T-statistic of 5.46 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 1001-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 13.6% with an average episode depth of 2.5%. The median recovery speed is 2.2 days per 1% of drawdown. 81 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%).

Rolling expectancy regression slope is positive (normalised +0.89), indicating the edge has strengthened over the backtest horizon. Second-half expectancy exceeds first-half by 101% (ratio 2.01). Profit factor across four quartiles (1.389, 1.342, 1.544, 1.841) trends upward overall (normalised slope +0.31). Win rate trends upward across quartiles (normalised slope +0.14). 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.

Win rate variance across weekdays falls within acceptable bounds. No structurally unprofitable weekday detected. Profit factor log-variance of 0.1632 and day-of-week variance of 12.5018 indicate edge quality does not fluctuate meaningfully by session day. This test checks whether the strategy's edge is consistent across all trading sessions or is heavily dependent on specific days or conditions.

Top 10% of winning trades account for 26.5% of total profit — well within the 30% ideal-diversification threshold. The largest single winner represents 0.8% 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 2.4% represents minimal cumulative drawdown pain. Max DD: 13.7%, avg DD: 1.65%, time underwater: 67.0%. 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.

1048 trades over 6.7 years exceeds the academic minimum of 175 trades. MinTRL (minimum track record length) statistic: 111. 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 0.033 (lag-2: 0.022) — 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.

Under 1,000 permutation shuffles of the exact trade sequence, the 95th-percentile maximum drawdown reaches 18.4% — a 1.4× expansion from the 13.7% historical figure. 99th percentile: 22.1%. A ratio below 2.0× confirms the strategy does not rely on a particularly favourable trade ordering. This test measures whether the backtest drawdown is structurally representative or a statistical artefact of a lucky sequence of trades.

95th-percentile loss of $438.94 is 2.77× the average win of $158.61 — a healthy ratio indicating tail losses are not catastrophically larger than typical wins. Average loss: $180.08. Single largest loss ($773.52) is 1.76× 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.

Block-bootstrap Monte Carlo (2,000 simulations, block size 15 preserving serial structure, AC lag-1: 0.053) produces a survival rate of 100.0% across all simulations. Coefficient of variation: 0.175. MC DD envelope — P50: 13.3%, P95: 26.6%. No position-scaling pattern detected — the strategy applies approximately uniform lot sizing regardless of recent outcomes. Block bootstrap preserves the serial correlation structure of returns (unlike naive IID resampling), producing more realistic stress scenarios.

Losers are held 0.91× longer than winners on average (winners: 7.6h, losers: 6.9h). Hold time ratio is within acceptable bounds. Discipline tier: GOOD. Median ratio: 0.61×. At the current 0.195R expectancy, this does not materially impact performance.