The existence of short term return reversals for equities has captured the attention of many financial researchers.
In 1990, Bruce Lehmann found that over the period of 1962 - 1986 stocks in the highest returns of the prior week typically had negative returns in the following week. In his study, he found that contrarian strategies (picking past losers and winners) generated abnormal returns of over 2% each month. In the same year, Jegadeesh found that short-term reversals exist over the 1 month horizon. These 1 month short-term reversals are why many academic researchers generally use a 2-12 momentum measurement (returns over the past 12 months, excluding the previous one) when examining momentum.
Researchers have put forth a number of theories to try and explain short-term reversals. Lehmann attributed the phenomemon to cognitive bias leading to market inefficiency while another series of studies cited market-microstructure frictions (bid-ask bounce) as the cause.
This notebook serves to analyze the findings on cross-sectional mean reversion strategies covered in various papers, during an out of sample period from 12-01-2011 to 12-01-2016. The study is done in two parts.
Part 1 specifically covers a review of the general contrarian strategies highlighted by Lehmann and Jegadeesh. Part 2 will cover more advanced and recently discovered contrarian strategies given to us by Quantpedia.
Our universe is defined as stocks in the Q1500 - I use the Q1500 as a proxy due to the liquidity and high market cap of most stocks in the universe.
In my notebook, I find that utilizing a decile grouping based on a returns lookback of 13 days is correlated with 13 day average returns, with the lowest/highest decile performing slightly over/under our SPY and Q1500 market benchmark with a 1.6% average spread per quarter. The actual implementation of short term reversal strategies suffers due to the high trading activity required to rebalance the portfolio. Due to this, the findings in many research papers fail to reflect the true profitability of short-term reversal strategies.
And while the performance is below the market, it's to be noted that this strategy is long/short compared to just long-only (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". With that being said, this long/short strategy has a sharpe of .84 and relatively low vol.
This two part series serves as a glance into the performance of cross-sectional mean reversion strategies in recent years. I encourage readers interested in these strategies to expand my analysis on the data generated in this notebook and experiment with optimizing portfolio construction for these strategies. Historically, most short term reversal strategies explored by researchers fail to reproduce the same performance found in studies during live trading, due to the substantial volume of stocks traded. More investigation in constructing a strategy to reduce portfolio turnover could substantially enhance the performance of various contrarian strategies.
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