英文标题：
《Commodity futures and market efficiency》
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作者：
Ladislav Kristoufek and Miloslav Vosvrda
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最新提交年份：
2013
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英文摘要：
  We analyze the market efficiency of 25 commodity futures across various groups -- metals, energies, softs, grains and other agricultural commodities. To do so, we utilize recently proposed Efficiency Index to find that the most efficient of all the analyzed commodities is heating oil, closely followed by WTI crude oil, cotton, wheat and coffee. On the other end of the ranking, we detect live cattle and feeder cattle. The efficiency is also found to be characteristic for specific groups of commodities -- energy commodities being the most efficient and the other agricultural commodities (formed mainly of livestock) the least efficient groups. We also discuss contributions of the long-term memory, fractal dimension and approximate entropy to the total inefficiency. Last but not least, we come across the nonstandard relationship between the fractal dimension and Hurst exponent. For the analyzed dataset, the relationship between these two is positive meaning that local persistence (trending) is connected to global anti-persistence. We attribute this to specifics of commodity futures which might be predictable in a short term and locally but in a long term, they return to their fundamental price.
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中文摘要：
我们分析了金属、能源、软商品、谷物和其他农产品等不同类别的25种商品期货的市场效率。为此，我们利用最近提出的效率指数发现，所有分析商品中效率最高的是取暖油，紧随其后的是WTI原油、棉花、小麦和咖啡。在排名的另一端，我们检测活牛和饲养牛。效率也被发现是特定商品群体的特征——能源商品是效率最高的，而其他农业商品（主要由牲畜构成）是效率最低的群体。我们还讨论了长期记忆、分形维数和近似熵对总效率的贡献。最后但并非最不重要的是，我们遇到了分形维数和赫斯特指数之间的非标准关系。对于分析的数据集，这两者之间的关系是积极的，这意味着局部持久性（趋势）与全局反持久性相关联。我们将其归因于大宗商品期货的具体情况，这些期货可能在短期和本地都是可预测的，但从长期来看，它们会回到基本价格。
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Statistical Finance        统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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