More often than not, it amounts to selling your best assets too early, holding onto mediocre positions for too long, and thus weakening exactly what drives long-term stockmarket performance: capturing the "big winners." Academic literature does not suggest that such a rule mechanically condemns every investor to underperform every year. Instead, it clearly shows that arbitrarily skimming winners while leaving the rest untouched reduces long-term expected returns and makes it harder to outperform a benchmark.
The first reason lies in the deeply asymmetrical nature of stockmarket returns. For a stock, the maximum loss is bounded: in the worst-case scenario, an investor can lose 100% of their stake if the company goes bankrupt. Conversely, the potential gain has no theoretical ceiling: a position can return +100%, +500%, +2,000%, or more.
Hendrik Bessembinder shows that, over a very long period in the United States, the best-performing stocks account for the bulk of net wealth creation in the equity market. Indeed, the top 4% of stocks alone generated the entire wealth surplus relative to Treasury bills; the rest of the market, in aggregate, performed no better than these risk-free assets. In an update covering US stocks through 2023, he also highlights that the majority of stocks actually produced a negative cumulative return over their listed lifetime.
In other words: in equities, a small minority of massive winners compensates for a mass of mediocre, disappointing, or capital-destroying stocks. Systematically cutting gains at +20%, +50%, or +100% amounts precisely to sabotaging access to that handful of exceptional trajectories that drive the bulk of long-term performance.
This is where the logic of asymmetrical returns comes into play. Stockmarket success does not depend solely on the "win rate"—the percentage of winning positions. It depends primarily on the combination of the win rate and the ratio of average gain to average loss. An investor can be right only half the time and still make money if their average gains are significantly higher than their average losses.
This is even a classic structure in many high-performance management approaches. If gains are artificially capped while potential losses remain open or are handled with less rigor, this ratio is mechanically degraded. The right side of the distribution—the one that pays for all the mistakes—is compressed without a symmetrical reduction of the left side. The result is not just psychologically reassuring; it is economically unfavorable.
This temptation to sell winners too early is perfectly documented by behavioral finance. It has a name: the "disposition effect." Terrance Odean demonstrated, using real retail investor accounts, that people are more likely to realize their gains than their losses. Barber and Odean, and their subsequent syntheses on individual investor behavior, show that this bias is recurrent: retail investors tend to sell rising stocks too quickly and hold falling ones for too long, with adverse effects on their performance. Barberis and Xiong later formalized the theoretical framework for this preference for realizing gains, helping to explain why materializing a profit provides a psychological satisfaction that has nothing to do with financial optimality.
The problem becomes even clearer when examined through the lens of momentum. Since Jegadeesh and Titman, literature has shown that a strategy of buying recent winners and selling recent losers has historically generated robust abnormal returns.
This finding has been confirmed over other periods and extended to other markets and asset classes, notably by Asness, Moskowitz, and Pedersen, who found consistent value and momentum premiums across eight markets and asset classes.
Kenneth French continues to publish momentum series in his Data Library, proving that the factor is fully integrated into the empirical architecture of modern asset pricing. Numerous studies explicitly compare standard models to their versions augmented by a momentum factor.
The chart below shows the evolution of the WML (Winners Minus Losers) premium in Europe, which is the result of a long-short strategy—roughly a mechanism of "buying what has gone up over the last 12 months and selling what has gone down over the same period." The result: +140% for this long-short since 2012. For more information, refer to the book "Surperformer," Section 6, Chapter 7. Conclusion: Buy stocks that are rising and do not sell them too early.
Valuations in USD excess returns VS primes
Zoom 1 month 3 months 6 months 1 year 2 years 3 years 5 years 10 years All 30 Dec. 2011 to 2 Apr. 2026
Stocks that have risen are, on average, more likely to continue performing well over the short-to-medium term than weak or deteriorating stocks. Mechanically skimming at +20%, +30%, or +50% therefore means positioning oneself, at least partially, against this premium. A positive exposure to momentum is replaced by an imposed mean-reversion reflex, without evidence that this fixed-threshold exit rule creates value.
