Skewness<\/a> 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<\/a> of random variables, such as near-normal distribution<\/a>, 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? <\/strong><\/p>\n\n\n\n