cases of poultry and tea the differences are of statistically significant nature.
Halloween effect, financial market, agriculture, commodity, seasonal anomaly.
- Andrade, S. C., Chhaochharia, V. and Fuerst, M. E. (2013) "“Sell in May and Go Away” Just Won’t Go Away”, Financial Analysts Journal, Vol. 69, No. 4, pp. 94-105. ISSN 0015-198X. DOI 10.2469/faj.v69.n4.4.
- Arendas, P. (2015) “The soybean market price cycle and its application on investment strategies”,Nová Ekonomika, Vol. 8, No. 3, pp. 31–38.
- Arendas, P. (2017) “The Halloween effect on the agricultural commodities markets”, AgriculturalEconomics, Vol. 63, No. 10, pp. 441-448. ISSN 0139-570X. DOI 10.17221/45/2016-AGRICECON.
- Borowski, K. (2015) “Analysis of selected seasonality effects in market of barley, canola, rough rice,soybean oil and soybean meal future contracts”, Journal of Economics and Management, Vol. 21,pp. 73-89. ISSN 1732-1948.
- Bouman, S. and Jacobsen B. (2002) “The Halloween indicator, “sell in May and go away”:Another puzzle”, American Economic Review, Vol. 92, No. 5, pp. 1618-1635. ISSN 0002-8282. DOI 10.1257/000282802762024683.
- Burakov, D. (2017) “Oil Prices, Exchange Rate and Prices for Agricultural Commodities: EmpiricalEvidence from Russia”, AGRIS On-line Papers in Economics and Informatics, Vol. 8, No. 2,pp. 17-31. ISSN 1804-1930. DOI 10.7160/aol.2016.080203.
- Cao, M. and Wei, J. (2005) “Stock market returns: A note on temperature anomaly”, Journalof Banking & Finance, Vol. 29, No. 6, pp. 1559-1573. ISSN 0378-4266. DOI 10.1016/j.jbankfin.2004.06.028.
- Čermák, M., Malec, K. and Maitah, M. (2017) “Price Volatility Modelling – Wheat: GARCHModel Application", AGRIS on-line Papers in Economics and Informatics, Vol. 9, No. 4, pp. 15-24.ISSN 1804-1930. DOI 10.7160/aol.2017.090402.
- Etienne, X. L., Irwin, S. H. and Garcia, P. (2014) “Bubbles in food commodity markets: Four decadesof evidence”, Journal of International Money and Finance, Vol. 42, pp. 129-155. ISSN 0261-5606. DOI 10.1016/j.jimonfin.2013.08.008.
- Fama, E. (1965) “Random walks in stock market prices”, Financial Analysts Journal, Vol. 51, No. 1,pp. 55-59. ISSN 0015-198X. DOI 10.2469/faj.v51.n1.1861.
- Haggard, K. S., Jones, J. S. and Witte, H. D. (2015) “Black cats or black swans? Outliers, seasonalityin return distribution properties, and the Halloween effect”, Managerial Finance, Vol. 41, No. 7,pp. 642657. ISSN 0307-4358. DOI 10.1108/MF-07-2014-0190.
- Hamilton, J. D. and Wu, J. C. (2015) “Effects of index-fund investing on commodity futuresprices”, International Economic Review, Vol. 56, No. 1, pp. 187-205. ISSN 1468-2354. DOI 10.1111/iere.12099.
- Hochman, G., Rajagopal, D., Timilsina, G. and Zilberman, D. (2014) “Quantifying the causesof the global food commodity price crisis”, Biomass and Bioenergy, Vol. 68, pp. 106-114.ISSN 0961-9534. DOI 10.1016/j.biombioe.2014.06.012.
- Hong, H. and Yu, J. (2009) “Gone fishin’: seasonality in trading activity and asset prices”, Journalof Financial Markets, Vol. 12, No. 4, pp. 672-702. ISSN 1386-4181. DOI 10.1016/j.finmar.2009.06.001.
- Induruwage, D., Tilakaratne, C. D. and Rajapaksha, S.R.M.S.P. (2016) "Forecasting Black TeaAuction Prices by Capturing Common Seasonal Patterns“, Sri Lankan Journal of Applied Statistics,Vol. 16, No. 3, pp. 195-214. ISSN 1391-4987. DOI 10.4038/sljast ats.v16i3.7832.
- Jacobsen, B. and Marquering, W. (2008) “Is it the weather?”, Journal of Banking & Finance,Vol. 32, No. 4, pp. 526-540. ISSN 0378-4266. DOI 10.1016/j.jbankfin.2007.08.004.
- Jacobsen, B. and Nuttawat, V. (2009) “The Halloween effect in U.S. sectors”, Financial Review,Vol. 44, No. 3, pp. 437-459. ISSN 1540-6288. DOI 10.1111/j.1540-6288.2009.00224.x.
- Lakonishok, J. and Smidt, S. (1988) “Are seasonal anomalies real? A ninety-year perspective”,Review of Financial Studies, Vol. 1, No. 4, pp. 403-424. ISSN 1465-7368. DOI 10.1093/rfs/1.4.403.
- Lean, H. H. (2011) “The Halloween puzzle in selected Asian stock markets”, Journal of Economicsand Management, Vol. 5, pp. 216-225. ISSN 1732-1948.
- Liu, L. (2014) “Cross-correlations between crude oil and agricultural commodity markets”,Physica A: Statistical Mechanics and its Applications, Vol. 395, pp. 293-302. ISSN 0378-437. DOI 10.1016/j.physa.2013.10.021.
- Mensi, W., Hammoudeh, S., Nguyen, D. K. and Yoon, S.-M. (2014) “Dynamic spilloversamong major energy and cereal commodity prices”, Energy Economics, Vol. 43, pp. 225-243.ISSN 0140-9883. DOI 10.1016/j.eneco.2014.03.004.
- Milonas, N. T. (1991) “Measuring seasonalities in commodity markets and the half-month effect”,The Journal of Futures Markets, Vol. 11, No. 3, pp. 331-345. ISSN 1096-9934. DOI 10.1002/fut.3990110307.
- Ott, H. (2013) “Extent and possible causes of intrayear agricultural commodity pricevolatility”, Agricultural Economics, Vol. 45, No. 2-3, pp. 225-252. ISSN 1574-0862. DOI 10.1111/agec.12043.
- Razali, N. M. and Wah, Y. B. (2011) “Power comparison of Shapiro-Wilk, Kolmogorov-Smirnov,Lilliefors and Anderson-Darling tests”, Journal of Statistical Modeling and Analytics, Vol. 2,pp. 21-33. ISBN 978-967-363-157-5.
- Wang, Y., Wu, C. and Yang, L. (2014) “Oil price shocks and agricultural commodity prices”, EnergyEconomics, Vol. 44, pp. 22-35. ISSN 0140-9883. DOI 10.1016/j.eneco.2014.03.016.
- Zhang, C. Y. and Jacobsen, B. (2013) “Are monthly seasonals real? A three century perspective”Review of Finance, Vol.17, No. 5, pp. 1743-1785. ISSN 1573-692X. DOI 10.1093/rof/rfs035.