Commodity futures and market efficiency

a r t i c l e i n f o We analyze the market efficiency of 25 commodity futures across various groups—metals, energies, soft commodities , grains and other agricultural commodities. To do so, we utilize the recently proposed Efficiency Index to find out that the most efficient among all of the analyzed commodities is heating oil, closely followed by WTI crude oil, cotton, wheat, and coffee. On the other end of the ranking scale we find live cattle and feeder cattle. The efficiency is also found to be characteristic for specific groups of commodities, with energy commodities being the most efficient and other agricultural commodities (composed mainly of livestock) the least efficient groups. We also discuss contributions of 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 the Hurst exponent. For the analyzed dataset, the relationship between these two variables is positive , meaning that local persistence (trending) is connected to global anti-persistence. We attribute this behavior to specifics of commodity futures: they may be predictable over a short term and locally, but over a long term they return to their fundamental prices. Efficient market hypothesis (EMH) has been a cornerstone of financial economics for decades and it has been brought to the forefront by the influential paper of Fama (1970), summarizing the empirical findings based on efficient market hypotheses by Fama (1965) and Samuelson (1965). Even though the actual definitions differ – the former study builds on a random walk definition and the latter on a mar-tingale definition – the qualitative consequences are the same: the efficiency of a market originates in the impossibility of systematic control of the market, usually in the form of above-average risk-adjusted returns. Fama (1991) later subdivided the efficiency hypothesis into three forms – weak, medium and strong – which vary by the different information sets taken into consideration, and all are based on inclusion of the information sets in market prices. The weak-form EMH says that all past price movements (and associated statistics) are already reflected in the market prices. Prediction of market movements based on historical time series (technical analysis) is thus not possible for this form. The medium-form EMH states that all publicly available information is already contained in the prices, while the strong-form EMH adds all (even privately) available information. The …