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What Mean Reversion Is, and How to Invest Using It

By Rebecca Hotsko • Published: • 10 min read

Economic booms and busts, or the peaks and troughs of the stock market, are typical examples of ‘mean reversion.’ However, investors often overlook how mean reversion affects companies’ valuations, the broader markets, and some are even trying to understand mean reversion for the first time.

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WHAT IS MEAN REVERSION?

The concept of mean reversion, also known as reversion to the mean, is a prevalent theory in finance that posits that the volatility and past performance of an asset’s price will eventually return to the average level over the entire data set.

mean reversion

Famed value investor Jeremy Grantham argues that “profit margins are probably the most mean-reverting series in finance, and if profit margins don’t mean revert, then something has gone badly wrong with capitalism. If high profits don’t attract competition, there’s something wrong with the system.”

Buffett agrees, and in 1999, he stated, “you must be wildly optimistic to believe profits can remain high for any sustained period.”

WHAT CAUSES MEAN REVERSION?

At an industry level, competition is the primary reason why mean reversion occurs, as fast-growing or highly-profitable industries attract new challengers.

This competition eats away at companies’ growth and profits. Eventually, the once fast-growing, profitable companies lose their competitive advantage or hit a mature point where most of their target market has been tapped.

If you take a step back and think about it simplicistly or logically, it makes perfect sense.

If there is a company that is growing wildly with significant margins, doesn’t it make sense that a company would come in and try to steal some of that market share?

It’s similar to an investor’s required rate of return. You might not buy a stock at a 3% Earnings Yield or a rental property at a 10% cash-on-cash return, but there might be somebody that is willing to. That’s how that stock or rental property can get bought and sold.

With a company’s profits and margins, they might be running at 80% gross margins and be happy with that. A competitor could come in and be happy with 70% gross margins. Because of that, they can likely offer a similar product at a lower price, which is attractive to potential customers.

This is the typical business’s life cycle, and it significantly impacts your returns as an investor.

MEAN REVERSION HAS TWO CRITICAL IMPLICATIONS FOR INVESTORS

Highly-profitable companies growing faster than the average tend to slow down and become less profitable over time.

Companies that were once profitable but now have declining profits, slowing growth, and are cheaply priced, may actually perform better over time.

A simple mistake that investors make is overpaying for fast-growing profits at present by extrapolating that growth unrealistically into the future.

If a company’s earnings per share (EPS) is growing above the market average of about 13% for the S&P 500 on a five-year basis, then the company’s shares should also be worth a premium to the market multiple.

Long-term returns, then, are derived from the company’s earnings growth, share price multiple expansions or contractions (price paid for a dollar of earnings), dividends, and share buybacks.

As investors, it’s essential to make educated guesses on how these factors will drive our returns in the future.

Let’s consider a company that can grow its earnings per share at an exceptional 25% rate.

This impressive growth should warrant that the stock trades at a premium to the market.

While a high-growth firm could outperform for years, most companies can’t sustain such elevated returns before new competitors drive their margins down, as I mentioned before.

Consequently, you might think that a company growing so fast would warrant paying almost any price to own it. However, your return depends not only on the company’s growth rate, but also the multiple, or price, you paid for that growth.

While it’s impossible to predict where a future price multiple will be, history shows that it tends to be very mean reverting.

Let’s further assume that the stock trades at a price-to-earnings ratio (PE) of 30, which is a premium to the average market earnings multiple of 20.

If this company wields 20% growth rates for any meaningful period, it’s less likely, not more likely, that it can continue doing so.

Suppose the company grows at 25% for three years before slowing to 20% in years 3-6 and then plateauing at the market average of 13% in years 6-10.

At the same time, because growth is slowing, the earnings multiple investors are willing to pay contracts from 30 to the market average of 20.

This is the result:

mean reversion example

Over time, as growth slows and the price multiple for its share correspondingly contracts, this investment’s compound annual growth rate (CAGR) over ten years is 10.65%, and you would have turned $10,000 into $27,514.

This isn’t bad by any means, but it’s far from the 20-25% rate you might have expected from this high-growth company.

Don’t forget, though, that the higher the multiple you pay today, the bigger deal this is to your return later on.

Let’s compare our results with what an investor would get if the company could maintain the same multiple:

stock investment return example

This result is drastically different from the first, where an investor expected this stock to earn an 18.59% CAGR over ten years with overly optimistic future price multiple expectations.

It’s often more reasonable to assume a company’s growth will revert to its industry’s average, as opposed to the market average, and compare those results.

Hopefully, this helps frame how to reconcile forecasts for an investment’s future earning growth with the anticipated earnings price multiple to develop better investment return expectations.

And if you’re stuck or want to know the historical growth rates by sector (compounded annually), along with the five-year growth rates in EPS, Aswath Damodaran publishes these data sets on his website.

FREQUENTLY ASKED QUESTIONS ABOUT MEAN REVERSION

In the context of financial markets, mean reversion is often used to describe the tendency for asset prices, exchange rates, interest rates, and other financial variables to move back towards its historical averages after experiencing periods of above-average or below-average returns. As example, typically profits margins and price multiples are two financial variable that tend to be very mean reverting over the long term.

History shows that price multiples tend to be very mean reverting. This means that there is a tendency of a company’s price-to-earnings (P/E) ratio (or other relevant price multiples) to move back towards the industry average over time. Price multiples, such as the P/E ratio, are widely used by investors to evaluate the value of a company’s stock.

