Mean Reversion Strategies

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Written By
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Written By
Dan Buckley
Dan Buckley is an US-based trader, consultant, and part-time writer with a background in macroeconomics and mathematical finance. He trades and writes about a variety of asset classes, including equities, fixed income, commodities, currencies, and interest rates. As a writer, his goal is to explain trading and finance concepts in levels of detail that could appeal to a range of audiences, from novice traders to those with more experienced backgrounds.
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Mean reversion strategies are based on the principle that prices of financial assets will eventually move back toward their long-term average or mean.

Here are a few examples of mean reversion strategies for trading financial markets:

Mean Reversion Strategies

Relative Value Trading

Relative value involves comparing the price of an asset to another related asset or market benchmark, and buying the undervalued asset and selling the overvalued one.

This strategy takes advantage of the tendency of related assets to move in tandem and the assumption that the mispricing will eventually correct itself.

Statistical Arbitrage

This strategy involves taking advantage of small price discrepancies between related assets that are expected to move in sync with each other over time.

Traders use statistical analysis to identify these discrepancies and then trade them to generate profits.

Collars

Collars could be considered a type of mean reversion strategy used to protect profits while still allowing for potential gains.

This strategy involves simultaneously buying a put option to limit downside risk and selling a call option to generate income, effectively creating a price range, or “collar,” within which the asset’s price can fluctuate while still allowing for profit.

Some traders use collars on dividend stocks. These tend to be more mature companies that aren’t likely appreciate as much.

So they surmise that selling calls allow for the accumulation of extra income while the put option can protect against a fall in the stock’s price.

We wrote more about this type of strategy here.

Rubber Band Trading

This strategy involves buying an asset when its price has moved significantly away from its mean, and then selling it once it has reverted back to the mean.

This strategy relies on the assumption that price fluctuations are temporary and that the asset will eventually return to its mean.

Moving Average Crossovers

Moving average crossover involves comparing the short-term moving average of an asset’s price to its long-term moving average.

When the short-term moving average crosses above the long-term moving average, it is seen as a buy signal, and when the short-term moving average crosses below the long-term moving average, it is seen as a sell signal.

Sometimes you can see market effects from a moving average crossover.

For example, when the 50-day MA cross under the 200-day MA, some traders will sell because it’s algorithmically built into certain systems. How much this affects each market (if at all) depends.

Bollinger Bands

This strategy involves using Bollinger Bands, which are a technical indicator that measures the volatility of an asset’s price, to identify overbought or oversold conditions.

When the asset’s price moves outside the upper or lower Bollinger Bands, it is seen as a buy or sell signal, respectively.

Mean Reversion Pairs Trading

Pairs trading is a strategy that involves identifying two historically correlated assets, buying the underperforming asset, and selling the outperforming one.

The assumption is that the relationship between the two assets will eventually return to its historical norm, leading to profits.

This strategy is a form of mean reversion as it capitalizes on the tendency of the asset prices to revert to their historical relationship.

Oscillator-based Strategies

Oscillator-based strategies involve using technical indicators such as the Relative Strength Index (RSI) or the Stochastic Oscillator to identify overbought or oversold conditions.

These indicators are based on the concept of mean reversion, as they assume that price movements will eventually reverse when they reach extreme levels.

Traders can use oscillator-based strategies to generate buy and sell signals based on the overbought or oversold conditions identified by these indicators.

Regression to the Mean Trading

This strategy involves identifying assets whose prices have deviated significantly from their historical regression lines.

Traders can use linear regression analysis to establish the mean price trend and identify instances where the asset’s price has moved too far away from this trend.

The assumption is that the price will eventually revert to the mean, allowing traders to profit from the subsequent price movement.

Percentage Price Oscillator (PPO) Strategy

The PPO is a technical indicator that measures the difference between two moving averages as a percentage.

Traders can use the PPO to identify overbought or oversold conditions and potential mean reversion opportunities.

When the PPO reaches extreme values, it may indicate that the asset’s price has deviated significantly from its mean, signaling a potential reversal.

Trading Price Channels

Price channels are a technical tool that can be used to identify mean reversion opportunities.

