Testing and Trading Mean-Reverting Price Extremes
Summary
The document outlines a basic approach to trading markets believed to revert toward a central level. It recommends first testing whether the price series is mean reverting, with the Augmented Dickey-Fuller test offered as one possible check. If the assumption holds, detrend the data, identify unusually high or low prices relative to their historical range, and enter short or long positions with exits near the mean or halfway back from the extreme.
The answer suggests using several years of history to define extremes around the outer percentiles and notes that detrending can remove long-term equity trends or futures carry effects. It offers practitioner experience mainly from mean-reverting spreads, rather than broad evidence of profitability. Prices can break beyond historical limits and produce large drawdowns; a momentum filter may help manage this risk but is imperfect. The discussion also cautions that RSI is not itself evidence of mean reversion.
Key ideas
- Test for mean reversion before building a strategy around it.
- Detrend price data to reduce long-term trend or futures carry effects.
- Enter positions at historically extreme levels and define exits near the mean or a partial reversion point.
- Price moves beyond historical limits can cause substantial drawdowns, and a momentum filter may only partly help.
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Full text
# Mean reverting strategies # Mean reverting strategies I would like to take advantage of a volatile market by selling highs and buying lows. As we all know the RSI indicator is very bad and I want to create a superior strategy for this purpose. I have tried to model the price using a time varying ARMA process, with no success for now. Any other ideas? ## Answer by pteetor (score 8, accepted) https://quant.stackexchange.com/a/155 Your question's title suggests the market prices are mean reverting. I strongly suggest verifying that assumption via one of the usual tests, such as the Augmented Dickey-Fuller test (implemented in the tseries package of R by the adf.test function, and in other R packages, too). If the market is truly mean reverting, a possible strategy is - Detrend the data. - Monitor the market for an extreme high or extreme low, based on its historical range. - Buy or sell-short the market at those extremes. - Cover at a logical point: at the mean or at the half-way point, for example. - Repeat. Detrending is useful to eliminate the long-term trend (in stocks) or eliminate the effects of carry (in futures). "Extreme highs" and "extreme lows" must really be extreme: I look for prices in the upper 90 to 95th percentile or lower 10th to 5th percentile, based on a few years of history. Buying or selling-short at the extremes is fine ... unless the market decides to exceed its historical limits, in which case you'll experience drawdown, potentially large. I use a momentum filter and that helps but it's not perfect. My experience is mostly in trading mean-reverting spreads. Your mileage may vary. (PS - I found no connection between the RSI indicator and mean reversion. I don't use it.)
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This summary was written by Stratmill's research agent from the original; it is not a copy of the source.