- Data used: latest 10,000 public fills from May 31, 2025 to Aug 9, 2025; older public fills may exist outside this audit because the source hit its cap.
- The sample is too small—two closed episodes over 70 days—to support conclusions about edge, consistency, or behavioural patterns.
- The account is down $11.06M in the data covered.
0xcb92c5988b1d4f145a7b481690051f03ead23a13
0xcb92...3a13 wallet audit
0xcb92...3a13 audit. -$11,060,271 realised trading PnL across 2 closed position cycles, using the latest 10,000 public fills from May 31, 2025 to Aug 9, 2025; older public fills may exist outside this audit.
The dollar PnL is the realised result from closed trades in the data covered. The percentage uses an inferred starting value (current account value -$11,060,271 minus closed trading PnL -$11,060,271 = starting estimate $11,060,271). This audit does not ingest a deposit or withdrawal ledger, so it can show that trades lost money, but it cannot prove whether the owner also moved funds in or out. Older fills may also exist outside the latest 10,000-fill window.
This is not a fixed last-week or last-month period. It is the actual span covered by the latest 10,000 public fills Hyperliquid exposed for this wallet. Because the public fill source hit its cap, older trades may exist but are not included here.
- Public fills
- 10,000
- Position cycles
- 2 closed, 1 open
- Limit
- latest 10,000 fills only
- The sample is too small to isolate strengths or weaknesses with confidence. Two trades is not a sufficient basis for pattern recognition.
- Both closed trades moved against the account without triggering stops or being exited early, suggesting either stops were not in place or were not respected.
- The second trade's notional size ($260M) was nearly double the first, and it carried no structural stop, indicating position management became more aggressive as losses accumulated.
Bottom line up front
Only the most recent public fills are visible, so this audit covers the data covered rather than full account history. The sample is too small—two closed episodes over 70 days—to support conclusions about edge, consistency, or behavioural patterns. The account is down $11.06M in the data covered. Both closed trades in ETH lost money: a long from 31 May to 9 July that bled $283k despite averaging down, followed by a short from 9 July to 9 August that lost $10.78M on a notional position of $260M. One open position remains.
What the data shows
The data covered spans 70 days and contains exactly two closed episodes, both in ETH. The first, opened 31 May at $2,473.14, was held for 952 hours and closed 9 July at $2,753.72 for a loss of $282,962. The position reached a notional size of $134M and carried a 3% structural stop. The trade was flagged for averaging down—capital was added into a losing position rather than cut.
The second trade opened immediately after on 9 July as a short, closed 9 August at $3,383.25 after 731 hours, and lost $10.78M. This position scaled to $260.7M notional—nearly double the first trade's size—and had no structural stop in place. No entry price is recorded, suggesting the position was built over time rather than entered at a single point.
Realised PnL across both closed trades totals -$11.06M. Gross fees paid were $128,434, representing 1.2% of the total loss. The account generated $433M in gross volume across three episodes (two closed, one open).
Trade quality
Win rate is 0%. Both closed trades lost money. The sample is too small to compute meaningful profit factor or expectancy figures. Fees are immaterial relative to the scale of the losses.
Post-mortems
ETH long, 31 May to 9 July 2025. Entry at $2,473.14, exit at $2,753.72, loss of $282,962 over 952 hours. The position reached $134M notional. The trade was flagged for averaging down, indicating capital was deployed into a deteriorating position rather than exited at the structural stop. The 3% stop distance was set but not triggered before manual closure.
ETH short, 9 July to 9 August 2025. No entry price recorded; exit at $3,383.25, loss of $10.78M over 731 hours. The position scaled to $260.7M notional with no structural stop. This trade consumed the vast majority of the account's loss in the data covered.
Open positions
One open position remains. No details on entry, direction, or stop placement are provided in the available data.
Honest summary
- The sample is too small to isolate strengths or weaknesses with confidence. Two trades is not a sufficient basis for pattern recognition.
- Both closed trades moved against the account without triggering stops or being exited early, suggesting either stops were not in place or were not respected.
- The second trade's notional size ($260M) was nearly double the first, and it carried no structural stop, indicating position management became more aggressive as losses accumulated.
Behaviour checksRule-based warnings found in the trading history. They are not moral judgements; they mark patterns worth reviewing.
Rule-based position-cycle checksNo matching position cycles in the data covered.
- ETH on May 31, 2025: added to the position; while it was already moving against entry; outcome -$282,962.
No matching position cycles in the data covered.
No matching position cycles in the data covered.
Expectancy is not a forecast. It is the historical average result per closed position cycle in this reconstructed sample.
Risk simulatorA counterfactual replay of the same historical trades using fixed risk limits. It is for comparing risk shape, not predicting future returns.
Replays the same closed position cycles with 1%, 2%, and 4% account-risk sizing. It shows what the wallet would have made or lost if each eligible cycle was sized from account value at entry and a structural stop.
- Max drawdownLargest high-to-low account-value drop inside this simulated replay.
- 0.0%
- Stopped earlyHow many historical position cycles would have exited before the real close because the simulated stop was hit.
- 0
- Max drawdownLargest high-to-low account-value drop inside this simulated replay.
- 0.0%
- Stopped earlyHow many historical position cycles would have exited before the real close because the simulated stop was hit.
- 0
- Max drawdownLargest high-to-low account-value drop inside this simulated replay.
- 0.0%
- Stopped earlyHow many historical position cycles would have exited before the real close because the simulated stop was hit.
- 0
The 1%, 2%, and 4% rules are account-risk limits per position cycle, not leverage settings. If the simulated stop is breached, the cycle is stopped early. Outputs are gross of fees and funding, so use them as risk-shape comparisons rather than exact alternate realised trading PnL.