They consist of two parallel lines, one above and one below the asset’s price, which are drawn based on a specified number of standard deviations from the moving average.

When the asset’s price touches or breaches the upper or lower channel lines, it may indicate a potential mean reversion opportunity, as the price is expected to revert to the moving average.

 

FAQs – Mean Reversion Strategies

What is mean reversion, and why is it important in trading?

Mean reversion is a financial concept that suggests asset prices tend to revert to their long-term average or mean values over time.

This principle is important in trading as it forms the basis for several strategies that aim to profit from the natural tendency of asset prices to “snap back” to their historical norms after periods of abnormal deviation.

What are the main things to know about mean reversion strategies?

  • Mean reversion strategies are based on the principle that asset prices tend to move back toward their long-term average or mean, and can be applied to various types of assets and markets.
  • Examples of mean reversion strategies include relative value trading, statistical arbitrage, moving average crossovers, Bollinger bands, and oscillator-based strategies.
  • Risk management is important when employing mean reversion strategies, and traders can use methods such as setting stop-loss orders, diversifying their portfolio, and adjusting position sizes to manage risk effectively.

Can mean reversion strategies be applied to different types of assets and markets?

Yes, mean reversion strategies can be applied to various types of assets, including stocks, currencies, commodities, and indices.

They can be traded via the underlying asset, options and derivatives, futures, and other means.

The effectiveness of these strategies, however, may vary depending on the asset class and market conditions.

How can I determine the appropriate time frame to use for mean reversion strategies?

The appropriate time frame for mean reversion strategies depends on your trading style, risk tolerance, and the specific strategy you are using.

Short-term technical traders may use intraday or hourly charts, while longer-term traders may prefer daily or weekly charts.

How can I manage risk when using mean reversion strategies?

Risk management is important when employing mean reversion strategies (and in any circumstance).

Some methods for managing risk include setting stop-loss orders or using options to limit potential losses and cut-off tail risk, diversifying your portfolio across multiple assets and strategies to avoid over-reliance, and adjusting position sizes based on the level of risk associated with each trade.

Additionally, incorporating other forms of analysis, such as fundamental or sentiment analysis, can help you make better trading decisions and manage risk more effectively.

Do mean reversion strategies work during periods of high market volatility?

Mean reversion strategies can work during periods of high market volatility, but their effectiveness may be reduced due to the increased potential for rapid and significant price fluctuations.

Some strategies may be too risky to employ during periods of heightened volatility.

Can mean reversion strategies be used in conjunction with other trading strategies?

Yes, mean reversion strategies can be used in combination with other trading strategies, such as trend-following, breakout, or momentum strategies.

Combining different strategies can help you diversify your trading approach, reduce risk, and improve overall performance.

It’s essential to test and optimize your strategy combinations to ensure they work well together and complement your trading style.

How do I know when to exit a mean reversion trade?

Exiting a mean reversion trade typically involves setting profit targets based on the asset’s historical mean or using technical indicators to identify when the price has returned to a more “normal” range.

It is also important to use stop-loss orders to protect your positions from significant losses if the price does not revert as expected.

Monitoring market conditions and adjusting your exit strategy as needed can help you maximize profits and minimize risk.

 

Conclusion

Mean reversion strategies offer traders the opportunity to capitalize on the natural tendency of asset prices to revert to their historical norms after periods of significant deviation.

By employing techniques such as Rubber Band Trading, Relative Value Trading, Statistical Arbitrage, Moving Average Crossovers, Bollinger Bands, and other strategies mentioned in this article, traders can identify potential reversals and generate profits from these price movements.

However, it’s important to recognize the limitations of mean reversion strategies.

Many of these have heavy reliance on indicators that focus primarily on translations of price and volatility. Accordingly, they may be overly simplistic and don’t account for all the cause-effect drivers of markets.

Moreover, risk management is important when using mean reversion strategies.

Implementing stop-loss orders (whether through an actual stop-loss, options, or other means), diversifying your portfolio, and keeping position sizes appropriate can help minimize potential losses.

By understanding the principles of mean reversion, employing a diverse range of strategies, and incorporating effective risk management techniques, traders can maximize the potential of mean reversion trading and improve their overall trading performance.