Strategy Backtests

A gold breakout system on r/algotrading showed +188% in 18 months, with a profit factor of 1.74. Its author asked if it holds up outside that window. We ran it on 2019 to 2021 real-tick data with full costs. At its own speed of about three trades a day, every matching setting lost 76% to 97% of the account.

We tested the Turnaround Tuesday rule on the S&P 500, Dow and Nasdaq 100. With one lot on every trade, it made about six times its costs. With normal position sizing, the same rule lost money.

People say the ICT Silver Bullet wins 70 to 90% of the time. We tested all three of its one-hour windows on six markets (three US indices, EUR/USD, GBP/USD and gold) from 2019 to 2021, before writing any strategy code. In 2,200 setups it won 36.1% of the time and lost 0.24R per trade. EUR/USD and gold, which its own teachers recommend, lost more than the indices.

Price breaks a swing high, comes back to test it, a confirmation candle forms, and you enter. Every price action course teaches this. We measured it on thirteen markets 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.

Quarterly Theory splits the trading day into four parts of six hours each. It says the second part (Q2) makes the day's high or low. We checked this on three FX majors, three US indices and gold, 2019 to 2021, before we wrote any strategy code. Q2 holds the day's high or low only 16.6% of the time. Chance alone gives 25%, and all seven markets are below chance. Trading the setup loses 0.06R per trade over 2,162 trades. With no costs at all, the price still moves 0.14R against the claim.

Many trading teachers show the London-open failed breakout trade. We measured 400 of them on GBP/USD tick data with the real spread. The price does move back, by about 1.21 pips before costs. But each trade costs 1.6 pips. The pattern is real, but there is no profit.

Everyone posts the 9:30 candle. We tested it on three years of 1-minute data for all three big US indices, before writing any EA code. When price closes outside the opening range, it does not keep going in either direction, on any index. The only profit came from buying a market that was going up.

Before writing any code for a carry strategy, we read IC Markets' real swap rates for eight pairs. After the broker's cut, the big interest gaps became very small. And the pair that pays the most is one you are not allowed to open.

This is the first test with our new 5-year test period for slow trend strategies. EURJPY channel breakouts have a small real edge, but never enough to pass. The filter that helped Bitcoin made EURJPY worse.

Top research journals say a currency tends to fall during its own country's trading hours. We tested this on EURUSD tick data. The European part still works, at 0.75 pips per trade. But the cost is 0.7 pips.

Man Group and AQR say trend following works because it trades many markets. Each market is weak, but together they make a good portfolio. We tried this with the six markets a normal retail account has. 58 of 60 settings lost money.

A published Bitcoin pattern makes 33% a year on exchange data. We measured it again with a real broker's costs. The 22:00 UTC rule lost money, because there was almost no price move at that hour. When we timed it to the New York close, it made about 0.04% per trade.

Research shows intraday momentum in stocks and in RUB-USD. We tested it on EURUSD after 2019. The best of 48 settings made only $371 in three years. The idea failed on a new market, and trading costs were not the reason.

A gold breakout system with a trend filter claims a profit factor of 1.85 over 28 years, with costs. Our best test got 1.14 over 104 trades. Results got better each time we made the system slower. But the edge seems to live at a speed too slow for us to test properly.

We took a well-known strategy that works on daily stock charts and tested it on the 1-hour gold chart. We used three years of tick data with real costs. Every setting lost money, and the reason is simple: the wins are too small to pay the costs.

A gold strategy was published with a great backtest: +60% in 11 months. We tested the same rules on seven years of real data with real costs. The edge is real, but it is about five times smaller than the claim, and half of it came in one year.