Mean Reversion: Meaning, Indicators, Trading Strategies and More

In this article, we will discuss

• What is Mean Reversion?
• Calculating the Likelihood of Mean Reversion
• An Example of Mean Reversion
• Technical Analysis: Indicators for Mean Reversion Analysis
• Mean Reversion Trading Strategies
• The Advantages of Trading Using Mean Reversion
• Limitations of Mean Reversion Trading
• Conclusion

The financial markets are dynamic segments where the prices of securities are constantly changing. To make sense of the constant market movements, experts and analysts have developed various theories and principles that offer greater clarity about price changes. These concepts form the foundation of the different trading strategies we use today. One such concept is mean reversion. It requires the use of key technical indicators like the Simple Moving Average (SMA), Exponential Moving Average (EMA), Bollinger Bands and more — all of which are available real-time on the Samco trading app.

The principle of mean reversion may be unfamiliar to beginners. However, by understanding what this concept is and how you can analyze it using technical trading indicators, you can tailor your strategies to make the most of the price movements expected.

In this article, we will discuss the meaning of mean reversion, how it works, what indicators you can use in mean reversion analysis and how to trade accordingly.

What is Mean Reversion?

Mean reversion is a theory or a concept that suggests that over time, an asset will revert to its average price levels. No asset’s price is a clean linear or exponential trajectory. There are periods of steep declines, significant increases and moderate changes. However, the principle of mean reversion states that extreme price movements are often followed by periods when asset prices return to the mean price level.

The mean reversion is not limited to asset prices alone. It can also be applied to various other characteristics of the market and the securities traded therein. These aspects include volatility, earnings, growth in earnings and the levels of any other trading indicators. In keeping with the theory, the more the price (or any other variable) deviates from the average, the higher the chances that it will adjust to revert closer to the mean.

Calculating the Likelihood of Mean Reversion

The mean is a statistical measure. So, to find the probability of mean reversion, you need to follow the statistical steps outlined below.

• Step 1: Calculate the Mean

Start by finding the mean price. You can use trading indicators like the SMA here. To find the mean, you can use this formula:

Mean = Sum of the prices over a given period ÷ Number of observations

• Step 2: Find the Deviation

Once you have the mean, you need to find out how much each price point in the set of observations deviates from the mean. To find this, use the formula shown below:

Deviation = Price — Mean

Some prices will have positive deviations (i.e. they will be higher than the mean) and others will have negative deviations (i.e. they will be lower than the mean).

• Step 3: Find the Standard Deviation

The next step is to find the standard deviation. This will give you a clearer idea of how much the prices have deviated from the average overall. The formula for the standard deviation is:

Standard Deviation = Square Root of [(The Sum of Deviations Squared) ÷ (The Number of Observations — 1)]

• Step 4: Arrive at the Z-Score

The last step is to find the Z-score, which tells you how far a data point is from the mean of the entire distribution. This is the formula to find the Z-score:

Z-Score = Deviation ÷ Standard Deviation

The Z-Score can tell you whether a stock is overvalued or undervalued. If the value exceeds 1.5 or 2, it indicates overvaluation. Conversely, if it is below -2, it indicates undervaluation. You can use this interpretation to determine the likelihood of a price correction and structure your mean reversion strategy accordingly.

An Example of Mean Reversion

Let us discuss a simple hypothetical example to understand how you can decide if a reversion is imminent. Say the average price of a company’s stock over the past 6 months is Rs. 100 and its standard deviation is Rs. X. Due to high quarterly revenue and profits, its share price increases to Rs. 130.

The Z-Score in this case can be calculated as the ratio of the deviation and the standard deviation. This gives us a score of around 4.2 (i.e. [Rs. 130 — Rs. 100] ÷ Rs. 7). A score as high as this means that the company is currently overvalued in the market and a price correction may be due. So, it may be a signal to short the security or close a long position.

Technical Analysis: Indicators for Mean Reversion Analysis

Although the mean is the most crucial trading indicator required to create a mean reversion strategy, you need to rely on various other metrics to make smarter decisions. These indicators include the following:

• Moving Averages:

You can use the SMA and EMA to easily find the mean price or variable over a given period. This threshold helps you identify if the market may be overvalued or undervalued. For instance, prices well above the mean may indicate an overbought situation, which means the stock or security may be poised for a decline. On the other hand, if the price is below the MA, the security may be oversold and could reverse upward in the near future.

• Relative Strength Index (RSI):

The RSI is another common trading indicator that helps determine oversold and overbought market conditions. It measures how quickly and how much a variable is changing. Its value can start from 0 and go up to 100. Typically, if the RSI of a stock’s price exceeds 70, it means the security may be overbought and ready to revert to the mean. Conversely, if the RSI is below 30, the security may be oversold and also due for a mean reversion.

