Quantopian & Quantpedia Trading Strategy Series: Cross-Sectional Equity Mean Reversion Thursday, 29 December, 2016
Quantopian & Quantpedia Trading Strategy Series continues ... Now with a 4th article, again written by Matthew Lee, focused on Cross-Sectional Equity Mean Reversion (Strategy #13):
Cross-sectional mean reversion in stocks (strong tendency of stocks with strong gains/losses to reverse in a short-term time frame - up to one month) is a well-known market observation and the main reason why so many academic researchers generally use a 2-12 momentum measurement (returns over the past 12 months, excluding the previous one) when examining momentum anomaly. Many academic papers examined this effect, the most notable are papers by Jagadesh, and Bruce Lehmann (see "Other papers" section on Quantpedia subpage for this reversal strategy for additional academic research papers). The most academics speculate that the fundamental reasons for the anomaly are market-microstructure frictions (bid-ask bounce) or investors' cognitive biases - overreaction to past information and a correction of that reaction after a short time horizon.
But is this simple equity strategy still profitable?
Matthew Lee from Quantopian performed an independed analysis during an out of sample period from 12-01-2011 to 12-01-2016. Overall, the performance of simple short-term equity reversal strategy is below the market. But, it's to be noted that this strategy is long/short compared to just long-only equity benchmark (which is the SPY). So if we want to compare total performance of that strategy, we should compare long only reversal of the "loser stocks decile". Long/short equity reversal strategy has a Sharpe ratio 0.84 and Beta of 0.15. Sharpe ratio of long/short version is comparable to market portfolio and a low correlation of equity reversal strategy makes it a possible addon to investment portfolio.
However ... Reversal strategy is very active (weekly, bi-weekly rebalancing) which means high transaction costs and slippage. So really high caution should be paid in a real-world implementation and steps which tries to limit strategy's turnover should be taken.
The final OOS equity curve:
Thanks for the analysis Matthew!
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