As example, if the 5-year industry average P/E ratio is 20 but the current P/E ratio of the company is 40, this suggests that the company is expected to grow much faster than the industry average to justify the higher-than-average multiple. But, mean reversion suggests that as the fast-growing company eventually matures over time, the P/E ratio should also revert back towards the industry average as well, which leads to a contraction of the multiple from 40x to 20x over time.

Mean reversion is used in several investment strategies such as pair trading, statistical arbitrage, contrarian investing, and value investing. These strategies aim to exploit fluctuations in prices and take positions in assets that are expected to revert to their historical averages over time. It’s important to note that mean reversion can be a good investing strategy for some investors, but there is no guarantee that prices will revert back to their historical averages. In addition, mean reversion may not work as well in certain market conditions, such as during periods of high volatility or economic uncertainty.

Whether mean reversion is profitable or not depends on several factors, including market conditions, the specific investment strategy being used, time horizon, and the investor’s ability to effectively execute the strategy.

In general, mean reversion strategies can be profitable when prices deviate significantly from their historical averages, and the expectation is that they will eventually return to average over time.

It is difficult to quantify the success rate of mean reversion as an investment strategy, as it depends on several factors such as the specific strategy used, the market conditions, and the investor’s ability to effectively execute the strategy. Mean reversion strategies may be more effective in markets with a high degree of liquidity, and low volatility.

Trend following is one strategy that relies on the opposite tendency to that of mean reversion. While mean reversion strategies seek to exploit price discrepancies and take positions in assets that are expected to revert to their historical averages over time, trend-following strategies seek to exploit sustained price movements in a particular direction. Trend-following strategies will take positions in assets that are appreciating in value, with the expectation that the trend will continue, and exit positions in assets that are declining in value, with the expectation that their prices will continue to decline.

A basic mean reversion strategy involves identifying stocks that have deviated significantly from their historical averages and taking long or short positions in these assets with the expectation that their prices will revert back to their historical averages over time.

While they are related concepts, they are not exactly the same. Mean regression refers to the statistical phenomenon where unusually large or small changes in a random variable tend to be followed by moves that are closer to the mean. It occurs whenever the correlation between two variables is less than one. While mean reversion is quite similar in nature, it refers to the tendency for one variable (such as asset prices) to return to its historical average value over time, particularly after facing large deviations from that average value.

Mean reversion can be considered a type of regression to the mean, but not all regression to the mean is mean reversion.

There is financial and economic evidence backing the concept of mean reversion in financial markets. Particularly in asset prices, interest rates, currencies and even financial metrics such as profitability. Statistical methods such as regression analysis, time series analysis and hypothesis testing are used to demonstrate mean reversion.

There is no clear answer as to whether mean reversion or trend following is a “better” strategy, as each strategy tends to perform better in opposite market conditions. The effectiveness of mean reversion versus trend following strategies in financial markets can depend on a variety of factors, including market conditions, the assets being traded, and the investment horizon.

As example, mean reversion strategies are based on the idea that prices will eventually revert back to their historical averages, and they tend to work well and be profitable in markets that are characterized by low volatility and low transaction costs. On the other hand, trend-following strategies are based on the idea that prices will continue to move in the same direction, and they can be profitable in markets that are characterized by strong trends and high volatility.

Regression to the mean can be a problem in investing because it can lead to false expectations or incorrect decisions. If investors are not aware of the concept of regression to the mean and its potential impact, they may be misled into thinking that a stock, market or active fund manager that has performed exceptionally well in the past will continue to do so in the future. This can lead to overvaluation of the stock or market and ultimately result in disappointing returns.

For example, suppose a stock’s price has been significantly outperforming the market for a prolonged period of time. An investor may be tempted to attribute this outperformance to some underlying factor and make an investment in the stock, expecting that the outperformance will persist.

However, the regression to the mean effect can cause the stock’s price to revert back towards its mean, even if the underlying factor remains unchanged. This can result in the investor experiencing losses if they had made an investment based on the assumption that the outperformance would persist.

The regression to the mean fallacy occurs when people try to give a causal explanation of a phenomenon that is merely statistical or random in nature.

Someone who commits the regression fallacy assumes that something has returned to normal because some corrective action has taken place. When really, they failed to account for natural fluctuations, that can be random. In the context of investing, the regression to the mean fallacy can cause investors to make incorrect decisions based on recent stock performance. For example, an investor may invest in a stock that has outperformed the market recently, assuming that it will continue to do so, when in reality the stock’s performance may revert back to its mean as a result of random fluctuations.

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About The Author

Rebecca Hotsko

Rebecca Hotsko is an investor and entrepreneur based in Canada. Most recently, she co-founded a luxury boat sharing club in Kelowna B.C. Rebecca graduated from the University of Saskatchewan with a bachelor’s degree in Economics and since has completed CFA level I and II. In prior years, Rebecca gained valuable experience working as an analyst for the Bank of Canada, the federal energy regulator and in investment management. Her passion for teaching others how to invest using time-tested strategies backed by empirical data also led her to create an investing blog in 2020.

Rebecca Hotsko

Rebecca Hotsko is an investor and entrepreneur based in Canada. Most recently, she co-founded a luxury boat sharing club in Kelowna B.C. Rebecca graduated from the University of Saskatchewan with a bachelor’s degree in Economics and since has completed CFA level I and II. In prior years, Rebecca gained valuable experience working as an analyst for the Bank of Canada, the federal energy regulator and in investment management. Her passion for teaching others how to invest using time-tested strategies backed by empirical data also led her to create an investing blog in 2020.