{"slug": "we-graded-13-famous-trading-strategies-on-6-years-of-data-all-13-failed", "title": "We graded 13 famous trading strategies on 6 years of data. All 13 failed.", "summary": "Tessen.ai graded 13 famous trading strategies on six years of crypto data and found that all 13 failed to pass all five pass/fail gates. The best performer, the ADX trend rider, passed only four of five gates and netted just 10.7 basis points per trade after costs. The results highlight that win rate is a trap, trend-following outperformed mean-reversion, and trading costs turn marginal edges into losses.", "body_md": "([https://tessen.ai/strategies](https://tessen.ai/strategies))\n\nEvery 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.\n\nWe 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 —\n\n6 years of crypto data across 10+ major pairs\n\nA strict out-of-sample split: parameters are chosen on the training window only; the grade comes exclusively from data the strategy never saw\n\nReal costs: taker fees and slippage modeled on every fill\n\nFive pass/fail gates: positive out-of-sample expectancy, clears the cost hurdle, robust across assets, survivable drawdown, and not overfit\n\nHere's the honest scoreboard:\n\nStrategy Gates passed Net/trade (after costs) OOS trades Win rate\n\nADX trend rider 4/5 +10.7 bp 4,235 37.8%\n\nBollinger breakout 4/5 +3.8 bp 6,382 36.8%\n\nMACD momentum 3/5 +3.5 bp 8,345 37.0%\n\nMomentum (rate of change) 2/5 +1.6 bp 5,944 36.6%\n\nGolden cross 2/5 +0.7 bp 8,126 37.6%\n\nIchimoku cloud 1/5 +1.4 bp 7,134 36.8%\n\nConnors RSI-2 1/5 −3.7 bp 12,141 47.8%\n\nTurtle trading 1/5 −8.0 bp 7,054 35.9%\n\nBollinger reversion 1/5 −9.7 bp 6,946 49.0%\n\nStochastic reversion 1/5 −13.5 bp 9,313 44.3%\n\nRSI mean-reversion 1/5 −19.8 bp 4,629 37.8%\n\nQuiet dip buyer 1/5 −28.3 bp 1,439 36.3%\n\nCMF money flow 0/5 −5.4 bp 3,615 33.3%\n\nZero out of thirteen passed all five gates.\n\nThree things worth actually learning from this\n\nWin 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.)\n\nTrend-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.\n\n\"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.\n\nWhy fees change everything\n\nMost 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.\n\nCheck the work\n\nEvery 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\n\nAnd 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.\n\nNothing 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.", "url": "https://wpnews.pro/news/we-graded-13-famous-trading-strategies-on-6-years-of-data-all-13-failed", "canonical_source": "https://dev.to/tessen/we-graded-13-famous-trading-strategies-on-6-years-of-data-all-13-failed-1aci", "published_at": "2026-07-13 20:27:47+00:00", "updated_at": "2026-07-13 20:45:46.511411+00:00", "lang": "en", "topics": ["machine-learning", "developer-tools"], "entities": ["Tessen.ai", "ADX trend rider", "Bollinger breakout", "MACD momentum", "Golden cross", "Ichimoku cloud", "Connors RSI-2", "Turtle trading"], "alternates": {"html": "https://wpnews.pro/news/we-graded-13-famous-trading-strategies-on-6-years-of-data-all-13-failed", "markdown": "https://wpnews.pro/news/we-graded-13-famous-trading-strategies-on-6-years-of-data-all-13-failed.md", "text": "https://wpnews.pro/news/we-graded-13-famous-trading-strategies-on-6-years-of-data-all-13-failed.txt", "jsonld": "https://wpnews.pro/news/we-graded-13-famous-trading-strategies-on-6-years-of-data-all-13-failed.jsonld"}}