Mean Reversion

What Is Mean Reversion?

Mean reversion, or reversion to the mean, is a theory used in finance that suggests that asset price volatility and historical returns eventually will revert to the long-run mean or average level of the entire dataset.

This mean level can appear in several contexts such as economic growth, the volatility of a stock, a stock's price-to-earnings ratio (P/E ratio), or the average return of an industry.

The Basics of Mean Reversion

Reversion to the mean involves retracing a condition back to its long-run average state. The concept assumes that a level that strays far from the long-term norm or trend will again return, reverting to its understood state or secular trend.

This theory has led to many investing strategies that involve the purchase or sale of stocks or other securities whose recent performances have differed greatly from their historical averages. However, a change in returns also could be a sign that a company no longer has the same prospects it once did, in which case it is less likely that mean reversion would occur.

Percentage returns and prices are not the only measures considered in mean reverting; interest rates or even the P/E ratio of a company can be subject to this phenomenon.

The theory of mean reversion is focused on the reversion of only relatively extreme changes, as normal growth or other fluctuations are an expected part of the paradigm.

Using the Mean Reversion Theory

The mean reversion theory is used as part of a statistical analysis of market conditions and can be part of an overall trading strategy. It applies well to the ideas of buying low and selling high, by hoping to identify abnormal activity that will, theoretically, revert to a normal pattern.

Mean reversion has also been used in options pricing to describe the observation that an asset's volatility will fluctuate around some long-term average. One of the fundamental assumptions of many options pricing models is that an asset's price volatility is mean-reverting.

As the figure below depicts, the observed volatility of a stock can spike above or drop below its mean, but always seems to be bounded around its average level. High-volatility periods are typically followed by low-volatility periods and vice versa. Using mean reversion to identify volatility ranges combined with forecasting techniques, investors can select the best possible trade.

Image by Julie Bang © Investopedia 2020

Mean reversion trading in equities tries to capitalize on extreme changes in the pricing of a particular security, assuming that it will revert to its previous state. This theory can be applied to both buying and selling, as it allows a trader to profit on unexpected upswings and to save on abnormal lows.

Limitations of Mean Reversion

The return to a normal pattern is not guaranteed, as unexpected highs or lows could indicate a shift in the norm. Such events could include, but are not limited to, new product releases or developments on the positive side, or recalls and lawsuits on the negative side.

An asset could experience a mean reversion even in the most extreme event. But as with most market activity, there are few guarantees about how particular events will or will not affect the overall appeal of particular securities.