RRektrospect

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.

limited sampleLimited sample: only 2 closed position cycles are visible in the data covered (May 31, 2025 to Aug 9, 2025). Raw metrics are shown, but behavioural conclusions stay caveated until there are at least 10 closed cycles. Classification basis: closed net pnl after fees available window.latest 10,000 fillsHyperliquid's public fills source is capped for very active wallets. This audit used the latest 10,000 public fills it could retrieve, covering May 31, 2025 to Aug 9, 2025. Older trades may exist outside this page, so lifetime claims are avoided.
ModeProfessional keeps the tone factual. Roast uses the same numbers but writes the commentary more sharply.
ProfessionalRoast
Max drawdownLargest fall from a previous balance high to a later low inside the data covered: May 31, 2025 to Aug 9, 2025.-100.0%2 closed position cycles
Win rateShare of closed position cycles that ended positive. Profit factor compares total winning realised PnL with total losing realised PnL.0.0%0 profit factor
Total volumeGross notional traded across 10,000 reconstructed public fills. A position cycle can contain many individual fills.$433,254,1723 position cycles
Trading PnL vs transfersRealised trading PnL comes from Hyperliquid closed-fill profit and loss. Deposits and withdrawals can change account value, but they are not counted as trading PnL here.

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.

Data coveredHyperliquid's public fills source is capped for very active wallets. This audit used the latest 10,000 public fills it could retrieve, covering May 31, 2025 to Aug 9, 2025. Older trades may exist outside this page, so lifetime claims are avoided.May 31, 2025 to Aug 9, 2025

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
Equity curveA historical line showing how the wallet balance moved across the data covered: May 31, 2025 to Aug 9, 2025. It is not a prediction.-$11,060,271
latest fills onlyHyperliquid's public fills source is capped for very active wallets. This audit used the latest 10,000 public fills it could retrieve, covering May 31, 2025 to Aug 9, 2025. Older trades may exist outside this page, so lifetime claims are avoided.
Equity curve by date and account valueX-axis shows date. Y-axis shows account value in US dollars. The line starts at Jul 9 with $11M and ends at Aug 9 with $0.Account value (USD)Date$11M$5.4M$0Jul 9Aug 9
Audit summaryA short extract from the full trader analysis below. It is built from the stored numbers and evidence pack.What matters immediately
  • 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.
Analysis readoutA plain-language interpretation layer from the trader analysis. Use the cards and tables below for the raw evidence.Strengths & weaknesses
  • 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.
Trader analysisThis is the full written analysis for this wallet and mode. The metrics, flags, simulator, and tables below are the supporting evidence.Full trader analysis

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 checks
FOMO re-entryReopened the same market and direction soon after a winning close, but at a worse entry.
0

No matching position cycles in the data covered.

Averaging downAdded size while the position was already moving against the entry.
1
Examples
  • ETH on May 31, 2025: added to the position; while it was already moving against entry; outcome -$282,962.
Oversized loserA losing position cycle more than 3x the wallet's median closed loss.
0

No matching position cycles in the data covered.

Revenge tradeOpened a larger-than-normal position within one hour after a closed loss.
0

No matching position cycles in the data covered.

ExpectancyAverage result per closed position cycle after wins and losses are blended. Positive means each completed cycle added money on average.-$5,530,135.33
Fees / realised PnLFees as a share of realised trading PnL. High values mean execution cost is eating a meaningful part of the edge.n/a
Maker fill rateShare of fills that added liquidity rather than crossed the spread. Higher maker share usually means more patient execution.+44.9%

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.

1% account-risk ruleThis scenario limits each eligible position cycle to about 1% of account value at the simulated stop.$157,707
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
2% account-risk ruleThis scenario limits each eligible position cycle to about 2% of account value at the simulated stop.$315,414
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
4% account-risk ruleThis scenario limits each eligible position cycle to about 4% of account value at the simulated stop.$630,828
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.

No simulator curve yetThis wallet has 1 simulated close with usable stop and candle data. The cards above are scenario totals; a time-series curve needs at least two simulated closes.

Top lossesThe largest realised losing position cycles in the data covered by this audit.

Click a row for the trade breakdown
MarketThe traded Hyperliquid market or coin.SideLong means the wallet benefited if price rose. Short means it benefited if price fell.SizeLargest notional exposure reached during the reconstructed position cycle.PnLRealised profit or loss when the position cycle closed.DateClosed date when available; otherwise the cycle open date.

Top winsThe largest realised winning position cycles in the data covered by this audit.

Realised position-cycle outcomes
MarketThe traded Hyperliquid market or coin.SideLong means the wallet benefited if price rose. Short means it benefited if price fell.SizeLargest notional exposure reached during the reconstructed position cycle.PnLRealised profit or loss when the position cycle closed.DateClosed date when available; otherwise the cycle open date.

By marketBreaks the audit down by traded market or coin so you can see which markets helped or hurt the account.

Realised results by coin
CoinThe traded Hyperliquid market.CyclesClosed reconstructed position cycles for this market. One cycle can contain many fills.WinShare of that market's closed position cycles that ended positive.PnLRealised PnL attributed to this market's closed position cycles in the data covered by this audit.
ETH20.0%-$11,060,271
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