What Is Mean Reversion, and How Do Investors Use It?

What Is Mean Reversion?

The concept of mean reversion is widely used in various financial time series data, including price, earnings and book value. When an asset's current market price is less than its average past price, it's considered attractive for purchase. Conversely, if the current price is above the average, it's expected to fall. Traders and investors use mean reversion for timing of their respective trading and investment strategies.

Understanding Mean Reversion

Mean reversion is a financial theory that suggests asset prices will eventually return to their long-term mean or average. This concept is grounded in the belief that asset prices and historical returns will gravitate toward a long-term average over time. The greater the deviation from this mean, the higher the probability that the asset's price will move closer to it in the future.

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 aren't the only measures considered in mean reverting; interest rates or even the price-to-earnings (P/E) ratio of a company can be subject to this phenomenon.

Use by Traders

Investors employ mean reversion strategies to capitalize on asset prices that have deviated significantly from their historical mean. The underlying assumption is that prices eventually will revert to their long-term average. Investors typically use mean reversion in the following ways:

• Statistical Analysis: Investors use statistical tools like Z-scores to measure how far an asset price has deviated from its mean. A Z-score above 1.5 or below -1.5 might signal a trading opportunity.
• Pairs Trading: Here, investors and traders identify two correlated assets. When the price ratio between them deviates from its mean, they go long on the undervalued asset and short the overvalued one.
• Volatility: Some traders and investors use mean reversion in the context of volatility, buying options when volatility is high with the expectation that it will revert to the mean.
• Risk Management: Stop-loss orders and take-profit points can be typically set around the mean to manage potential losses and secure gains.
• Algorithmic Trading: Quantitative analysts use mean reversion in algorithmic trading strategies, often using complex mathematical models to predict price movements.

Some considerations involved in mean reversion involve time horizon and market conditions. The effectiveness of a mean reversion strategy can vary based on the time horizon. Short-term traders may use intraday data, while long-term investors may use yearly data.

Another consideration is that mean reversion is more effective in range-bound markets and less so in trending markets.

Calculating Mean Reversion

Calculating mean reversion involves a series of statistical and quantitative steps to measure how far an asset's price has deviated from its historical mean.

First, historical price data is gathered for the respective asset. The time frame can vary based on the investor or trader's time horizon. Then the average price is computed over the selected time frame.

$Mean = Sum of prices of Prices / Number of Observations$Mean=SumofpricesofPrices/NumberofObservations

From there the deviation is calculated for each price point.

$Deviation = Price - Mean$Deviation=Price−Mean

Next, the standard deviation of the price series is computed, to understand the volatility.

$Standard Deviation = Square Root (Sum of Squared Deviations/ (Number of Observations -1)$StandardDeviation=SquareRoot(SumofSquaredDeviations/(NumberofObservations−1)

With these figures, a Z-score is determined. The Z-score measures how many standard deviations an element is from the mean.

$Z-Score = Deviation / Standard Deviation$Z−Score=Deviation/StandardDeviation

A Z-score above a certain threshold ( commonly 1.5 or 2) may indicate the asset is overvalued, and below a certain threshold (commonly -1.5 or -2) may indicate the asset is undervalued.

Mean Reversion and Technical Analysis

Mean reversion is a prominent concept in technical analysis, serving as the underlying principle for various indicators and trading strategies. It helps traders identify overbought or oversold conditions, thereby providing potential entry and exit points. Some technical indicator tools where the concept of mean reversion is involved:

• Moving Averages: Traders and investors often use moving averages to identify the mean price over a specific period. When the price is above the moving average and over a certain threshold, it may be considered overbought. Conversely, when the price is below the moving average and under a certain threshold, it may be considered oversold.
• Bollinger Bands: The bollinger bands technical analysis indicator consists of a middle band (simple moving average) and two outer bands calculated using the standard deviation. Prices are expected to revert to the middle band.
• Relative Strength Index (RSI): The RSI ranges from 0 to 100 and is used to identify overbought and oversold conditions. An RSI above 70 suggests overbought conditions, while below 30 suggests oversold conditions, both implying a potential mean reversion.
• Stochastic Oscillator: This indicator compares a security's closing price to its price range over a specific period, usually 14 days. Values in the stochastic oscillator that are above 80 are considered overbought, and values below 20 are considered oversold.
• Moving Average Convergence Divergence (MACD): The MACD is used to identify changes in the strength, direction, momentum, and duration of a trend. When the MACD crosses above or below its signal, it can be a sign that the asset is deviating from its mean.

Day Trading and Mean Reversion

Day trading involves buying and selling financial instruments within the same trading day, often holding positions for just a few minutes or hours. Mean reversion plays a critical role in day trading strategies, as it helps traders capitalize on short-term price fluctuations.

Some key strategies include intraday moving averages. Day traders often use short-term moving averages to identify the intraday mean price. When the asset's price deviates significantly, a reversion is expected.

