RRektrospect

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.

limited sampleLimited sample: only 7 closed position cycles are visible in the data covered (Oct 29, 2025 to Nov 11, 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 Oct 29, 2025 to Nov 11, 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: Oct 29, 2025 to Nov 11, 2025.-98.8%7 closed position cycles
Win rateShare of closed position cycles that ended positive. Profit factor compares total winning realised PnL with total losing realised PnL.+57.1%1.54 profit factor
Total volumeGross notional traded across 10,000 reconstructed public fills. A position cycle can contain many individual fills.$281,952,52713 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 $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.

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 Oct 29, 2025 to Nov 11, 2025. Older trades may exist outside this page, so lifetime claims are avoided.Oct 29, 2025 to Nov 11, 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
7 closed, 6 open
Limit
latest 10,000 fills only
Equity curveA historical line showing how the wallet balance moved across the data covered: Oct 29, 2025 to Nov 11, 2025. It is not a prediction.$0
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 Oct 29, 2025 to Nov 11, 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 Nov 6 with -$141k and ends at Nov 11 with $0.Account value (USD)Date$304k$82k-$141kNov 6Nov 10Nov 11
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 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 conclusions about edge, consistency, or behavioural patterns.
  • The account shows $164,315 realised profit in the data covered, but this result rests on a single outsized ETH long ($315,479 gain over 293 hours, opened 29 October, closed 10 November at 3952.47) that dwarfs all other closed trades combined.
Analysis readoutA plain-language interpretation layer from the trader analysis. Use the cards and tables below for the raw evidence.Strengths & weaknesses
  • 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 conclusions about edge, consistency, or behavioural patterns.
  • The account shows $164,315 realised profit in the data covered, but this result rests on a single outsized ETH long ($315,479 gain over 293 hours, opened 29 October, closed 10 November at 3952.47) that dwarfs all other closed trades combined.
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—seven closed episodes across thirteen days—to support conclusions about edge, consistency, or behavioural patterns. The account shows $164,315 realised profit in the data covered, but this result rests on a single outsized ETH long ($315,479 gain over 293 hours, opened 29 October, closed 10 November at 3952.47) that dwarfs all other closed trades combined. Two sharp losses in the final 24 hours (ETH long on 10–11 November and a ZEC short on 11 November) erased $284,874 and left the account near zero. The headline profit masks severe fragility.

What the data shows

BTC and ETH longs generated the data covered's profit: BTC contributed $152,973 across three episodes (100% win rate), and ETH contributed $116,630 across two episodes (50% win rate). ZEC shorts lost $105,288 across two episodes with a 0% win rate. The single dominant trade was the ETH long from 29 October to 10 November, which captured $315,479 on a $108.5 million notional position. That trade alone accounts for 192% of the account's net realised profit in the data covered; without it, the account would be deeply underwater.

The two largest losses occurred back-to-back on 10–11 November. An ETH long entered at 3561.18 on 10 November and exited at 3547.13 on 11 November, losing $198,848 in 23 hours on a $14.9 million notional. Immediately after, a ZEC short entered at 484.72 and exited at 509.89 in 14 minutes, losing $86,026 on a $2.2 million notional. These trades suggest reactive positioning after the large ETH win closed. The structural stops on both trades were tight (1.37% on ETH, 9.4% on ZEC), but the ZEC stop was breached in minutes, indicating either a failed short thesis or poor entry timing.

Gross fees paid totalled $57,525 on $281.9 million in gross volume, a net fee drag of $57,005. Realised PnL before fees would have been $221,320; fees consumed 26% of gross profit. The account ran six open positions at the time of the data pull, but the data covered shows only closed trades.

Trade quality

Win rate stands at 57.14% across seven closed episodes. Profit factor is undefined due to the structure of the data: the account is profitable overall, but the concentration of profit in a single trade and the sharp losses at the end create a fragile distribution. Expectancy per closed trade is $23,473 (realised PnL divided by closed episodes), but this figure is heavily skewed by the single large ETH win and does not reflect typical trade outcomes.

The sample is too small to assess consistency or edge stability.

Post-mortems

ETH long, 29 October–10 November, entry 3614.98, exit 3952.47, +$315,479. This trade generated nearly all data-covered profit. Held 293 hours, notional peaked at $108.5 million, structural stop at 1.31% below entry. The trade captured a sustained rally and was exited cleanly.

ETH long, 10–11 November, entry 3561.18, exit 3547.13, −$198,848. Opened after the prior ETH win closed, held 23 hours, notional $14.9 million, structural stop 1.37% below entry. Price moved against the position immediately and the stop was not triggered, suggesting the stop was advisory rather than hard. The exit was a manual close into weakness.

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.
2
Examples
  • BTC on Nov 6, 2025: re-entered at 104,743.18 after closing at 102,852.33 (Nov 6, 2025 prior close); outcome $128,133.
  • BTC on Nov 9, 2025: re-entered at 105,812.82 after closing at 104,360.15 (Nov 9, 2025 prior close); outcome $1,217.
Averaging downAdded size while the position was already moving against the entry.
1
Examples
  • BTC on Oct 29, 2025: added to the position; while it was already moving against entry; outcome $23,623.
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.$23,473.60
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.+24.4%

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.-$886,858
Max drawdownLargest high-to-low account-value drop inside this simulated replay.
-886.9%
Stopped earlyHow many historical position cycles would have exited before the real close because the simulated stop was hit.
4
2% account-risk ruleThis scenario limits each eligible position cycle to about 2% of account value at the simulated stop.-$1,773,716
Max drawdownLargest high-to-low account-value drop inside this simulated replay.
-1773.7%
Stopped earlyHow many historical position cycles would have exited before the real close because the simulated stop was hit.
4
4% account-risk ruleThis scenario limits each eligible position cycle to about 4% of account value at the simulated stop.-$3,547,433
Max drawdownLargest high-to-low account-value drop inside this simulated replay.
-3547.4%
Stopped earlyHow many historical position cycles would have exited before the real close because the simulated stop was hit.
4

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.

Equity curve by date and account valueX-axis shows date. Y-axis shows account value in US dollars. The line starts at Nov 10 with -$771k and ends at Nov 11 with -$1.7M.Account value (USD)Date-$771k-$1.2M-$1.7MNov 10Nov 9Nov 11

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.
ETHlong$108,527,845$315,4792025-11-10
BTClong$31,455,188$128,1332025-11-09
BTClong$22,984,727$23,6232025-11-06
BTClong$7,412,260$1,2172025-11-10

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.
BTC3+100.0%$152,973
ETH2+50.0%$116,630
ZEC20.0%-$105,288
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