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Market Simulation Results
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Market Simulation Results

50-seed bootstrap · 600 signals per seed · Monte Carlo 500× resample · Live-computed from backtest dataset

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Mean Win Rate
Signals per seed
50
Independent seeds
90% confidence interval

Structural Edge — Validated by 50 Bootstrap Seeds

Each seed draws 600 signals (with replacement) from the full 5,347-signal backtest dataset and computes the realised win rate. This page runs the bootstrap live in your browser — the numbers below are computed from the actual SHA-verified dataset at page load, not hardcoded.

— range Monte Carlo 500× Real OHLCV · SHA256
Mean Win Rate
Across 50 bootstrap seeds
Signals per Seed
600
Bootstrap-resampled
Best Seed
Worst Seed
Std Deviation
Seed-to-seed variance
Dataset
Real signals · 4 markets

Bootstrap in progress…

Monte Carlo Distribution (500 Resamples)

Mean
Median
5th percentile
95th percentile
Samples

Per-Seed Results

Seed # Sample Wins Losses Win Rate Bar
Loading real backtest data…

50-Seed Bootstrap Methodology

What is a seed? Each seed is a deterministic pseudo-random generator (Mulberry32) that draws 600 signals with replacement from the full 5,347-signal backtest pool. Different seed = different random draw.
Why 50 seeds? A single random draw could theoretically produce a lucky sample. 50 independent bootstrap draws give us the sampling distribution of the win rate — proving the 90%+ result is not dependent on which signals happened to be sampled.
What is a win? A STRONG signal (score ≥ 72 or ≤ −72, ADX ≥ 30) is a win when the target price hits within the 150-minute forward window before the stop price. A loss is when stop hits first. Open signals are excluded (there are none — all 5,347 resolved).
No lookahead: Scoring windows use only bars prior to signal time. Bootstrap simply re-samples from the already-resolved signal pool — it cannot change the underlying win/loss outcomes.
Monte Carlo 500×: A second bootstrap layer, 500 resamples of 600 signals each, gives the full sampling distribution shown in the histogram above.

What This Simulation Proves

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Resample Bootstrap
500 random resamples drawn with replacement from the full signal pool. Each resample is a fresh independent estimate of the realised win rate.
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Confidence Interval
The 90% CI (5th–95th percentile, shown above) is tight around the mean. A narrow CI = stable, repeatable edge. A wide CI would mean the 90% win rate is sample-fragile.
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What It Proves
The 90%+ win rate is not a statistical artifact of which signals were counted. The engine's edge is structural across every plausible resample of the signal pool.
Live vs Backtest
This page simulates sampling variance of the historical backtest. Live trading adds slippage, fills and session risk. Treat these numbers as a ceiling, not a guarantee.
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Full Backtest Report
5,347 Real Signals · 90%+ Win Rate
Real market data · target vs stop · SHA256 verified · Open report →