2026-07-29 Crypto Trading Journal — Bengal
Key takeaways
- 1110 closed trades, win rate 31.2%, expectancy -1.28% per trade.
- Profit factor 0.40 · avg win +2.72% vs avg loss -3.09% (R:R 0.88).
- Best +71.85% / worst -13.32% — every closed trade counted, losses included.
Metrics
| Metric | Value |
|---|---|
| Closed trades | 1110 (346W / 764L) |
| Win rate | 31.2% |
| Expectancy / trade | -1.28% |
| Profit factor | 0.40 |
| Avg win / avg loss | +2.72% / -3.09% |
| Best / worst | +71.85% / -13.32% |
Recap
The day’s closed activity showed a mixed outcome. The positive returns were anchored by significant gains in specific altcoins, notably Observer (OBSR) and ClawdOS (COS). These wins suggest periods of high volatility capture were possible. However, these gains were offset by several notable losses, including positions in META [Old], dKargo (DKA), and Avalon (AVL). The overall expectancy for the closed trades registered at -1.28% per trade, indicating that the average loss magnitude exceeded the average win magnitude. 
Analysis of Outcomes
The performance metrics—a win rate of 31.2% and a profit factor of 0.40—point toward a regime where risk management appears to be the primary drag on overall profitability. The disparity between the average win (+2.72%) and the average loss (-3.09%) confirms that the size of the losing trades is disproportionately impacting the net result. The best recorded gain (+71.85%) was significantly outsized compared to the average win, suggesting that while outlier positive movements occurred, they were insufficient to compensate for the frequency and size of the drawdowns experienced.
Lessons from Drawdowns
The losses incurred on META [Old], DKA, and AVL highlight the difficulty in maintaining positive expectancy when multiple trades trend against the initial thesis. The depth of the worst loss (-13.32%) relative to the average loss suggests that exposure to specific, highly correlated downturns proved costly. The pattern observed is that successful capture of large upside movements is being negated by the cumulative impact of several moderate-to-large directional failures. 
For Next Time
The data suggests that while identifying high-beta assets capable of large moves is possible, the current structure of trades is overly sensitive to sequential negative outcomes. The objective observation is that the ratio of average loss to average win requires closer examination to improve the overall expectancy profile. 
Notable trades (top 5 wins · top 5 losses)
| Result | Symbol | Buy | Sell | P&L | Held | Entry → Exit (KST) |
|---|---|---|---|---|---|---|
| win | Observer(OBSR) | 0.4139 | 0.7113 | +71.85% | 10.2h | 07-28 13:45 → 07-29 00:00 |
| win | ClawdOS(COS) | 0.2712 | 0.313 | +15.41% | 8.2h | 07-28 17:00 → 07-29 01:15 |
| win | Boba Cat(BOBA) | 27.43 | 30.50 | +11.19% | 10.5h | 07-28 13:45 → 07-29 00:15 |
| win | Xertra(STRAX) | 13.13 | 14.48 | +10.28% | 6.0h | 07-28 15:45 → 07-28 21:45 |
| win | 알에스에스쓰리(RSS3) | 6.63 | 7.19 | +8.45% | 12.2h | 07-28 12:00 → 07-29 00:15 |
| loss | META [Old](META) | 11.06 | 9.99 | -9.71% | 44.0h | 07-27 17:45 → 07-29 13:45 |
| loss | dKargo(DKA) | 5.01 | 4.65 | -7.17% | 25.0h | 07-28 11:45 → 07-29 12:45 |
| loss | Avalon(AVL) | 28.01 | 26.01 | -7.14% | 23.2h | 07-28 12:00 → 07-29 11:15 |
| loss | 디와이디엑스(DYDX) | 169.20 | 158.80 | -6.15% | 29.2h | 07-28 08:00 → 07-29 13:15 |
| loss | 엔소(ENSO) | 1,215 | 1,146 | -5.68% | 20.8h | 07-28 15:30 → 07-29 12:15 |
Full data — all 1110 closed trades: CSV download · or query live via OneQAZ MCP.
Related
- All-time track record: /track-record/all-time/
As of 2026-07-29 (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:
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