0x940df59ba33f3387deff3c2400fecf1286fcce4c
0x940d...ce4c audit. -$5,394,105 realised trading PnL across 37 closed position cycles, using 2,000 public fills from Apr 6, 2025 to May 6, 2025.
The dollar PnL is the realised result from closed trades in the data covered. The percentage uses an inferred starting value (current account value $333 minus closed trading PnL -$5,394,105 = starting estimate $5,394,438). 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.
This is not a fixed last-week or last-month period. It is the actual span covered by the public fills used for this wallet, so the page should be read as 29 calendar days of visible trading history.
This account is -99.99% in the analysed window, down $5.39M from an estimated starting balance of $5.39M. The wallet was liquidated in real time. The core failure is not volatility or bad luck—it is catastrophic position sizing combined with revenge trading after large losses. On 6 April, after taking a $3.82M loss on an ETH long, the trader opened a $9.34M ETH long (revenge trade), then a $4.96M BTC long (averaging down into the same losing thesis), then another $966K ETH long. All three were closed at losses within hours. The account never recovered. Win rate of 62% is meaningless when the average loss is $386K and the average win is $600.
The account opened on 6 April 2025 with approximately $5.39M. Within six hours, it suffered three catastrophic losses totalling $5.44M. The first loss—an ETH long opened and closed on 6 April with no entry price recorded—lost $3.82M on a notional position of $25.1M. This was immediately followed by a revenge trade: a $9.34M ETH long opened at 6 April 20:34, closed at 1581.03 on 6 April 21:03, for a loss of $1.46M. Minutes later, a $4.96M BTC long was opened at 79,431.65 on 6 April 21:15, held for 9.33 hours, and closed at 77,936.87 on 7 April for a loss of $116K. A fourth position, a $966K ETH long opened on 6 April 21:16 and closed on 7 April, returned a small profit of $1.88K.
By 16 April, the account had fallen to $957.73. A brief recovery to $2,066.76 on 23 April was erased by late-month re-entries into ETH. The account closed the window at $333.16.
ETH accounts for $5.28M of realised losses across 30 episodes. BTC contributed $115.6K in losses across 4 episodes. SOL lost $20. Long positions lost $5.40M; short positions gained $2.92K. The 62% win rate is a statistical mirage: 23 winning trades averaged $600 each, while 14 losing trades averaged $386K each. Profit factor is 0.0—losses consumed all gains and more.
Fees paid were $11,039 on $47M gross volume. Fee drag is immaterial relative to the catastrophic PnL bleed.
Win rate 62.16% is a false comfort metric. Profit factor of 0.0 means the account has no edge. Expectancy is -$145,787 per trade. The win/loss ratio is 0.0 because average losses dwarf average wins by a factor of 643x. The largest loss ($3.82M) was 4,479 times the median loss. The second-largest loss ($1.46M) was 1,714 times the median loss. This is not variance; this is structural.
The max loss streak was 3 consecutive losses. The max win streak was 9 consecutive wins—all small, all closed quickly, none offsetting a single large loss.
ETH long, 6 April 20:34–21:03, closed at 1581.03, loss $1,461,650. This is a revenge trade opened immediately after the $3.82M loss on the same coin. Notional position size was $9.34M. Duration 0.69 hours. No entry price is recorded, suggesting a market order or rapid scaling. The position was sized to recover the prior loss in a single trade. It failed.
BTC long, 6 April 21:15–7 April 06:48, entry 79,431.65, exit 77,936.87, loss $116,102. Opened as a revenge trade following the ETH losses. Notional $4.96M. The position was averaged down 13 times between 79,401 and 79,399. A 3% structural stop was in place but not triggered; the exit was a manual close. This is a textbook averaging-down sequence into a losing position. The trader added size at lower prices, increasing notional exposure while the thesis deteriorated.
Under a 1% stop-loss rule applied historically, the account would have realised a loss of $33,187 with a max drawdown of -29.1%, stopping out 2 episodes early. Under a 2% rule, losses would have been $66,373 with a -58.2% drawdown. Under a 4% rule, losses would have been $132,747 with a -116.4% drawdown. These are gross of fees. The simulator shows that even modest mechanical stops would have reduced losses by 99%, but the account did not use them. The 3% structural stops that were in place on some trades were either not respected or not applied to the oversized positions that mattered.
No open positions at window close.
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.