All 8 of 8 equal calendar periods generated positive returns across the backtest horizon. No losing period detected. Return consistency CV of 0.4 confirms profitability is spread evenly, not concentrated in a single regime window. This score measures temporal robustness — a strategy that only profits in one or two periods may be regime-dependent rather than exhibiting a repeatable edge.

T-statistic of 4.16 exceeds the 99% two-tailed significance threshold of 2.576. (p = 0) Probability of results arising by chance is below 0.1%. The edge is statistically real given this 325-trade sample. This test applies a Welch t-test on the profit distribution and requires the mean return to be significantly different from zero.

Maximum drawdown of 8.7% with an average episode depth of 3.0%. The median recovery speed is 5.5 days per 1% of drawdown. 44 drawdown episodes were detected. No single episode dominates the overall drawdown profile, indicating consistent rather than event-driven risk. This test scores three components: max DD depth (50%), average episode depth (30%), and recovery quality in days per 1% of DD (20%).

Compound annual growth rate of 29.3% against 8.7% maximum drawdown. Calmar ratio of 3.4× meets the professional benchmark range of 3–5×. CAGR is computed using true compound growth (end equity / start equity)^(1/6.35 years), not simple annualisation. Capital efficiency rewards strategies that generate high risk-adjusted returns relative to their worst historical loss.

Rolling expectancy regression slope is positive (normalised +1.13), indicating the edge has strengthened over the backtest horizon. Second-half expectancy exceeds first-half by 95% (ratio 1.95). Profit factor across four quartiles (2.043, 1.693, 2.06, 1.799) shows a mild downward drift (normalised slope -0.06). Win rate trends upward across quartiles (normalised slope +0.11). This test detects whether a strategy's edge is eroding over time — a critical check for curve-fitted systems that perform well historically but deteriorate as market conditions evolve.

Top 10% of winning trades account for 32.7% of total profit — above the 30% ideal-diversification threshold but below the 50% concentration-risk threshold. The largest single winner represents 2.5% of total profit, confirming no individual trade disproportionately sustains the overall result. Profit distribution is scored on two components: top-decile share (80%) and single largest winner share (20%). A well-distributed profit profile indicates genuine repeatable edge rather than lottery-dependent returns.

Ulcer Index of 3.0% represents minimal cumulative drawdown pain. Max DD: 8.7%, avg DD: 2.11%, time underwater: 65.8%. Unlike maximum drawdown which captures a single worst point, the Ulcer Index integrates both depth and duration of all underwater periods — a UI below 5% indicates drawdowns are shallow, brief, and recover quickly.

325 trades over 6.3 years exceeds the academic minimum of 125 trades. MinTRL (minimum track record length) statistic: 30. Confidence factor applied to all other tests: 1. Sample adequacy is the foundational test — a backtest with insufficient trades cannot produce statistically valid conclusions regardless of how impressive the individual metrics appear.

Lag-1 autocorrelation of 0.057 (lag-2: -0.093) — no meaningful serial dependence. Returns are effectively independent. No martingale signature or hidden clustering pattern detected. Significant autocorrelation can indicate position-sizing escalation or regime-dependent behaviour that inflates backtest results.

Maximum consecutive losing streak of 6 trades against a statistically expected maximum of 6.6 (ratio 0.9×). Loss clustering ratio of 1.04 — losses are not grouping more frequently than random distribution predicts. Worst streak required approximately 15 average wins to fully recover (damage ratio 7.2×). This test checks four dimensions: observed vs expected streak length (30%), loss clustering (25%), worst streak damage (25%), and recovery speed (20%).

95th-percentile loss of $778.16 is 1.69× the average win of $461.71 — a healthy ratio indicating tail losses are not catastrophically larger than typical wins. Average loss: $340.15. Single largest loss ($846.09) is 1.09× above the P95 level — no structural outlier. This test uses the 95th-percentile loss rather than the single largest loss as the primary metric, making the score more robust to one-off broker anomalies while still flagging structural outliers separately.

Under a 10% uniform execution degradation scenario (wins reduced 10%, losses increased 10%), per-trade expectancy retains 0.67× of its backtest level. Original expectancy: $126.17 → degraded: $85.08 (32.6% impact). Strategy remains profitable under this stress test. At 0.371R base expectancy, the strategy retains meaningful cushion against real-world execution costs.

Winners are held 1.3× longer than losers on average (winners: 13.4h, losers: 10.3h). This is a positive pattern — the strategy allows profitable trades to run while cutting losses relatively quickly. Discipline tier: GOOD. Median ratio: 0.9×. At the current 0.371R expectancy, this does not materially impact performance.