AI Trading Report
Session 030 · BTCUSD (Bitcoin vs US Dollar) · M5 · Backtest · PracticeSimulator_rcm · Tradexfin Limited
Statistical Summary
| Trading period | 2026-08-14 00:22:40 – 2026-08-14 20:21:20 |
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| Total trades | 14 |
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| Total profit / loss | −82.50 USD |
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| Winning trades / total winning profit | 8 / +109.29 USD |
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| Losing trades / total losing loss | 6 / −191.79 USD |
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| Win rate | 57.1% |
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| Profit Factor | 0.57 |
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| Average risk-reward | 0.43 |
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| Average profit / loss | +13.66 / −31.97 USD (net −5.89 per trade) |
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| Average price move per trade | 395.8 points |
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| Maximum drawdown (amount) | 152.80 USD |
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| Maximum drawdown (%) | ≈ 217% of peak session profit (account balance unknown) |
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Charts
1. Cumulative Profit
Profit peaked at +70.30 after trade 10, then the final cluster erased everything down to −82.50.
2. Trade-wise Profit
Wins are small and frequent; the 4 losses at the end are individually larger and dominate the result.
3. Profit Distribution
Wins cluster in the +5 to +15 band; losses spread over a wider negative range.
4. Win / Loss Breakdown
Win rate 57.1%, but the losing side carries 2.3x the average size of a win.
5. Maximum Drawdown per Trade
Drawdown stays at zero through trade 10 and then accelerates through the final losing cluster.
AI Judgment
| Win Rate Stability | C 57.1% win rate is decent, but results come in extreme streaks (7 wins / 4 losses), so the win rate is not stable over time. |
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| Volatility Adaptability | D Cluster A captured a strong downtrend, but cluster B entered SELL right before an upward reversal. No volatility-regime adaptation was observed. |
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| Risk Management | D Average loss (31.97) is 2.3x average win (13.66); one cluster (−152.80) exceeded the session's entire profit. |
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| Overall Evaluation | D A profitable pattern in trends, but risk concentration makes the session net-negative. |
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Overall Comment: This session shows a strategy that wins often but loses bigger. The core issue is not the entry logic's hit rate — it is that a single cluster of four losses was allowed to erase the whole day's profit. Fixing loss concentration and the risk-reward balance should be the priority before any further refinement.
Issues and Improvement Suggestions
1. Uncapped cluster risk
- Issue: 4 trades in one cluster lost 152.80, erasing the +70.30 profit from the previous 10 trades.
- Details: All cluster positions shared one entry decision and one direction; when that decision was wrong, every position lost together.
- Suggestion: Add a per-cluster or per-day loss limit that stops new entries and closes remaining positions after a fixed adverse move. Test it in the backtester.
2. Unfavorable risk-reward
- Issue: Average loss (31.97) is 2.3x the average win (13.66); Profit Factor is 0.57.
- Details: The largest-lot segments are closed first and absorb the biggest adverse moves, while winners are mostly the small lots.
- Suggestion: Cut losses earlier, extend profit targets, or reduce lots on the most exposed early segments to bring the average risk-reward toward 1.0 or better.
3. Entries into reversal zones
- Issue: The 17:36 cluster entered SELL at ~62,752 just before price bottomed and reversed upward to ~63,250.
- Details: No filter distinguishes trend continuation from trend exhaustion before re-entering hours after a successful cluster.
- Suggestion: Add a trend/momentum confirmation filter and skip re-entries near fresh extremes or after a long winning streak.
Notes on units: P&L figures are in USD. BTCUSD is quoted to 2 digits; 1 point = 0.01 USD and 1 lot = 1 BTC (contract size 1). Average price move is expressed in points. Maximum drawdown % is relative to the peak session profit because the starting account balance is not available in the export.