Mean Reversion
Respecting the tendency of some securities prices to return to their long-term mean is an essential trading strategy.
While hype can inflate markets like hot air in a balloon, prices tend to return to Earth at a moment that’s notoriously difficult to forecast. Conversely, underpriced stocks often regain the value they’ve lost. These are reasons traders can put a little faith in the statistically backed mean-reversion strategy.
Still, the strategy works only for a handful of mean-reverting asset classes that oscillate around a historical average price. Many futures markets have recently begun moving beyond their average price, but even that trend presents an intriguing opportunity for mean-reversion traders.
How so? Well, mean reversion is simply the idea that a price or measure will revert to its long-term mean at some point if it’s not already there. If prices are far beyond their average, either above or below, they may be likely to snap back.
While mean reversion may not work on a longer timescale with all markets—equities that exhibit positive drift, for example—it can provide an effective strategy in interest rate, volatility and commodity markets.
Take 10-year interest rates, which were about 3% in 2018, that swiftly fell to 0.50% during the pandemic and have since climbed back to 2%. That’s near their mean price for this look-back window. The mean 10-year interest rate for this period is 1.84%, relating to a Small 10-Year U.S. Treasury Yield futures price of 18.40. That mean provides a summary of the data, and traders can calculate it by dividing the sum of data points by their number.
The opportunity to employ a mean reversion strategy may present itself when the current price moves far above or far below the mean. While rates may not be near the mean at the moment, they may clearly exhibit a tendency to revert to the mean.
Mean reversion can occur in various time frames. On Feb. 16, for example, crude oil was sitting far above its long-term mean, potentially indicating a reversion opportunity. In determining when to buy or sell based on mean reversion, one technique would be to use a statistical measure such as standard deviation. Standard deviation is the mean’s good friend and helper in measuring valuable, yet realistic, opportunities; it’s simply a measure of how much the data points deviate from the mean.
The mean price of crude oil, for example, has been roughly $70 per barrel over the last 10 years. The standard deviation is +/- $22. From statistical theory, 68% of the data (price) during the last 10 years has been within this $48 to $92 price range.
Thus, if the current price moves beyond $92, it indicates an overstretched market that may return to its average price of $70.
So, a mean-reversion trader taking a long-term view of crude oil may consider selling the commodity because over the last decade most values fall below the recently breached $92 threshold. (The war in Ukraine may void this example, but the principle holds true.)
By adjusting the look-back period in markets that exhibit mean reversion tendencies, traders can find new opportunities. Whether it’s intraday scalping or swing trading over several weeks, adjust the time frame and standard deviations to fine-tune entry and exit and thus gain control of profit and loss.
Michael Gough enjoys retail trading and writing code. He works in business and product development at the Small Exchange, building index-based futures and professional partnerships. @small_exchange
