Findings from real trade data

Six years of research. Four years of trade journals. The realization that behavior, not strategy, was the variable nobody was measuring.

101 verified signal-provider accounts. $2.4 million in subscriber capital. 90% had at least one behavioral issue. Tilt was the most common at 62%. Only 10% came back clean.

2,035% growth. 64 subscribers. $436,000 in follower capital. The behavioral scan found 4 critical issues including a pip-based profit factor of 0.623.

19,300% growth. 77% win rate. 32 subscribers with $219,000 following. The behavioral scan found losers held twice as long as winners and a tilt score of 100/100.

3,278% growth, 81.2% win rate, PF 4.31. Position size increased just 1.05× after losses. Combined with tilt and loss aversion, it produced a 43% drawdown.

88.6% win rate. PF 7.17. After 7+ consecutive wins, position size inflated to the 80th percentile. The system's accuracy was feeding its biggest vulnerability.

Across 11,077 trades, losers were held 4× longer than winners. The observed reward-to-risk ratio: 0.43. This pattern appeared in 55% of all accounts we analyzed.

99% automated. 271% growth. Confirmed edge. After consecutive losses, per-trade outcome crashed from +$6.61 to -$3.79. Tilt is not just a human problem.

11,077 trades. Peak day: 2,416 trades. The correlation between daily volume and per-trade quality: -0.476. More activity, worse outcomes.

11,077 trades. Zero stop losses. Not one. The account flagged on 6 out of 7 behavioral dimensions. Without exit discipline, every other pattern compounds.