It is also important to emphasize a point that is often misunderstood: a +20% capital gain is not a financial signal in itself. It says nothing, on its own, about future valuation, business quality, growth duration, earnings revisions, the strength of the moat, or the persistence of momentum.
A stock that has just risen by +40%, for example, may have become excessively expensive; but it could just as easily be at the beginning of a long sequence of value creation. Microsoft, Alphabet, Amazon, Nvidia, and ASML have all experienced multiple +40% plateaus throughout their market history. An investor who applied a blind skimming rule each time would have missed out on a large part of the convexity of these trajectories.
The stock market disproportionately rewards the ability to remain exposed to the rare "mega-winners." Any rule that cuts these winners without robust fundamental or quantitative analysis tends to damage portfolio convexity. This idea is precisely consistent with Bessembinder's work on the extreme concentration of wealth creation in a small number of stocks.
This also explains why this type of discipline can make it difficult to outperform a benchmark. A market-cap-weighted index mechanically allows its winners to grow as long as their market weight increases. An investor who regularly sells their strong positions at +20%, +30%, or +50% denies themselves this natural concentration mechanism in the best performers. They must then compensate for this handicap with a reallocation capability far superior to that of the market: they must sell winners early, immediately identify other future outperformers, and repeat the process without major error. This is a much higher stock-picking requirement than that imposed by simply holding winners with discipline. In practice, this mechanical skimming increases the difficulty of beating the index because it removes one of the portfolio's most powerful engines: the progressive scaling of the best positions.
However, an important nuance must be maintained for the argument to remain scientifically defensible. To say that skimming capital gains is a market fallacy does not mean that one should never sell a position with a large gain. A winner can certainly be sold for good reasons: an invalidated investment thesis, a valuation that has become clearly excessive, a deteriorating risk/reward profile, a concentration risk that has become disproportionate, tax changes, a need for diversification, or an arbitrage toward a higher-quality opportunity. What the literature disputes is not the act of selling itself; it is the mechanical rule based solely on the fact that a position has reached +20%/+30%/+50%. The threshold contains no fundamental information. It is not an investment rule; it is an emotional accounting reflex.
The most important practical question remains: what should an investor do who actually needs to generate liquidity each year?
The right answer is not to systematically cut winners, but to organize withdrawals in a way that is compatible with performance logic.
- A first solution is to fund liquidity needs through the portfolio's natural flows: dividends, coupons, new cash inflows, or even a dedicated cash bucket covering 12-to-24 months of withdrawals. This avoids forcing sales of the best positions at the wrong time.
- A second solution is to first sell positions where the thesis has deteriorated, where future potential has normalized, or where the valuation clearly exceeds the expected quality.
- A third solution, often very effective, is to perform rare and tolerant rebalancing—for example, once or twice a year—by selling only those positions that have become oversized relative to a predefined maximum weight limit. In this context, you do not sell because the position is up +20%; you sell because it has become too large relative to the total portfolio risk. This is very different.
Finally, if liquidity must absolutely be extracted each year, it is better to establish a withdrawal budget ex-ante, then select divestments according to a rational hierarchy: first available cash, then cases where relative quality has weakened, then excessively overweight positions. High-quality winners should only be touched as a last resort. This logic meets the need for cash flow without adopting a structurally anti-momentum stance.
Conclusion
Skimming winning positions as soon as they reach +20%/+30%/+50%, while leaving the rest untouched is not a better discipline; in most cases, it is a rule that compresses winners, preserves mediocre positions for too long, and contradicts two massive facts of financial research: the extreme asymmetry of individual returns and the consistency of the momentum premium's performance.
Since the majority of stocks will not be big winners, long-term performance depends on a minority of exceptional positions. It is precisely this minority that a mechanical skimming rule prevents from playing its full role.
An investor who wants to maximize chances of outperforming the benchmark must therefore avoid selling simply because a position is positive. They must sell for an economic reason. And if they need liquidity, they must organize their withdrawals around cash, rebalancing overweights, and arbitraging weakened theses, not around an arbitrary capital gain threshold.
