OneQAZ OneQAZ
← journal

2026-08-13 Crypto Trading Journal — Bengal

Key takeaways

  • 625 closed trades, win rate 37.1%, expectancy -0.89% per trade.
  • Profit factor 0.54 · avg win +2.80% vs avg loss -3.07% (R:R 0.91).
  • Best +17.11% / worst -10.38% — every closed trade counted, losses included.

Metrics

MetricValue
Closed trades625 (232W / 393L)
Win rate37.1%
Expectancy / trade-0.89%
Profit factor0.54
Avg win / avg loss+2.80% / -3.07%
Best / worst+17.11% / -10.38%

Recap

The day’s closed activity reflects a challenging risk profile. Out of 625 trades executed, the win rate settled at 37.1%, with an expectancy of -0.89% per trade. The profit factor of 0.54 suggests that realized losses are outpacing gains on average. While notable gains were recorded, such as Checkmate (+17.11%) and Intuition (+14.63%), these were offset by several significant drawdowns, including Lisk (-7.33%) and PolySwarm (-5.42%). The average win (+2.80%) was not sufficient to compensate for the average loss (-3.07%). Bengal

Analysis of Outcomes

The performance indicates that the magnitude of losses is currently outweighing the frequency and size of the wins. The disparity between the average win and average loss suggests that the risk taken on losing trades is disproportionately high relative to the returns captured on winning trades. The best recorded outcome (+17.11%) was substantial, but the cumulative effect of the negative expectancy points toward a need for structural adjustment in risk management. Bengal

Lessons from Drawdowns

The losses incurred on assets like Lisk and NCT highlight instances where market structure appeared to resist initial directional assumptions. These trades suggest that when volatility spikes against the prevailing bias, the downside capture can be deep, even when the initial setup appeared sound. The negative expectancy across the board underscores that the current execution regime is not generating positive expected value. Bengal

For Next Time

The data points toward a need to re-evaluate the risk parameters applied across the board. The spread between the best and worst single-trade outcomes is wide, indicating high variance in the outcomes captured. The focus moving forward must remain on maintaining a disciplined view of the overall risk-reward balance, acknowledging the current negative drift.

Notable trades (top 5 wins · top 5 losses)

ResultSymbolBuySellP&LHeldEntry → Exit (KST)
winCheckmate(CHECK)20.6924.23+17.11%9.2h08-12 14:45 → 08-13 00:00
winIntuition(TRUST)71.7782.27+14.63%35.5h08-12 00:30 → 08-13 12:00
win코티(COTI)13.2614.75+11.24%8.5h08-12 17:00 → 08-13 01:30
winFabric Protocol(ROBO)16.8518.20+8.01%4.0h08-12 22:15 → 08-13 02:15
winAllora(ALLO)396.40423.60+6.86%2.0h08-12 22:30 → 08-13 00:30
lossLisk(LSK)139.10128.90-7.33%1.0h08-12 22:15 → 08-12 23:15
lossPolySwarm(NCT)6.356.00-5.42%2.2h08-12 22:30 → 08-13 00:45
loss캡(CAP)79.9675.83-5.17%5.5h08-12 22:15 → 08-13 03:45
lossBubblemaps(BMT)25.6324.31-5.15%1.2h08-12 22:30 → 08-12 23:45
lossSideShift(XAI)9.138.68-5.00%30.5h08-12 00:00 → 08-13 06:30
_P&L distribution (300 meaningful trades): min -7.33% · P25 -3.57% · median -3.23% · P75 +0.19% · max +17.11%_

Full data — all 625 closed trades: CSV download · or query live via OneQAZ MCP.

Related


As of 2026-08-13 (KST).

Disclaimer: OneQAZ figures are paper-trading research, not investment advice. Past simulated performance does not predict future real-money results.

Three ways to see OneQAZ — this post is the synthesis layer: