Mean Reversion vs Trend Following – Primary Risks & Optimal Markets

In my last post we contrasted the effects of data integrity and sample size on the backtested performance of mean reversion and trend following models. In today’s post we’ll explore which markets are most suited to each approach, but before we do that, let’s quickly take a look at why I believe that every strategy can be categorised as either mean reversion or trend following, regardless of the underlying logic.

Over the years I’ve tested and analysed the performance of countless trading strategies. Through the process I’ve learned that the performance profile of any strategy falls within either of the following:

  • Moderate to high activity, high win rates, low average gains and consequently low risk/reward ratios and fat left tails.
  • Low activity, low win rates, high average returns and consequently high risk/reward ratios and fat right tails.

The first profile is typical of mean reversions strategies, while the second trend following strategies. It doesn’t matter whether you’re employing fundamental, technical, economic or any of form of data to drive the decision making, the performance profile will resemble one of the above. This essentially has to do with the way trades are closed – if the exit strategy capitalises on long pronounced trends, then you’re going to see a performance profile that resembles that of trend following. On the other hand, if a strategy seeks to lock in small and frequent gains, the performance profile will more closely resemble that of mean reversion.

The stark differences in performance statistics across each of these approaches leads to a unique set of risks, which in turn provide some insight into the suitability of each approach with a given set of markets. Next we’ll explore these risks and then look for markets that are more conducive to reducing these risks, providing each approach with the best set of market conditions for success.

Primary Risks

Mean reversion strategies do not let profits run since the target exit point is the mean. Essentially, they cut profits short which results in many small gains but infrequent and large losses – make small gains every month and then loose a fortune in a single month. Therefore, the single most significant risk to mean reversion lies in the left tail, or the probability that the market will trend severely against us (price shocks).

Trend following strategies let profits run, but since trends are rare, they experience many small losses and few large gains. Although losses are small, their frequency can result in large overall losses to a portfolio. Therefore, the primary risk to trend following is the cumulative effect of many consecutive losses, or said differently, the market’s inability to trend.

We can then conclude that mean reversion is better suited to markets that are less susceptible to powerful trends, while trend following is better suited to markets that tend to display powerful trends. As a result, we tend to find that either mean reversion or trend following work at any given moment, but not at the same time, that is, they’re mutually exclusive.

Optimal Markets

I’m now specifically examining the equity markets. Let’s see if we can uncover segments of the market that are better suited to each approach.

Which market segment is more prone to trend? What about large cap stocks? Well, for one thing these stocks are broadly followed, have already disrupted their respective markets and are well established. Therefore, the ability of large cap stocks to continually deliver products or services with massive market impact deteriorates, reducing the probability of significant future price trends.

What about small cap and mid cap stocks? These companies are still in the process of establishing themselves, are not as broadly followed and may provide technologies or services with the potential to significantly disrupt markets resulting in massive growth and powerful price trends.

The above premises are intuitive and make economic sense. Moreover, they bear themselves out in the data. I’ve quantified this extensively and found this to universally hold, not matter which exchange from the global markets we consider. With this knowledge we can now assign the most suitable approach to each market segment thereby boosting our chances of success.

Trend following strategies are far more effective in the mid cap and small cap market segment (long only – shorting the equity market to capture trends is exceedingly difficult due to the strong upward bias that equities display). These market segments provide the best hope of capturing extended price trends that can easily offset the many small losses that result from high losing rates and are consequently perfectly suited to trend following.

On the other hand, mean reversion strategies work much better on large cap stocks. These stocks have reduced price shock risk and their strong following means professionals actively support stocks during sell-offs (institutions love buying dips) and often engage in profit taking during short-term bursts to the upside, which results in precisely the behaviour we’re after for successful mean reversion.

Optimal Time-Frames

Trends take time to mature, which is why trend following approaches are better suited to longer time frames or longer holds. In fact, using weekly or monthly data yields better results than daily data. Because mean reversion is actively seeking to avoid long powerful trends, they tend to work better in shorter time frames. Therefore, daily data is more appropriate, and unless you have access to fundamental data that you can use as an overlay to gauge the health of a stock, mean reversion does not work well on weekly or monthly data because price is given too much room to mature into a powerful trend against us.


The unique performance characteristics of mean reversion and trend following make them ideal complements within a single portfolio. Mean reversion works well to bring some consistency to a portfolio, while trend following keeps the door open for the rare but significant right tail trends that can lead to fantastic outsized returns. Blending the two approaches in a single portfolio yields very desirable trade return distributions that enjoy both higher win rates and right skew. As a result, it’s my view that a blended approach is as close to holy grail as we can get. And the exciting news is that you can expect to see a multitude of powerful trend following strategies added to QuantLab within the next twelve months. Including trend following in our diverse offering will greatly improve our diversification abilities and further empower clients to build truly powerful and robust portfolios that enjoy exceptional trade return distributions.

Happy Trading,

Passionate about generating and sharing quantified trading models that empower individuals to trade successfully. I founded to realise my passion.

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