What is mean reversion trading strategy?

How to use mean reversion trading strategy: 3 tested examples by traders

A lot of different financial time series data, such as price, earnings, and book value, use the idea of mean reversion. An asset is considered appealing for purchase when its current market price is lower than its average historical price. On the other hand, a price decline is anticipated if it is currently higher than average. The timing of individual trading and investing strategies is determined by traders and investors using mean reversion.

The underlying assumption of this idea is that historical returns and asset prices are inclined toward a long-term average. The likelihood that the value of the asset will eventually approach this mean increases along with the size of the deviation from it.

Mean reversion: Deeper understanding

The concept known as mean reversion is based on the idea that metrics and prices tend to swing around their extended average value. Put simply, mean reversion suggests that a price or other metric will eventually revert back towards its historical average if it deviates from it.

Numerous investing strategies that entail buying or selling stocks or other securities whose recent results have deviated significantly from their historical averages have been produced by this theory. Mean reversion is less likely to happen in this scenario, though, as a shift in returns may also indicate that a company’s prospects have changed. Mean reversion takes into consideration more than just prices and percentage returns. Interest rates and even a company’s price-to-earnings (P/E) ratio may be affected.

How traders use mean reversion

In the trading world, mean reversion can be used to analyse price, volatility, and other market metrics. Traders who use mean reversion, for instance, might search for stocks or other assets that have seen a sudden increase or decrease in price. This could suggest that the market has overreacted to a breaking story or event. In the event that they see a return to their long-term average price, they might then try to purchase or sell those assets.

Mean reversion can be used in relation to volatility, as mentioned above, where traders can search for unexpectedly high or low volatility periods and employ that information to guide their trade selections. Mean reversion strategies can also be used with other indicators, like moving averages, to pinpoint overbought or oversold market conditions.

Mean reversion trading strategies: 3 examples

Mean Reversion Strategy with a Moving Average

Traders using this strategy search for price differences from the moving average, as these could indicate opportunities to buy or sell. An asset is said to be undervalued when its price falls below its moving average. Traders may want to consider purchasing the asset since it is probably going to return to its mean. Similar to this, an asset is deemed overpriced when its price is trading above its moving average; traders may want to sell the asset since it is probably going to return to its mean.

A simple moving average (SMA), which determines the average price of an asset over a predetermined time period (such as 50 days, 200 days, etc.) by adding up the prices and dividing by the number of periods, is usually the moving average used in the moving average mean reversion strategy.

Other moving averages, like the exponential moving average (EMA), which places more weight on recent price data and may react to price changes more quickly, may be used by certain traders. Traders have the option of using multiple alternative moving averages. The type of moving average a trader uses will ultimately depend on their trading style and personal preferences.

Mean Reversion Strategy for Pairs

Trading this strategy begins with traders selecting two comparable instruments (e.g., two stocks in the exact same category or a pair of currencies in a similar region) that have moved together historically. The past connection connecting the two instruments is then calculated, for example, by figuring out the difference in price. Deducting the price of one instrument from the other gives the spread, which is the price difference between the two.

Traders might think about making a trade when the spread breaks away from its historical mean or average. For instance, traders may think about purchasing an asset that is more affordable while selling the asset that is somewhat more costly if the spread expands beyond its historical range. The idea behind this strategy is that the spread will ultimately return to its mean.

In contrast, traders may think about selling the comparatively less expensive instrument and purchasing the comparatively more expensive instrument if the spread narrows below its historical range. They would do this in the hopes that the spread would eventually return to its mean.

Mean Reversion Strategy for Volatility

When using this strategy, traders usually look for times with extreme or low volatility using a volatility indicator, like the VIX (CBOE Volatility Index). Often used as an indicator of market fear or uncertainty, the VIX index calculates the potential volatility of options on the S&P 500 index.

With the hope that volatility will eventually return to its mean, traders may think about selling options or shorting the underlying asset when the VIX moves above its long-term average or mean. On the other hand, traders may think about purchasing options or going long on the underlying asset when the VIX moves below its long-term average, hoping that volatility will eventually rise back to its mean.

To find possible mean reversion opportunities, traders can also use other volatility indicators, such as the implied or historical volatility of specific stocks or other financial instruments.

Mean reversion: Advantages & Disadvantages

Advantages

Easy to comprehend and use: Trading strategies based on mean reversion are comparatively easy to comprehend and use, making them available to traders with varying levels of expertise.

Historical information: A large body of historical data attests to the past performance of mean reversion trading strategies.

Clearly defined entry & exit points: The clearly defined entry and exit points of mean reversion trading strategies encourage traders’ ability to control risk and realise profits.

Market errors: Mean reversion trading techniques capitalise on these variations in the market to make profitable trades.

Disadvantages

No assurance: Although mean reversion trading techniques have shown potential in the past, there is no guarantee that this success will continue.

Risk of an extended departure from the mean: While mean reversion trading strategies count on prices and other metrics to eventually revert to their long-term average, there’s a chance that they won’t, and this could cause traders to lose money if the strategy’s deviations from the mean persist for an extended length of time.

Challenges in identifying the mean: Finding the long-term average or mean can be challenging since various approaches can yield different outcomes and the mean can fluctuate over time.

Requires time and control: For traders who prefer more active trading strategies, mean reversion trading strategies can be difficult to use because they require patience and discipline while they wait for the value or other metric to shift back towards the mean.

Final thoughts

The goal of mean reversion strategies is to profit from asset prices that return to average, or normal, levels. Therefore, although historical data is important to take into account when evaluating a mean reversion strategy, it does not guarantee that the asset price will rise or fall. The financial asset’s mean may rise in line with its average. It is rare for prices to hold steady for a prolonged period of time when taking the mean into account.

Disclaimer:
This information is not considered investment advice or an investment recommendation, but instead a marketing communication. IronFX is not responsible for any data or information provided by third parties referenced or hyperlinked in this communication.