An Evaluation of the Skewness Model on 22 Commodities Futures

Skewness is one of the less-known but practical measures from statistics that can be used in trading. It is defined as a measure of the asymmetry of the probability distribution of a random variable around its mean. Financial mathematics and most quantitative models assume some kind of symmetric distribution of random variables, such as near-normal distribution, which would have zero skewness. From the perspective of traders, it is always interesting to look for extreme values of skewness which attributed to non-expected outcomes. When you bet a reasonable amount of capital on non-quite-probable but good-calculated events, it is possible to catch a chunk of those tails risks while also possible to hedge harmful exposure (if you have some of the opposite exposure). But is using skewness as a factor in a systematic strategy really profitable?The goal of this analysis is to explore the commodity skewness trading strategy and perform the battery of robustness tests to see how sensitivity analysis changes overall results regarding performance, volatility, and Sharpe ratios.We have covered the topic of robustness testing topic extensively; we also mentioned the lottery effect and possible asymmetric payoffs that make skewness as a predictor an especially lucrative topic for trading strategies. We encourage you to look at similar of our past posts on our Blog