QTUM Bollinger Bands Strategy (1h) - Backtest Results
Price Action & Trades
Recent Trade History (Live Proof)
| Entry Date | Exit Date | Type | Entry Price | Exit Price | Profit/Loss Ratio |
|---|---|---|---|---|---|
| Jan 22, 14:00 | Jan 27, 00:00 | Long | $1.2910 | $1.3000 | +0.7% |
| Jan 20, 08:00 | Jan 21, 03:00 | Long | $1.3450 | $1.3630 | +1.34% |
| Jan 18, 01:00 | Jan 19, 19:00 | Long | $1.4710 | $1.3880 | -5.64% |
| Jan 15, 03:00 | Jan 16, 21:00 | Long | $1.5000 | $1.4450 | -3.67% |
| Jan 11, 20:00 | Jan 13, 13:00 | Long | $1.4510 | $1.4200 | -2.14% |
| Jan 7, 14:00 | Jan 10, 08:00 | Long | $1.4610 | $1.5110 | +3.42% |
| Dec 30, 00:00 | Dec 31, 07:00 | Long | $1.2740 | $1.3600 | +6.75% |
| Dec 28, 18:00 | Dec 29, 07:00 | Long | $1.2680 | $1.3380 | +5.52% |
| Dec 25, 10:00 | Dec 27, 11:00 | Long | $1.2380 | $1.2820 | +3.55% |
| Dec 21, 01:00 | Dec 24, 22:00 | Long | $1.2810 | $1.2610 | -1.56% |
Equity Curve
AI Deep AnalysisPowered by algorithmic insights
The 53.85% win rate is within expected range for Bollinger Bands algorithms. Focus shifts to risk-reward optimization.
Low profit factor (1.04) indicates potential parameter optimization is needed for QTUM.
High signal frequency (26 trades) suits active traders seeking regular QTUM engagement.
Compound growth strategy: reinvest 25% of profits into position size.
QTUM liquidity levels support clean Bollinger Bands execution without significant slippage impact.
The algorithm capitalizes on QTUM's characteristic volatility patterns on the 1h timeframe.
Performance Metrics
See Live Signal
Real-time technical analysis
View the current Bollinger Bands signal for QTUM with live market data, AI analysis, and trading recommendations.
About The Bollinger Bands Strategy
Backtest Methodology
Key Takeaways
- Clear rules-based system for QTUM.
- Bollinger Bands is beginner-friendly indicator.
- 1h gives time to analyze before action.
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