Two trend followers can look at the same market, reach opposite conclusions about how to trade it, and both be right. This is not a paradox. It is the consequence of a distinction that is frequently overlooked in discussions of trend following methodology: not all trends are the same, they are not drawn from the same region of the return distribution, and the strategies appropriate for one class of trend are structurally unsuited to the other.
Two Classes of Trend, Two Regions of the Distribution
Market return distributions are not uniform. They have a central region, where the bulk of price movements cluster around an equilibrium, and tail regions, where extreme deviations mark transitions between regimes. These two regions produce fundamentally different types of trend, and understanding which region a trend is drawn from is the first step toward understanding what kind of strategy is appropriate for it.
Convergent trends emerge from the central region of the distribution. They are directional moves within larger cycles of mean reversion, where prices oscillate around a central equilibrium and periodically extend in one direction before returning toward it. These trends are relatively frequent, reasonably predictable in form and duration, and they follow patterns that linear models can describe with some reliability. They arise from the peak of the market’s return distribution, from the stable regimes where participant behaviour is consistent and the rules governing price movement are relatively well-defined. For traders who target this region, the predictability of convergent trends makes them accessible and manageable. Entry and exit rules can be specified with reasonable precision. The duration of the move can be estimated within a useful range. Position sizing and correlation management can be calibrated on the basis of historical behaviour that is likely to persist.
Outlier trends are drawn from the tail regions of the distribution. They are the transitions between regimes: the large, persistent, serially correlated moves that mark the breakdown of one stable equilibrium and the emergence of another. They are infrequent, non-linear in character, and their duration and magnitude cannot be estimated from the statistical properties of the prior stable regime. They break away from the patterns that convergent strategies are calibrated to exploit. They are not more extreme versions of convergent trends. They are a different phenomenon entirely, arising from a different part of the distribution and requiring a different strategic architecture to navigate and capture.
Different Distributions, Different Strategies
The strategic implications of this distinction are direct and consequential. A convergent strategy is designed to exploit the predictability and stability of the central distribution. It can use tighter stops, because the expected move has a more defined character and a reversal that exceeds the expected range is informative rather than just noise. It can use correlation-based position sizing and portfolio construction, because the relationships between assets in a stable regime are relatively persistent. It can adjust position size post-entry on the basis of how the move is developing relative to the model’s expectations, because the model’s expectations are meaningful in a linear, predictable regime.
An Outlier-targeting strategy cannot apply the same rules. The non-linear, non-stationary nature of Outlier trends means that the statistical properties of the prior regime are not reliable guides to the current one. Tight stops that would correctly identify a failed convergent trade will be triggered by the ordinary noise of a developing Outlier move before the move has had the opportunity to express its full magnitude. Correlation-based portfolio construction that works in stable regimes will produce misleading estimates of diversification benefit precisely when the Outlier is arriving, because correlations shift in transition events. Position sizing rules calibrated on the volatility of the prior stable regime will undersize the position relative to the opportunity that the Outlier represents.
The Outlier Hunter’s approach inverts the convergent strategy’s priorities. The primary discipline is not exploiting the predictability of the move. It is surviving the unpredictability of the path. Cutting losses short on positions that do not develop into Outliers, accepting a high frequency of small losses as the cost of maintaining participation across the full range of potential Outlier locations, and letting profitable positions run without a fixed target are the structural requirements of Outlier capture. These rules produce a positively skewed return distribution precisely because they are the wrong rules for convergent trends and the right rules for Outlier trends.
Why Practitioners Disagree
This is the source of the genuine methodological disagreements among trend following practitioners that can appear, to an outside observer, as contradictions. Whether to use stops or not, whether to adjust position size post-entry, whether to rely on correlations to manage portfolio risk, how much diversification to apply: the answers to all of these questions depend on which region of the distribution the strategy is targeting. A practitioner who says Tomato and a practitioner who says Potato are not making the same argument with different words. They are targeting different phenomena from different parts of the distribution, and the rules appropriate for one are structurally inappropriate for the other.
This does not mean that one approach is correct and the other is not. Convergent strategies extract genuine edge from the predictable properties of stable regimes. Outlier strategies extract genuine edge from the fat-tail properties of transition events. They are not in competition. They operate in different regions of the same distribution, and both regions produce tradeable opportunities for a process correctly designed to exploit them.
What they cannot do is share the same rulebook. The diversity of approaches within trend following is not a symptom of confusion or disagreement about the nature of markets. It is the rational consequence of practitioners correctly identifying which region of the distribution they are targeting and designing strategies appropriate to it. Trend following is a broad methodology precisely because the distribution of market returns is broad, and different parts of that distribution require fundamentally different responses.