We graded 13 famous trading strategies on 6 years of data. All 13 failed.
Every trading book, YouTube channel, and Discord server teaches the same classics: RSI mean-reversion, the golden cross, Bollinger bands, MACD momentum, Turtle trading. They're taught because they're intuitive and they backtest beautifully - if you let yourself be a little dishonest about how you backtest.
We run a strategy-grading engine, so we did the obvious thing: we took 13 of the most widely taught strategies and graded them all the same way we grade everything:
- 6 years of crypto data across 10+ major pairs
- A strict out-of-sample split: parameters are chosen on the training window only; the grade comes exclusively from data the strategy never saw
- Real costs: taker fees and slippage modeled on every fill
- Five pass/fail gates: positive out-of-sample expectancy, clears the cost hurdle, robust across assets, survivable drawdown, and not overfit
Here's the honest scoreboard:
| Strategy | Gates passed | Net/trade (after costs) | OOS trades | Win rate |
|---|---|---|---|---|
| ADX trend rider | 4/5 | +10.7 bp | 4,235 | 37.8% |
| Bollinger breakout | 4/5 | +3.8 bp | 6,382 | 36.8% |
| MACD momentum | 3/5 | +3.5 bp | 8,345 | 37.0% |
| Momentum (rate of change) | 2/5 | +1.6 bp | 5,944 | 36.6% |
| Golden cross | 2/5 | +0.7 bp | 8,126 | 37.6% |
| Ichimoku cloud | 1/5 | +1.4 bp | 7,134 | 36.8% |
| Connors RSI-2 | 1/5 | −3.7 bp | 12,141 | 47.8% |
| Turtle trading | 1/5 | −8.0 bp | 7,054 | 35.9% |
| Bollinger reversion | 1/5 | −9.7 bp | 6,946 | 49.0% |
| Stochastic reversion | 1/5 | −13.5 bp | 9,313 | 44.3% |
| RSI mean-reversion | 1/5 | −19.8 bp | 4,629 | 37.8% |
| Quiet dip buyer | 1/5 | −28.3 bp | 1,439 | 36.3% |
| CMF money flow | 0/5 | −5.4 bp | 3,615 | 33.3% |
Zero out of thirteen passed all five gates.
Three things worth actually learning from this
Win rate is a trap. The two highest win rates on the board - Bollinger reversion at 49% and Connors RSI-2 at 47.8% - both lose money after costs. Meanwhile the closest thing to a passing strategy, the ADX trend rider, wins only 37.8% of its trades. A high win rate with small wins and large losses is how a strategy feels good while bleeding out. (This is personal: the founder ran a live bot with a 78% win rate that turned out to be flat over 6 years. The win rate was hiding a 1:0.34 reward-to-risk.)
Trend-following beat mean-reversion - everywhere. Look at the top of the table: ADX trend rider, Bollinger breakout, MACD momentum. Now look at the bottom: RSI reversion, stochastic reversion, dip buying. On this data, every strategy built on "it went down, so buy the bounce" lost money after fees, and every strategy that got close to passing was riding moves, not fading them.
"Close to passing" is still failing. Two strategies passed 4 of 5 gates. That sounds encouraging until you remember what the fifth gate was protecting you from. A strategy that isn't robust across assets, or that only worked because its parameters were tuned to the test period, will do to your real money exactly what it couldn't be caught doing in a sloppy backtest.
Why fees change everything
Most published backtests of these classics quietly assume zero or near-zero trading costs. At thousands of trades over six years, even a few basis points per trade compounds into the difference between "works" and "wipes out." Connors RSI-2 is the cleanest example: with 12,141 out-of-sample trades, it's gross-positive and net-negative. The strategy isn't wrong about the market - it's just too small an edge to pay its own way.
Check the work
Every grade above has a public verify page with the full per-asset breakdown - the methodology is the same for all 13, and the inputs can't be edited after the fact: tessen.ai/strategies
And if you have a strategy of your own - from a book, a video, or your own head - you can run it through the same five gates free, no signup: tessen.ai/grade. Fair warning, most ideas fail. Knowing that before you fund an account is the entire point.
Nothing here is financial advice. A failed grade on historical data doesn't prove a strategy can never work; a passed one wouldn't guarantee it keeps working. These are measurements, not predictions.
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