0x94d3735543ecb3d339064151118644501c933814
0x94d3...3814 audit. -$480,981 realised trading PnL across 26 closed position cycles, using the latest 10,000 public fills from Apr 11, 2026 to Jun 30, 2026; 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 $51,745 minus closed trading PnL -$480,981 = starting estimate $532,726). 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.
Only the most recent public fills are visible, so this audit covers the data covered rather than full account history. This account is -90.29% in the data covered, having fallen from $2.74M to $51.7K. The deepest decline in this window reached -98.38%. The core problem is catastrophic position sizing on two BTC trades that lost $460.6K combined, compounded by revenge trading, FOMO re-entries, and averaging down into losers. ETH is the only instrument with an edge (100% win rate, 3 episodes), but it represents a rounding error against the BTC wreckage.
The account opened with approximately $532.7K on 11 April 2026 and peaked at $2.74M on 15 April—a 414% gain in four days. That highest balance in this window was the high-water mark. The account then entered a systematic deepest decline in this window phase driven almost entirely by BTC trading.
BTC accounts for 19 closed episodes and -$460.5K of realised PnL. The two largest losses dominate the narrative. The first: a short position opened 11 April at 78,201.93, held 314 hours, and closed 24 April at 76,984.95 for -$137.7K, despite a 1.2% move in the intended direction. The position notional reached $93.7M—a leverage multiple so extreme it suggests the account was operating with minimal margin buffer. The second: a long position opened 24 April at 79,129.49 (immediately after the first loss closed), held 421 hours, and closed 12 May at 79,540.70 for -$322.9K. This was a revenge trade following the short loss. The position notional hit $12.88M. Both trades had ATR-based structural stops set at 0.5–0.77% distance, yet the account did not exit at those levels, suggesting either stops were not enforced or were moved.
After the May 12 close, the account had fallen to approximately $1.4M. The next phase shows five FOMO re-entries into BTC, all unprofitable. The most damaging: re-entry on 24 June at 59,357.03 (after closing at 60,003.61) for -$3.5K, followed by another re-entry on 26 June at 59,872.59 for -$5.1K. These were tight re-entries into the same instrument after losses, characteristic of revenge-driven decision-making.
ETH delivered the only consistent edge: three episodes, all profitable, totalling +$6.7K realised PnL. Two were short positions (one with a FOMO re-entry flag but still profitable). The third was a long scalp. Win rate 100%.
xyz:CL (crude oil) produced four episodes, all losses, totalling -$27.2K. Two were flagged as oversized losers and revenge trades. The account averaged down into a long position on 14 June, adding 13 times, reaching a max size of 1,841 contracts, then closed for -$379.67. It then opened a short revenge trade on 15 June for -$8.1K, then another long on 16 June for -$17.99K. This pattern—averaging, reversing, re-entering—is textbook loss-chasing behaviour.
Fees paid total $41.1K gross. Realised PnL before fees was -$437.4K, so fees consumed 9.4% of the loss magnitude but are immaterial relative to the core damage.
Win rate: 42.31%. Profit factor: 0.07. Expectancy: -$18,499.26 per episode. Win/loss ratio: 0.1 (one win for every ten losses in dollar terms).
These numbers describe an account with no edge. The 42% win rate is slightly above coin-flip, but the average loss (-$34,466.60) is 10.5 times the average win (+$3,274.38). The profit factor of 0.07 means the account loses $93 for every $1 it makes. Expectancy is deeply negative: each trade costs the account $18.5K on average, before fees.
The max loss streak reached 5 consecutive losses. The max win streak was 3. Streaks are short and losses cluster.
BTC short, 11–24 April, -$137.7K. Opened at 78,201.93, closed at 76,984.95 after 314 hours. The position notional reached $93.7M—approximately 176× the starting account balance. The structural stop was set at 0.5% distance (78,591.93), but the position was held through a 1.2% adverse move and closed at a 1.8% profit on the direction. This trade was flagged as an oversized loser and triggered a revenge trade immediately after.
BTC long, 24 April–12 May, -$322.9K. Opened at 79,129.49, closed at 79,540.70 after 421 hours. Position notional hit $12.88M. This was a direct revenge trade following the short loss. The trade had a 4.64% maximum favourable excursion but only a 0.06% maximum adverse excursion, meaning the account was in profit at one point but held through a reversal and closed near entry. The structural stop was 0.77% away (79,740.53); the account did not exit there. This single trade consumed 67% of the account's highest balance in this window balance.
xyz:CL long, 14–20 June, -$379.67 (averaged 13 times). Opened 14 June at 81.128, added at 81.131 and 81.129, reached max size 1,841 contracts, and closed 20 June at 75.62 for a 3% loss on the position. The account then opened a revenge short on 15 June at 77.08 for -$8.1K, and another long on 16 June at 77.99 for -$17.99K. The pattern shows the account chasing losses across three separate episodes in two days.
Under a 1% hard stop rule, the account would have realised -$97.2K (gross of fees) with a maximum decline of -18.24%, versus the actual -90.29%. Under 2%, the simulated loss would be -$194.4K with a -36.49% decline. Under 4%, -$388.8K with a -72.97% decline. The simulator stopped 8 episodes early across all three rules.
These counterfactuals show that enforcing mechanical stops would have reduced losses by 80% at the 1% level. The account's actual behaviour—holding through stops, averaging down, re-entering—cost approximately $383.8K in additional losses relative to a 1% rule.
No open positions at the time of the latest fill (30 June 2026).
Expectancy is not a forecast. It is the historical average result per closed position cycle in this reconstructed sample.
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.
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.