What Is Mean Reversion and How to Use It?

What Is Mean Reversion?

Mean reversion is a finance theory suggesting that when an asset's price deviates significantly from its historical average, it will eventually return to that average.

For example, if a stock's price has been trading above its historical average, it may be considered overbought and due for a downward correction. On the other hand, if it is trading below its historical average, it may be seen as oversold and due for an upward correction.

This idea isn’t limited to just stock prices. You can apply mean reversion to other aspects of finance, like volatility, earnings, or even the overall performance of a market. The key takeaway is that extreme price movements often don’t last, and prices will eventually "revert to the mean."

How Does Mean Reversion Work?

At its core, mean reversion works on the idea that prices fluctuate around a central value, and when prices move too far from that value, they eventually return. Here’s a simple breakdown of how it works:

1. Identify the Average: Traders first look at an asset’s historical data to figure out its average price over a given time period.

2. Track Deviations: They then monitor when prices deviate significantly from that average.

3. Act on Deviations: When prices are too far above the average, they might sell (or "short") the asset. When prices fall well below, they might buy it.

For example, let’s say a stock typically trades around $100, but a news event pushes the price up to $130. A mean reversion trader might predict that this spike won’t last and expect the price to drop back toward $100.

Mean reversion appeals to a lot of traders because it can navigate any market dynamic without bias. 

Marco Santanche, quant strategist and author of the Quant Evolution newsletter, stated “Mean reversion is a popular strategy for a very simple reason: it is truly market neutral. In its most common application, pairs trading, mean reversion looks for cointegrated assets and identifies tradable pairs to build a market neutral portfolio."

How to Calculate Mean Reversion?

Now that we understand the concept, let’s look at how to calculate it.

The calculation of mean reversion involves statistical measures that help identify when an asset's price significantly deviates from its mean.

Don't worry, it's simpler than it sounds. Here are the mean reversion formula:

• Moving Averages

• Standard Deviation

• Z-Score

Moving Averages

Moving averages smooth out price data to highlight the trend direction over a specific period.

There are different moving averages, but the most common are the Simple Moving Average (SMA) and the Exponential Moving Average (EMA).

Simple Moving Average (SMA): The SMA is calculated by taking the average of a specified number of closing prices. For example, a 50-day SMA sums up the closing prices of the last 50 days and divides by 50.

Simple Moving Average Formula:

Where N is the number of periods.

Exponential Moving Average (EMA): The EMA gives more weight to recent prices, making it more responsive to new information. The calculation involves a smoothing factor, which is usually 2 divided by the number of periods plus 1.

Exponential Moving Average Formula:

Where N is the number of periods.

Standard Deviation

Standard deviation measures the dispersion of a set of values from their mean. In trading, it indicates the volatility of an asset's price.

A high standard deviation means prices are spread out over a large range, while a low standard deviation indicates prices are clustered closely around the mean.

Where:

• Xi is each individual price

• μ is the mean price

• N is the number of periods

Z-Score

The Z-score measures how many standard deviations a data point is from the mean. In mean reversion finance, it helps identify extreme price movements that may revert to the mean.

Z-Score Formula:

Where:

• X is the current price

• μ is the mean price

• σ is the standard deviation

Mean Reversion Calculation

Therefore, to calculate mean reversion, we put all of the above together:

1. Determine the mean price using the Simple Moving Average (SMA) or Exponential Moving Average (EMA) formula.

2. Calculate the standard deviation to measure price volatility.

3. Use the Z-Score formula to identify how many standard deviations the current price is from the mean, indicating potential reversion points.

This process helps you spot significant deviations from the average price, suggesting potential buying or selling opportunities.

Mean Reversion and Technical Analysis

Successful mean reversion trading often relies on the right technical tools. Here are a few key indicators you can use.

Bollinger Bands Mean Reversion Strategy

Bollinger Bands help you identify mean reversion opportunities.

They consist of a middle band (usually a 20-day SMA) and two outer bands that are set two standard deviations away from the middle band.

• When the price moves above the upper band, it suggests that the asset might be overbought and due for a mean reversion downward.

• When the price falls below the lower band, it indicates the asset might be oversold and due for a mean reversion upward.

Bollinger Bands effectively highlight volatility, helping you understand when prices will likely revert to the mean.

Relative Strength Index (RSI)

The Relative Strength Index (RSI) is a momentum oscillator that measures the speed and change of price movements on a scale of 0 to 100. It is used to identify overbought or oversold conditions.

• Overbought: An RSI above 70 suggests that the asset might be overbought and due for a downward correction.

• Oversold: An RSI below 30 indicates that the asset might be oversold and due for an upward correction.

Using RSI, you can spot potential mean reversion points where the price might revert to its historical average.

Stochastic Oscillator

The Stochastic Oscillator is another momentum indicator that compares a security’s closing price to its price range over a specified period.

• Values above 80 indicate that the asset might be overbought, suggesting a potential downward mean reversion.

• Values below 20 suggest that the asset might be oversold, indicating a potential upward mean reversion.

The Stochastic Oscillator helps you identify mean reversion opportunities by highlighting potential reversals in price trends.

Moving Average Convergence Divergence (MACD)

MACD is a trend-following momentum indicator that shows the relationship between two moving averages of an asset’s price (typically the 12-day and 26-day EMAs).