• Bollinger Bands:

This indicator uses the SMA as well, making it crucial for developing an effective mean reversion strategy. It consists of three bands — with the middle one representing the SMA and the two outer bands representing the standard deviations from the mean. If the price of a stock is closer to any of the outer bands, it may suggest an extreme move that is due for a reversion.

• Moving Average Convergence Divergence (MACD):

The MACD is a versatile indicator that gives you wide-ranging insights into the behaviour of a stock. It tells how strong a price movement is, the direction of that price movement, its momentum and the duration of the price change. It is a three-part signal that includes the MACD line, signal line and histogram. Extreme values in the MACD histogram or large distances between the MACD and signal lines may signal the possibility of a reversion.

• Stochastic Oscillator:

This trading indicator helps you account for price oscillations or swings. In simple terms, it compares a stock’s current price with its historical price variation over a given period. Its values also oscillate between 0 and 100 like the RSI. The threshold limits, however, are 20 and 80. Oscillator values less than 20 suggest that the stock is oversold and due for a bullish correction. Conversely, values over 80 suggest that the stock is overbought.

Mean Reversion Trading Strategies

Now that you know what this concept is and how to identify a possible price correction, you can better understand how different mean reversion strategies are formulated. Let us explore the top trading strategies you can employ when you expect a price correction to the mean.

• Intraday Trading

An intraday mean reversion strategy focuses on short-term price fluctuations within a single trading day. You need to look for temporary price deviations from intraday moving averages and other intraday technical indicators. This strategy aims to capitalise on quick reversions, so you can use indicators like RSI or Bollinger Bands to identify overbought or oversold conditions within the day. Since you open and close the position within the same day, you need to use this strategy only in liquid markets with high intraday volatility.

• Swing Trading

This mean reversion strategy spans across several days to weeks and targets larger price movements. You need to identify assets that have significantly deviated from their long-term moving averages or trend lines. Then, you should enter a new position when the price shows signs of reverting. It is best to hold the trade open until the price approaches the mean. This strategy may require the use of fundamental analysis alongside technical trading indicators to confirm the likelihood of reversion.

• Pairs Trading

Pairs trading is a market-neutral mean reversion strategy where you purchase one asset and sell another correlated asset simultaneously. To execute this type of trade, you must identify two assets that historically move together and initiate a new position when their price relationship deviates significantly from the norm. As the relationship reverts to its mean, your trade can generate profit. You can apply this strategy to stocks in the same sector, ETFs or even securities in different asset classes.

• Volatility-Based Trading

This strategy focuses on the mean reversion of volatility rather than price. Here, you use indicators like the India VIX (Volatility Index) or historical volatility measures to identify periods of extremely high or low volatility. Then, you can take positions expecting the volatility to return to its average levels. This can involve trading volatility-based products directly or using options strategies. The trading strategy is particularly popular in options markets, where you can leverage temporary mispricing caused by volatility spikes or lulls.

• Algorithmic Trading

Algorithmic mean reversion strategies use computer programs to identify and execute trades based on predefined criteria. These algorithms can analyse vast amounts of data quickly to identify subtle mean reversion opportunities across multiple assets. They often incorporate advanced statistical methods like cointegration analysis or machine learning to refine their predictions. Algorithmic approaches can execute trades with high frequency and precision, so you can capitalise on small price deviations. This strategy is particularly effective in high-frequency trading environments.

The Advantages of Trading Using Mean Reversion

Trading with mean reversion strategies can be beneficial in many ways. The main advantages include the following:

• Versatility and validity across different asset types and asset classes
• A systematic approach that is also beginner-friendly
• Easier risk management with specific target profit and stop-loss levels
• Multi-point confirmation using different technical indicators
• Significantly profitability is sideways or range-bound phases in the market

Limitations of Mean Reversion Trading

Mean reversion trading also has a few downsides such as these:

• Non-directional trading style that may not be preferable for some traders
• Possibility of false signal misleading your strategy
• Ineffective in markets that are highly directional
• Potentially high transaction costs if you use mean reversion strategies that require frequent trading

Conclusion

To sum it up, mean reversion strategies can be extremely useful if you employ them in the right markets. Technical analysis is crucial for identifying periods of strong price or volatility deviations. So, to get better at spotting the potential for reversions, focus on technical indicators like moving averages, MACD, Bollinger Bands and RSI.

You can monitor these indicators and more live on the Samco trading app. If you do not have a Samco trading account, open yours today to gain access to this app, which offers a host of features to make trading easier and more effective across all market segments.

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