QTUM Supertrend Strategy (1h) - Backtest Results
Price Action & Trades
Recent Trade History (Live Proof)
| Entry Date | Exit Date | Type | Entry Price | Exit Price | Profit/Loss Ratio |
|---|---|---|---|---|---|
| Dec 27, 11:00 | Jan 19, 00:00 | Long | $1.2820 | $1.3410 | +4.6% |
| Dec 13, 01:00 | Dec 21, 13:00 | Long | $1.5120 | $1.2410 | -17.92% |
| Dec 9, 15:00 | Dec 12, 15:00 | Long | $1.4930 | $1.3980 | -6.36% |
| Dec 2, 15:00 | Dec 7, 14:00 | Long | $1.4930 | $1.3820 | -7.43% |
Equity Curve
AI Deep AnalysisPowered by algorithmic insights
With only 25% winners, this is an outlier-hunting strategy. The few wins must cover many small losses.
At 0.12x, transaction costs and slippage could erode gains. Factor in realistic trading costs.
The limited 4 sample size suggests viewing this as indicative rather than conclusive.
Consider testing Bollinger Band periods of 18-22 candles for potential QTUM optimization.
Volatility-adjusted sizing: reduce position size when QTUM ATR exceeds 150% of average.
Shorter timeframes show more signals but lower win rates. 1h is the sweet spot.
Performance Metrics
See Live Signal
Real-time technical analysis
View the current Supertrend signal for QTUM with live market data, AI analysis, and trading recommendations.
About The Supertrend Strategy
Backtest Methodology
Key Takeaways
- Supertrend generates clear entry/exit signals.
- No parameter optimization needed for QTUM.
- Robust across multiple market regimes.
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