A regime-adaptive BTC strategy stayed positive across nearly every tested year, and the full 2018–2026 backtest reached 215% with a 22% max drawdown.
This video breaks down the exact BTC system logic, how it switches between trending and ranging conditions, and what the CoinQuant AI backtest actually showed year by year. I also point out a real exit-condition issue in the test so you can judge the results with the right amount of skepticism.
What you’ll see in this video:
→ The BTC one-hour strategy built and backtested in CoinQuant AI
→ How ADX acts as the regime filter between trend and range modes
→ The five classic indicators used in the system logic
→ The exact take profit and stop loss setup at 5.5% and 1.5%
→ Year-by-year backtest results from 2019 onward
→ The full-period result of 215% return with 22% max drawdown
→ Why one backtest detail may affect the exit accuracy
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🔗 Resources & Links:
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• Try CoinQuant For FREE: https://app.coinquant.ai/?ref=nZtzOwut
• My Algorithmic Trading Courses → https://codetradingcafe.com
• My Book: “Algorithmic Trading with Python” → https://a.co/d/6woMBHt
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If you want more AI trading builds and backtests, just tell me which asset I should test next.
#aitrading #machinelearning #trading #btc
▸ CHAPTERS
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0: 00 Profitable Every Year
1: 22 ADX Regime Switch
2: 05 Trend Entry Rules
4: 04 Range Mode Setup
5: 03 Exits And Platform Issue
6: 25 Performance Metrics Review
7: 55 Year By Year Backtests
11: 02 Full Period Results
12: 03 Strategy Takeaways