Also day traders use RSI and stochastic oscillators for identifying overbought or oversold conditions on an intraday basis. Signals from these technical analysis tools often prompt day traders to enter or exit positions. Additionally, with bollinger bands, day traders look for "squeezes" where the bands tighten, indicating low volatility and the potential for a significant price move. The reversion is expected to the mean or middle band.

Indeed, some day traders use algorithmic strategies to execute high-frequency trades based on mean-reversion algorithms.

Swing Trading and Mean Reversion

Swing trading is a style of trading in which positions are held for several days to weeks, aiming to profit from short to medium term prices. Mean reversion is a key concept in swing trading, helping traders identify potential reversals in price trends.

A crossover or crossunder of the price and the moving average followed by a significant deviation from the price and the moving average can signal a potential reversal.

Also, tools like the RSI and the MACD are used to identify overbought or oversold conditions, signaling a possible mean reversion. Moreover, Fibonacci retracements are used to identify potential levels where the price may revert to the mean. The most common retracement levels are 38.2%, 50%, and 61.8%.

Finally, swing traders also can use candlestick patterns like the doji, hammer, bullish engulfing, and bearish engulfing patterns to identify potential reversals, including mean reversion opportunities.

Forex Trading Using Mean Reversion

As it pertains to forex trading, mean reversion strategies aim to capitalize on currency pairs reverting to their historical mean or average price. Mean reversion can be particularly useful for identifying short-term opportunities using technical analysis indicators.

Forex traders often use moving averages to identify the mean exchange rate over a specific period. When a currency pair deviates significantly from this average, a reversion is often expected.

Indicators like the RSI and stochastic oscillator are commonly used to identify overbought or oversold conditions in currency pairs, signaling potential mean reversion.

Another tool forex traders and investors use is pivot points. These are used to identify potential support and resistance levels where the price may revert to the mean. They are calculated based on the high, low, and closing prices of the previous trading session.

Finally, another tool that is used is currency correlations. Some traders and investors use mean reversion in the context of currency correlations. When two historically correlated currency pairs diverge, traders may go long on the underperforming pair and short the outperforming one.

A Hypothetical Example of Mean Reversion

Consider a mean reversion situation involving the stock of Company XYZ.

Over the past 200 days, the stock of Company XYZ has had an average closing price of 50. Due to a positive earnings report, the stock price jumps to $70.

The standard deviation of the stock's price over the past 200 days is $5.

The Z-score will then be calculated where (70-50)/5 = 4.

A Z-score of 4 indicates that the stock is significantly overvalued compared with its historical mean. This could be a signal to short the stock, as it is expected to revert to its mean.

Over the next few weeks, the initial excitement fades, and the stock price gradually fall back to around $52, closer to its historical mean.

Benefits and Limitations of Mean Reversion

Mean reversion offers a structured and versatile approach to trading but comes with its own set of challenges, including sensitivity to market conditions and higher transaction costs. Therefore, it is crucial for traders and investors to be aware of these factors and use robust risk management techniques.

Benefits of Mean Reversion

Mean reversion offers several benefits. These include:

• A Systematic Approach: Mean reversion provides a structured methodology for trading, making it easier to identify entry and exit points.
• Versatility: Applicable across various asset classes and time frames, from intraday to long-term ones.
• Risk Management: Fixed stop-loss and take-profit levels can be set around the mean, aiding in risk control.
• Profit Potential: The strategy can be profitable in range-bound markets, where other strategies like trend-following may not be as effective.
• Confirmation: Multiple indicators such as the ones described above, can be used to confirm mean-reverting signals, increasing the strategy's reliability.

Limitations of Mean Reversion

Any approach comes with challenges and limitations. Some limitations of mean reversion include:

• Market Conditions: Mean reversion is less effective in strongly trending markets, where prices may not revert to the mean for extended periods.
• Transaction Costs: The strategy often involves frequent trading, which has a propensity of higher transaction costs.
• False Signals: Shorter time frames in particular are susceptible to market noise, which can generate false mean-reverting signals.
• Economic Events: Economic shocks or sudden news can disrupt mean-reverting patterns, leading to potential losses.
• Lack of Direction: Unlike trend-following strategies, mean reversion is non-directional, which may not suit all trading styles.
  

The Bottom Line

Mean reversion is a financial theory that says asset prices will tend to revert to their historical mean or average over time. It serves as the backbone for various trading strategies across multiple asset classes, including stocks, forex, and commodities. Investors commonly use indicators like moving averages, RSI, and bollinger bands to identify mean-reverting opportunities. These indicators help pinpoint overvalued or undervalued assets, providing potential entry and exit points.

The strategy can be applied across different time periods, from intraday to long-term, and is particularly effective in range-bound or sideways markets. However, it's crucial for traders and investors to incorporate robust risk management techniques and be mindful of transaction costs, given the frequently traded nature of mean reversion strategies.