PYTH RSI Strategy (4h) - Backtest Results
Price Action & Trades
Recent Trade History (Live Proof)
| Entry Date | Exit Date | Type | Entry Price | Exit Price | Profit/Loss Ratio |
|---|---|---|---|---|---|
| Jan 16, 08:00 | Jan 28, 04:00 | Long | $0.0655 | $0.0615 | -6.11% |
| Jan 12, 20:00 | Jan 14, 16:00 | Long | $0.0646 | $0.0705 | +9.13% |
| Dec 30, 16:00 | Jan 2, 20:00 | Long | $0.0583 | $0.0628 | +7.72% |
| Dec 5, 16:00 | Dec 21, 00:00 | Long | $0.0678 | $0.0600 | -11.5% |
| Nov 14, 16:00 | Dec 3, 08:00 | Long | $0.0937 | $0.0740 | -21.02% |
| Nov 3, 12:00 | Nov 7, 16:00 | Long | $0.0932 | $0.1118 | +19.96% |
| Oct 28, 16:00 | Nov 1, 20:00 | Long | $0.1128 | $0.1091 | -3.28% |
| Oct 16, 00:00 | Oct 19, 12:00 | Long | $0.1194 | $0.1151 | -3.6% |
| Oct 4, 12:00 | Oct 13, 12:00 | Long | $0.1515 | $0.1291 | -14.79% |
| Sep 23, 20:00 | Oct 2, 08:00 | Long | $0.1503 | $0.1605 | +6.79% |
Equity Curve
AI Deep AnalysisPowered by algorithmic insights
With only 40% winners, this is an outlier-hunting strategy. The few wins must cover many small losses.
Low PF (0.63) combined with this win rate makes the setup high-variance. Trade cautiously.
The 10 signals provide enough data for reliable backtesting while avoiding overtrading.
Kelly Criterion suggests minimal position sizing for this edge.
Order book analysis suggests PYTH has strong support/resistance levels aligning with RSI triggers.
Volatility clustering in PYTH may cause consecutive signals—beware of correlation between trades.
Performance Metrics
See Live Signal
Real-time technical analysis
View the current RSI signal for PYTH with live market data, AI analysis, and trading recommendations.
About The RSI Strategy
Backtest Methodology
Key Takeaways
- Minimum $500 account for micro positions on PYTH.
- 1% risk = $10 per trade on $1,000 account.
- Scale position size with account growth.
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