Are soft commodities markets affected by the Halloween effect?

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.

AN ANOMALY WITHIN AN ANOMALY: THE HALLOWEEN EFFECT IN THE LONG-TERM REVERSAL ANOMALY

In this paper, we investigate the presence of the Halloween effect in the long-term reversal anomaly in the US. When we examine the cross-sectional returns of winner-minus-loser portfolios formed on prior returns over the time period of 1931-2021, we find evidence of stronger returns during winter months versus summer months. In particular, the effect appears to be driven by very strong winter-summer seasonality in the portfolio of small-capitalisation losers, and lack of Halloween effect in the portfolio of large-capitalisation winners. Our finding is robust to alternative measures of long-term reversal, differing sub-periods, the inclusion of the January effect and outlier considerations, as well as within small and large-sized companies.

The Month-of-the-Year Effect in the European, American, Australian and Asian Markets

This paper examines the existence of the month-of-the-year effects in four different continents, namely Europe, Asia, America, and Oceania. Nine indexes were analyzed in order to verify differences between monthly returns from January 1990 to December 2013, followed by an examination of the January effect, Halloween effect, and the October effect, testing for statistical significance using an OLS linear regression in order to verify whether those effects offer consistent opportunities for investors. Investors with globally diversified portfolios benefit from the Halloween effect, with a 1.2% average monthly excess return in winter and spring, while the pre-dotcom-bubble period had a better performance than the post-dotcom-bubble period. In the global post-dotcom-bubble period, there is statistical evidence for 1.60% and 1% lower average monthly returns in January (the January effect) and in months other than October (the October effect), respectively, contradicting the literature. The dotcom bubble seems to be responsible for the January effect differing from what might otherwise have been expected in the later period. There is no consistent and clear impact on continental incidence. The Halloween effect is revealed to be a fruitful strategy in the FTSE, DAX, Dow Jones, BOVESPA, and N225 indexes taken one-by-one. The January effect excess average return was only statistically significative for the pre-dotcom-bubble period for globally diversified portfolios. This paper contributes to a wider global and comparable view upon month-of-the-year effect.

Trick or treat? The Halloween effect in stock markets revisited

PurposeThe subject of this paper is seasonal variation in the return on stocks. The phenomenon we analyze here is known as the “Halloween effect” or the trading strategy “sell in May and go away.” The authors test the hypothesis that stock markets tend to return considerably less in the six months beginning in May than in the other half of the year. This effect has shown persistency over time and is seemingly large enough to be a candidate for economic significance.Design/methodology/approachThe authors analyze monthly data from 13 countries for the period 1958–2019, using the Kruskal–Wallis test, t-test and a boot-strap based estimator. In addition, we look a sub-periods for a larger group of countries and include data on both stock returns and interest rates.FindingsThe authors find a strong seasonal effect in a large majority of the markets, with the period from November to April seeing higher returns than the other six months of the year. This result also holds for a larger sample of countries based on data from a shorter period. The effect is found to be economically significant in most countries in the sample. The authors examine one potential explanation for seasonal variation in stock returns, i.e. seasonal affective disorder (SAD). The authors find some, albeit weak, support for this hypothesis.Originality/valueThis paper uses a rich dataset that has not been used for this purpose before and robust tests of statistical and economic significance to shed light on an important aspect of global financial markets.