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Positive skew in invested assets as proxy for long term outperformance / increasing skewness of momentum trading strategy.

Dear all,

the following presents a model portfolio where the equity selection is done by picking the stocks with the highest positive skew.

Thesis: Equities with positive skew will outperform the market over long time periods and help to shift negatively skewed trading startegies towards more positive skews.

The concept of skew is well know amongst traders and investors, since it can be applied to both trading strategies and individual assets one might choose to invest in.
In this short research, it was explored if it is a viable strategy to hold an assortment of the equities with the most positive skew. The rational behind this thesis is that in theory, statistically speaking, this should reduce the impact of "negative surprises" and increase the impact of "positive surprises", leading to less downside volatility and to the possibility of outperforming a mostly negatively skewed market.
For this, in the first part the constituents of the top 500 US stocks by market cap where sorted based upon skew. Every month, the entire capital was invested into the top 30 companies with the biggest positive skew. This was only done when the SPY happened to be in an uptrend.
If the SPY was in a downtrend, the entire portfolio was liquidated at once.
While the results are only mediocre at best, the data still shows that skewness can indeed provide a certain amount of edge in the market.

In the second part of this research, it was evaluated if adding a skewness criterion to an existing momentum trading strategy could help increase the skewness of the strategy towards 0. It was found that for the particular ruleset employed, considering the skewness of the individual equities did indeed increase the skewness of the strategy by about 1/3 and reduced the kurtosis towards 3.

Best regards, Kristof

2 responses

Good job, Kristof. Very neat and clean code. I think the negative skewness could be used in lower timeframe to detect early stock drop.

Thank you! I was thinking along the same lines when doing the research but I'm not sure if the skewness would be to slow to be used that way. Anyhow, it might be worth trying out a skew based SL. I'll have to code it but maybe the 1st derivative of the skewness versus time could signal an increasing likelyhood for a major stock drop when it crosses the x-axis from top to bottom, thus signaling an inflection of the skewness.