Strategy Backtests

Break a swing high, wait for the retest, wait for a confirmation candle, enter on the continuation. It is in every price action course. We measured it on thirteen instruments and 5,836 setups, 2019 to 2021, before writing any strategy code. It loses on all thirteen, at every profit target from 1R to 3R. And the confirmation candle, the part that is supposed to be the discipline, costs money.

The Silver Bullet is the most specific promise in the ICT canon: a one-hour window, a particular gap, and win rates quoted between 70 and 90 percent. We measured all three published windows on six markets, three US indices plus EUR/USD, GBP/USD and gold, 2019 to 2021, before writing any strategy code. Across 2,200 setups it wins 36.1% of the time and loses 0.24R per trade. The FX pairs, which its own sources call the most widely traded for this setup, lose more than twice as much as the indices.

Quarterly Theory splits the trading day into four six-hour quarters and says the second one manufactures the day's high or low. We measured that on three FX majors, three US indices and gold, 2019 to 2021, before writing any strategy code. Q2 holds the extreme 16.6% of the time against the 25% you get from chance, and every one of the seven markets lands below chance. Trading the setup loses 0.06R per trade across 2,162 trades, and the cost-free drift runs 0.14R against the claim.

A published gold strategy came with a spectacular backtest. We retested the same rules on seven years of tick data with real costs, swept the complete parameter grid, and gave the survivors one shot at four unseen years. The edge is real. It is also five times smaller than advertised, and half of it lives in a single year.

Every prop-firm guru teaches the London-open failed breakout fade. We measured 400 of them on GBP/USD tick data with the real spread. The snap-back exists, pays about 1.21 pips gross, and costs 1.6 pips to trade. The pattern is real; the profit is not.

Everyone posts the 9:30 candle. We tested it on three years of 1-minute data for all three US indices, in-sample only, before writing a line of EA code. A close beyond the opening range doesn't continue in either direction, on any of them. The only positive drift is being long a market that was rising.

The FX session cycle is documented in top journals: currencies fall during their own trading hours. We measured it on EURUSD tick data. The European leg still works, at 0.75 pips a trade. Costs are 0.7.

Trend following works because of breadth, say Man Group and AQR: many mediocre streams, one good portfolio. We ran the experiment with the six markets a retail account actually has. 58 of 60 configurations lost money.

A published BTC seasonality earns 33%/yr on exchange data. On CFD pricing, every configuration we tested lost money before commission. The spread is the whole story, and we measured it from raw ticks.

Before writing a line of code for a carry strategy, we read IC Markets' real swap rates for eight candidate pairs. The broker's cut shaved the fat interest gaps down to pennies, and the fattest pair of all is one you are not allowed to open.

First run of our pre-registered 5-year slow-trend window: EURJPY channel breakouts are mildly real, never validation-grade, and the filter that helped Bitcoin made the carry cross worse.

Intraday time-series momentum is documented in equities and RUB-USD. On post-2019 EURUSD, the best of 48 configurations made $371 in three years. A clean transfer-test failure, with costs ruled out.

A filtered Donchian breakout on gold claims PF 1.85 over 28 years, costs included. Our grid tops out at a 1.14 profit factor over 104 trades, improving monotonically as we slowed it down. Where the edge lives, no gate can follow.

We transferred one of the most replicated mean-reversion strategies from daily equities to gold H1 and optimized it on three years of tick data with real costs. The optimizer found nothing, and the reason why is a lesson in edge geometry.