软商品市场是否受到万圣节效应的影响?

M. Krawiec, A. Górska
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引用次数: 0

摘要

在过去的三十年里,商品市场,包括软商品市场,已经变得越来越像金融市场。因此,商品价格可能表现出与在不同金融资产的行为中观察到的相似的模式或异常。它们的存在可能使人们对商品市场的竞争力和效率产生怀疑。这促使我们进行本文提出的研究,旨在研究1999年至2020年万圣节对基本软商品(可可、咖啡、棉花、冷冻浓缩橙汁、橡胶和糖)市场的影响。如此长的时间跨度确保了结果的可信度。除了进行双样本t检验和秩和Wilcoxon检验外,我们还研究了自回归条件异方差(ARCH)效应。它在我们的数据中的存在使我们能够估计广义自回归条件异方差[GARCH(1,1)]模型,其中假人代表万圣节效应。我们还研究了一月效应对万圣节效应的影响。结果显示,棉花的万圣节效应显著(受一月效应驱动),糖的万圣节效应显著相反。它给市场上的主要参与者带来了有益的启示。他们可以运用交易策略产生满意的利润或提供对冲软商品价格的不利变化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
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