September 2025 marks the first anniversary of StockHero’s Sigma Series stock trading strategies. From a debut 90% win rate, the Sigma Series strategies have steadily climbed to an average 95% win rate over the first year -evidence that the Sigma models adapt across various market conditions. The strategies withstood the following major events a) the August and September 2024 market corrections and the April 2025 market crash.
Within the lineup, Sigma Series Fast has been the star performer: it has never fallen below a 90% monthly win rate, peaked at a record 97%, and even through the April 2025 turbulence still netted 91% in winning trades.
How unusual is that in the world of automated trading? It’s important to separate win rate (hit rate) from overall profitability—because many elite quantitative styles are designed to win only modestly more (or even less) than half the time while relying on strong payoff ratios (risk-reward). For example, large-sample research on trend-following – one of the core algorithmic quantitative trading methodology – typically finds trade-level win rates around 40–45%; profitability comes from letting winners run and cutting losses quickly. Recent empirical work puts a representative trend-following program’s win rate near 43.9%, squarely in that range. (source: Longboard).
But, an under 50% win rate will not cut it for most of us. This is because not many of us can endure the punishing string of losses that can result from such a strategy.
In trading, two performance philosophies dominate:
Average win rate (≈50%) with a high reward-to-risk ratio – the classic model of trend-followers, discretionary traders, and many quantitative hedge funds.
High win rate (≈90%) with a moderate reward-to-risk ratio – the profile of strategies like StockHero’s Sigma Series.
On the surface, both can yield attractive returns. But in practice, they are not comparable, and the distinction has profound implications for traders and investors.
A system that wins only half the time – even if profitable overall – requires investors to endure long losing streaks. Quantitative hedge funds with ~50% hit rates rely on unbalanced gains: a single outsized winner must cover numerous small losses. This is rational in theory but emotionally punishing in reality. Consecutive losses erode investor confidence, leading to early redemptions or abandoning the strategy before it pays off.
By contrast, a 90% win rate strategy delivers consistent positive feedback, greatly reducing investor anxiety. Frequent wins smooth the equity curve, encouraging adherence and capital commitment – critical in compounding performance.
High win rate strategies like the Sigma Series demonstrate resilience across conditions. For example, even during April 2025’s volatility, stock trading bots that run on the Sigma Series Fast still delivered 91% winning trades. Such durability is rare in reward-risk-driven systems, which often falter in choppy market environments when their few “big winners” never materialize.
Even legends illustrate how rare very high monthly hit rates are. Public reporting on Renaissance Technologies’ Medallion fund shows only 17 losing months between January 1993 and April 2005—an extraordinary feat implying roughly ~88% positive months over that span, and still the exception that proves the rule. (source: Wikipedia)
Against this backdrop, Sigma Series Fast strategy’s record is notable not only for peak months (97%) but for durability: starting at 90%, grinding higher to a 95% first-year average, and holding ≥90% even in a stress month like April 2025.
In the field of automated stock trading, the Sigma Series’ consistently high win-percentage showcases its superior profile – one that speaks to careful risk controls, diversified signal design, and superb models across shifting market states.
