Mean-Reversion Trading Strategies

Mean-reversion trading Strategies are based on the idea that a financial asset's prices return to their average price level over a particular period. The trading technique aims to earn profits from significant changes in an asset's price.

Mean reversion methods assume that when a share price or other indicator deviates too far from its historical mean, it is most likely to return to its historical mean in the future. In trading, mean reversion can be employed to analyze a wide range of market parameters, including cost, fluctuations, and other signals.

Mean-reversion trading Strategies assume stock prices will return to their average levels. In this trading style, prices appear to move quickly and steadily for an extended time frame. A trader who implements these techniques designs multiple strategies for executing the action. Consequently, in all circumstances, there is no absolute certainty of gains because instability, prices, and other trading elements influence the mean reversion signal.

In the stock market, the mean reversion theory claims that security prices and financial indicators are prone to returning to their historical average. The mean reversion approach may be applicable to the fundamental elements of investing, such as purchasing a stock with a modest profit-earnings (PE) ratio and anticipating the PE increase in comparison to the historical average PE. Traders commonly employ this approach to purchase securities for long-term investing. 

#1 - Day Trading and Mean Reversion

Day trading is the process of purchasing and selling financial assets on the same trading day. It involves holding a position that often lasts for only a few hours or minutes at most. Mean reversion is essential in day trading approaches because it enables traders to take advantage of short-term movements in the market. Intraday moving averages are one of the primary strategies that traders employ. Day-trading investors frequently utilize short-term moving averages to determine the intraday average price. When a security's price diverges substantially from the average, a return to its initial value is likely to take place.

#2 - Swing Trading and Mean Reversion

Swing trading is a type of trading approach in which positions are kept over multiple days or even weeks with the goal of benefiting from short to medium-term price movements. Mean reversion is a fundamental idea in swing trading because it helps traders detect expected turnarounds in price movements. Swing traders frequently employ longer-term moving averages than day traders to figure out the average price for a given time frame. A crossover or cross under of the market price and moving average, which is followed by an extensive departure from the price and moving average, may indicate a potential reversal in price trends.

#3 - Forex Trading and Mean Reversion

In forex trading, mean reversion methods seek to profit from pairs of currencies returning to their historical average or mean price. Mean reversion is especially beneficial for finding short-term prospects with the help of technical analysis markers. Forex traders frequently utilize moving averages to determine the average exchange rate for a given time range. When a currency combination diverges substantially from the mean, a reversal can usually be anticipated.

Let us study the following examples to understand this trading strategy:

Example #1

Suppose a company named Apex Softwares has its equity traded at an average closing price of $100 over the last 300 days. Following this period, a favorable earnings report resulted in the stock price rising to $150. The share price has a standard deviation of $10 during the last 300 days. The Z-score was, therefore, computed as (150-100)/10 = 5. The Z-score of 5 implied that the share price was considerably overpriced in comparison to its historical average. The result served as an indicator to short the stock, which was anticipated to fall back to its average. During the next several weeks, the initial sense of optimism diminished, and the company's share price gradually returned to its historical average. This is an example of the mean reversion technique.

Example #2

On December 11, 2023, the Nifty reached new highs for two weeks in a row, and the undercurrent was enthusiastic. The previous week, the Time Map demonstrated equality between bulls and bears, and they suggested employing mean reversion measures to achieve the most favorable trading outcomes. In general, the bulls had complete control of the financial markets, allowing little opportunity among the bears. PSU stocks went on to surpass, and the automobile industry followed suit, as anticipated. The most notable surprise was the enormous growth of OMCs (oil marketing companies).

Some benefits of this trading method include the following:

• Mean reversion trading methods are usually easy to comprehend and employ. It makes the strategies accessible to traders with many different levels of expertise and experience.
• These trading strategies have historically been proven effective, and there is an extensive amount of data from the past to back them up.
• The trading strategies offer clearly established entry and exit points. This feature allows traders to control the risks and rewards more effectively.
• This trading technique capitalizes on the market's ineffectiveness and, therefore, might end up in lucrative transactions.

The limitations of this trading method are:

• Even though mean reversion trading methods may have proved beneficial in the past, they are unlikely to be effective in the future.
• While these trading strategies presume that prices and other indicators will eventually return to their long-term average, they may continue to diverge from the mean for an extended amount of time, potentially resulting in losses for traders who use these methods.
• Identifying the historical average or mean can be challenging since different approaches may present varying responses, and the mean fluctuates over an extended period.
• Mean reversion trading methods require patience and discipline for an asset's price or other parameter to return to the mean. This method can be complicated for specific traders who enjoy proactive trading tactics.