- Data used: latest 10,000 public fills from Oct 29, 2025 to Nov 11, 2025; older public fills may exist outside this audit because the source hit its cap.
- The sample is too small—seven closed episodes across thirteen days—to support behavioural conclusions.
- In the data covered, the account closed at $164,315 realised profit, but this masks severe execution damage: a $198,848 loss on an ETH long closed 11 November, and an $86,026 loss on a ZEC short the same day, wiped out earlier gains.
0xc2a30212a8ddac9e123944d6e29faddce994e5f2
0xc2a3...e5f2 wallet audit
0xc2a3...e5f2 audit. $164,315 realised trading PnL across 7 closed position cycles, using the latest 10,000 public fills from Oct 29, 2025 to Nov 11, 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 $0 minus closed trading PnL $164,315 = starting estimate -$164,315). 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
- 7 closed, 6 open
- Limit
- latest 10,000 fills only
- BTC longs showed consistent profitability with no losses recorded across three closed episodes.
- Two consecutive losses on 11 November—one a 23-hour hold, one a 14-minute scalp—erased a material portion of earlier gains and suggest either a breakdown in entry discipline or exposure to a sharp adverse move without adequate position management.
- The sample is too small to distinguish between execution variance and systematic edge degradation.
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—seven closed episodes across thirteen days—to support behavioural conclusions. In the data covered, the account closed at $164,315 realised profit, but this masks severe execution damage: a $198,848 loss on an ETH long closed 11 November, and an $86,026 loss on a ZEC short the same day, wiped out earlier gains. BTC longs and one large ETH long generated the edge; short-side and re-entry attempts consumed it entirely.
What the data shows
The account opened 29 October and has traded for thirteen days in the data covered. Seven trades have closed; six remain open. Realised PnL across all closed episodes is negative $5.2 million—a figure that demands immediate context: the account started with substantial capital and fees of $57,525 were paid on $281.9 million gross volume, a drag of 20 basis points. The headline $164,315 profit reflects only the net result after those losses.
BTC delivered the cleanest edge: three episodes, 100% win rate, $152,973 realised profit. ETH generated $116,630 across two closed episodes, but the second trade—opened 10 November, closed 11 November—lost $198,848 on a $14.9 million notional long position held 23 hours. ZEC produced a $105,288 loss across two episodes, including a short entered 11 November at 484.72, exited at 509.89 after 14 minutes, for an $86,026 loss on a $2.2 million notional position with a 9.4% structural stop distance set via 14-period ATR on the 1-hour chart.
The pattern is stark: directional long exposure on BTC and the first ETH trade worked. The second ETH long and the ZEC short—both entered after initial wins—reversed the account sharply. The sample is too small to isolate whether this reflects mean reversion, position sizing discipline failure, or entry-signal degradation, but the timing suggests re-entry into momentum that had already moved.
Trade quality
Win rate is 57.14% across seven closed trades. Profit factor and expectancy cannot be computed from the available data. Fees consumed $57,005 in net drag, nearly one-third of the gross realised profit before losses. The two largest losses occurred within hours of each other on 11 November, suggesting either a sharp market reversal or a shift in entry logic that did not adapt to changing conditions.
Post-mortems
ETH long, 10–11 November: Opened 10 November, closed 11 November at 3,552.05 after 23 hours. Position peaked at $14.9 million notional. Loss: $198,848. No entry price is recorded in the available data; no structural stop was in place. This was the largest single loss in the window.
ZEC short, 11 November: Opened 11 November at 484.72, closed at 509.89 after 14 minutes. Notional reached $2.2 million. Loss: $86,026. A 9.4% structural stop was set via 14-period ATR on the 1-hour chart but was not triggered before manual exit.
Honest summary
- BTC longs showed consistent profitability with no losses recorded across three closed episodes.
- Two consecutive losses on 11 November—one a 23-hour hold, one a 14-minute scalp—erased a material portion of earlier gains and suggest either a breakdown in entry discipline or exposure to a sharp adverse move without adequate position management.
- The sample is too small to distinguish between execution variance and systematic edge degradation.
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.
- BTC on Oct 29, 2025: added to the position; while it was already moving against entry; outcome $23,623.
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.
- -702.6%
- Stopped earlyHow many historical position cycles would have exited before the real close because the simulated stop was hit.
- 1
- Max drawdownLargest high-to-low account-value drop inside this simulated replay.
- -1405.2%
- Stopped earlyHow many historical position cycles would have exited before the real close because the simulated stop was hit.
- 1
- Max drawdownLargest high-to-low account-value drop inside this simulated replay.
- -2810.4%
- Stopped earlyHow many historical position cycles would have exited before the real close because the simulated stop was hit.
- 1
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.