- Data used: 1,005 public fills from Feb 4, 2025 to Jun 1, 2025; this is the actual visible trading span, not a preset last-week or last-month period.
- This account is -47.2% over the data covered, with a -52.8% max drawdown and a current balance of $20,681.
- The account does have a visible BTC long edge, but the result is dominated by one large CL re-entry loss and a thin post-fee margin.
@Wintermute - 0xecb63caa47c7c4e77f60f1ce858cf28dc2b82b00
@Wintermute wallet audit
@Wintermute audit. -$14,333 realised trading PnL across 36 closed position cycles, using 1,005 public fills from Feb 4, 2025 to Jun 1, 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 $20,681 minus closed trading PnL -$14,333 = starting estimate $27,915). 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 117 calendar days of visible trading history.
- Public fills
- 1,005
- Position cycles
- 36 closed, 3 open
- Limit
- public fill cap not hit
- BTC longs are the only clear strength in this data covered.
- CL re-entry risk is the main account-level wound.
- Shorts and FARTCOIN both subtract from the BTC edge.
- The simulator cards need to carry the loss case because this is the canonical Rektrospect use case.
Bottom line up front
This account is -47.2% over the data covered, with a -52.8% max drawdown and a current balance of $20,681. The account does have a visible BTC long edge, but the result is dominated by one large CL re-entry loss and a thin post-fee margin.
What the data shows
The account is not uniformly poor. BTC produced $6,131 across 29 closed position cycles, and the long book generated $12,109 while shorts lost $10,539. That asymmetry matters because the wallet's best historical behaviour is concentrated rather than broad.
The damage is also concentrated. The CL long opened on 7 April at $109.88 and closed on 14 April at $92 for -$14,333. FARTCOIN adds another weak pocket: 12 closed position cycles, 0% win rate, and -$777 realised PnL.
Trade quality
The headline trade-quality numbers are a 54.3% win rate, 1.04 profit factor, -$398.14 expectancy, and 0.88 win/loss ratio. That is a fragile profile: enough winners to look active, not enough payoff control to absorb a large loser.
Post-mortems
The diagnostic position cycle is the CL long from 7 April. The audit marks it as both a FOMO re-entry and an oversized loser, with a -16.3% worst move against the position and -$14,333 realised damage.
What the risk simulator reveals
Under a simulated 1% rule, the CL-heavy historical path would have produced -$360 with 15 position cycles stopped early. Under 2%, it would have produced -$720 with 13 position cycles stopped early. Under 4%, it would have produced -$1,440 with 10 position cycles stopped early.
Honest summary
- BTC longs are the only clear strength in this data covered.
- CL re-entry risk is the main account-level wound.
- Shorts and FARTCOIN both subtract from the BTC edge.
- The simulator cards need to carry the loss case because this is the canonical Rektrospect use case.
Behaviour checksRule-based warnings found in the trading history. They are not moral judgements; they mark patterns worth reviewing.
Rule-based position-cycle checks- CL on Apr 7, 2025: re-entered at 109.88 after closing at 89.9 (Mar 24, 2025 prior close); outcome -$14,333.
No matching position cycles in the data covered.
- CL: -$14,333 realised loss; 8.2x median closed loss.
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.
- -8.5%
- Stopped earlyHow many historical position cycles would have exited before the real close because the simulated stop was hit.
- 15
- Max drawdownLargest high-to-low account-value drop inside this simulated replay.
- -14.2%
- Stopped earlyHow many historical position cycles would have exited before the real close because the simulated stop was hit.
- 13
- Max drawdownLargest high-to-low account-value drop inside this simulated replay.
- -22.1%
- Stopped earlyHow many historical position cycles would have exited before the real close because the simulated stop was hit.
- 10
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.