• When the MACD line crosses above the signal line, it suggests a potential upward mean reversion.

• When the MACD line crosses below the signal line, it indicates a potential downward mean reversion.

MACD is particularly useful for identifying changes in the strength, direction, momentum, and duration of a trend, which are essential for spotting mean reversion points.

Practical Application

By combining these technical analysis tools, you can develop a comprehensive mean reversion strategy.

For example, you might look for a stock trading below its lower Bollinger Band, with an RSI below 30 and a MACD line crossing above the signal line.

This combination of signals can indicate a strong mean reversion opportunity, prompting you to consider a buying position.

Mean Reversion Trading Strategies

Mean reversion trading revolves around the idea that prices will revert to their historical averages, providing traders with opportunities to buy low and sell high.

These strategies can be applied to multiple assets such as stocks, forex, commodities, and indices.

Let's dive into some specific trading strategies that leverage mean reversion, including day trading, swing trading, and forex trading.

Day Trading and Mean Reversion

Day trading involves buying and selling securities within the same trading day.

To implement a day trading mean reversion strategy:

1. Identify Overbought and Oversold Conditions: Use technical indicators like RSI, Stochastic Oscillator, or Bollinger Bands to spot overbought and oversold conditions.

2. Set Entry and Exit Points: Once you identify an overbought or oversold condition, plan your entry and exit points.
   If an asset is overbought, consider shorting it with a target to buy back at the mean level. Conversely, if it's oversold, consider buying it with a target to sell at the mean level.

3. Use Stop-Loss Orders: Day trading can be risky, so always set stop-loss orders to manage potential losses. Place your stop-loss orders just outside the identified overbought or oversold levels to protect your position.

4. Monitor Market Conditions: Continuously monitor the market for any changes that might impact your trade. Quick reactions to new information can be crucial in day trading.

Swing Trading and Mean Reversion

Swing trading aims to capture gains over a few days to several weeks. Mean reversion, which takes advantage of price corrections over a medium-term timeframe, fits well with this approach.

1. Identify Trends and Retracements: Use moving averages to identify the overall trend. Look for periods where the price deviates significantly from the moving average, indicating a potential mean reversion.

2. Combine Multiple Indicators: To increase the accuracy of your trades, combine multiple technical indicators. For example, use Bollinger Bands to spot price deviations and RSI to confirm overbought or oversold conditions.

3. Plan Your Trades: Set clear entry and exit points based on the identified mean reversion levels. For instance, if the price is below the lower Bollinger Band and RSI indicates oversold conditions, plan to buy and set your target at the moving average.

4. Patience is Key: Swing trading requires patience. Allow the trade to develop over a few days or weeks, giving the price time to revert to the mean.

Mean Reversion Forex Strategy

Forex trading involves trading currency pairs, and mean reversion can be particularly effective due to the cyclical nature of currency markets.

1. Identify Currency Pairs with Historical Trends: Find currency pairs with well-established historical trends and mean levels.

2. Use Technical Indicators: Apply moving averages, Bollinger Bands, and RSI to identify overbought or oversold conditions in currency pairs.

3. Set Entry and Exit Points: Plan your trades around the identified mean reversion levels. Enter a trade when the currency pair is overbought or oversold, and set your exit point at the mean level.

4. Consider Economic Data: Forex markets are heavily influenced by economic data releases. Incorporate fundamental analysis to complement your technical strategy, ensuring you're aware of upcoming economic events that could impact your trades.

Long-Term Investors’ Mean Strategy

Short-term traders, such as day traders and forex traders, use mean reversion in a more fast-paced, tactical way. They aim to profit from temporary price swings that occur within a few hours or even minutes.

However, for long-term investors like Warren Buffett, mean reversion is more than just a trading strategy—it’s a core principle of investing. 

Buffett’s approach involves buying stocks that are undervalued relative to their historical averages, expecting that over time, the market will correct itself and prices will return to more reasonable levels.

For example, if a solid company’s stock price drops sharply due to short-term bad news, a long-term investor might see this as a great buying opportunity. 

The assumption here is that the company’s fundamentals haven’t changed, and the price will eventually "revert" to reflect the company’s true value.

This approach requires patience. Long-term investors are less concerned with day-to-day price fluctuations and focus instead on the bigger picture, waiting months or even years for the stock to return to its historical average.

When Does Mean Reversion Work Best?

Mean reversion works best in range-bound markets, where prices are moving back and forth around a certain level without a strong trend. 

In bullish or sideways markets, mean reversion strategies often outperform because prices are more likely to correct back to their averages.

However, in bear markets or times of strong trends, mean reversion can be trickier. When prices are trending strongly in one direction, they may not revert to the mean for a long time, if at all.

Benefits and Limitations of Mean Reversion

Mean reversion provides benefits to traders but also has its own limitations.

Benefits:

• Provides clear entry and exit points based on historical data.

• Can be applied across various time frames (day, swing, forex) and markets.

• Helps identify overbought and oversold conditions.

Limitations:

• Market trends can persist longer than expected.

• False signals can occur, leading to potential losses.

• Requires a strong understanding of statistical measures and technical indicators.

Conclusion

Mean reversion helps you identify entry and exit points by understanding that prices tend to return to their historical average. By applying these mean reversion strategies, you can improve your trading performance and capitalize on profitable opportunities.