Mean reversion is a theory implying that asset prices and historical returns gradually move towards the long-term mean, which can be based on the economy, industry, or average return within a set of data.
The greater the deviation from their mean, the higher probability that the next movement of asset prices will be closer to the mean. In other words, an extreme event that would increase or decrease the momentum of a stock would likely be followed by a less extreme event that would cause far less fluctuation.
Trading with Mean Reversion
Generally, mean reversion is used as a statistical analysis of market conditions to determine a trading strategy. For example, from the perspective of investing, strategies that involve mean reversion are comparing stocks or other securities whose price-performance greatly contrasts its historical average.
Applying that knowledge, investors are capable of measuring and determining when to buy under the mean and sell above it. Mean reversion is also used in options pricing to better determine how an asset’s volatility fluctuates along with its long-term average.
Under the assumption that assets will revert back to their mean, many traders attempt to capitalize on catalysts that affect the price action of the stock. Thus, in terms of buying and selling, traders profit from upswings and prevent losses on downswings.
How Catalysts Affect Mean Reversion
It is important to recognize that unexpected highs or lows can ultimately imply a shift in the nature of the stock, caused by events such as positive or negative news. For example, if news that Tesla just produced a new model is released to the public, there would likely be a positive shock in prices for a certain period of time before reverting to levels before the shock. The duration for when the stock reverts is called the time to reversion.
Generally, returns of normal patterns are not always guaranteed, but it is indeed still possible for assets to experience mean reversion in the most extreme circumstances. Nonetheless, much like any event, it is difficult to fully determine how market activity for securities will be affected by the news.
Instead of reverting back to the mean, stock prices may lead to a random walk post-shock. A random walk is a process when prices do not return to previous levels, nor do they gradually move towards the mean. For example, an increase in the momentum of the stock may lead to a greater deviation from the mean.
Complementary Technical Indicators and Financial Information
For traders, tools such as the Relative Strength Index (RSI) can be used to determine oversold or overbought price levels, which act as proxies to enter and exit mean reversion trades.
Standard deviation, Bollinger Bands, and money flow are used to determine the distance away from the long-term average; therefore, these tools can be used to track unusual price movements.
Regarding financial statements, many investors analyze earnings reports. If a company reports strong quarterly earnings due to positive news or development, it’s been mentioned that the next quarter’s report would likely be closer to the average.
Arguments Against Mean Reversion
1. Markets are efficient
Many individuals believe that markets reflect all available information and that it is impossible to outperform the markets unless insider information is provided or some sort of illegal competitive edge’s been given.
For example, if a stock increases by 30%, there should be a cause behind that positive momentum. The stock may rise earlier than expected, potentially due to unreleased positive news. therefore, many people believe such price actions should not be possible before the announcement unless there is a specific, factual cause.
2. Poor performance indicators
With mean reversion indicators, such as Shiller’s CAPE, it’s been argued that many similar tools were tested using insufficient sample sizes. Thus, their results would be ineffective against the entire market.
Arguments for Mean Reversion
Although there are arguments against mean reversion trading strategies, many successful investors employed such an approach in the past and enjoyed a track record of success with it.
Long-term investors, such as Warren Buffett, use a contrarian type of investing strategy, which is fairly similar to mean reversion. Hedge fund founder Jim Simons of Renaissance Capital used mean reversion trading strategies to build capital.
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