Evaluating trading strategies by the skewness of returns

Question

How to deal with skewness of returns when evaluating different trading strategies? More specifically, I'm back testing different strategies to be implemented as an automated black box strategy. While e.g. Sharpe ratio is a convenient and intuitively simple way to compare the strategies, but if the returns are not normally distributed it is vastly inadequate measure if one considers e.g. the use of leverage. This point is all the more important, when one considers e.g. many of the dynamic strategies like momentum that typically has a negative skew.

This leads me to my question: what is the most convenient way/is there an industry standard to comparing the skew of a trading strategy? Or does everybody simply use max drawdown to evaluate the possibility of the strategy blowing up and as a guideline when considering how much leverage to use?

Answer 1

You do not state whether your evaluations will result in potentially implementing multiple strategies or just one of them. This matters because if you are going to be combining multiple ones then you need some reasonable capital allocation assumptions, which increases complexity immensely.

Let's take the simpler case where you just want to choose one. Multiple metrics depend on the strategy size, of which unscalable mean/variance (Sharpe) ratios are just one. For example, size affects trading costs, market impact, and broker fees.

Thus, I suggest you choose a few candidate strategy sizes (in terms of capital) and do your analysis just on them. You can then properly add costs and market impact, and you do not need to worry about scaling.

I'll further add that if negative skew is important you may wish to look at downside deviation and Sortino ratios in addition to Sharpe and max drawdown.