RRektrospect

@aguilatrades - 0x1f250df59a777d61cb8bd043c12970f3afe4f925

@aguilatrades wallet audit

@aguilatrades audit. -$3,576,661 realised trading PnL across 12 closed position cycles, using the latest 10,000 public fills from Aug 12, 2025 to Aug 24, 2025; older public fills may exist outside this audit.

loss-dominatedA quick bucket assigned from realised trading PnL, closed position-cycle count, and whether the public fill source was capped. Data covered: Aug 12, 2025 to Aug 24, 2025. 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 Aug 12, 2025 to Aug 24, 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: Aug 12, 2025 to Aug 24, 2025.-99.2%12 closed position cycles
Win rateShare of closed position cycles that ended positive. Profit factor compares total winning realised PnL with total losing realised PnL.+25.0%0.06 profit factor
Total volumeGross notional traded across 10,000 reconstructed public fills. A position cycle can contain many individual fills.$769,861,08414 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 -$3,576,661 minus closed trading PnL -$3,576,661 = starting estimate $3,576,661). 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 Aug 12, 2025 to Aug 24, 2025. Older trades may exist outside this page, so lifetime claims are avoided.Aug 12, 2025 to Aug 24, 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
12 closed, 2 open
Limit
latest 10,000 fills only
Equity curveA historical line showing how the wallet balance moved across the data covered: Aug 12, 2025 to Aug 24, 2025. It is not a prediction.-$3,576,661
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 Aug 12, 2025 to Aug 24, 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 Aug 12 with $3.8M and ends at Aug 24 with $0.Account value (USD)Date$3.8M$1.9M$0Aug 12Aug 14Aug 24
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 Aug 12, 2025 to Aug 24, 2025; older public fills may exist outside this audit because the source hit its cap.
  • This account lost $3.58M in the data covered, a -100% realisation on an estimated $3.58M starting balance.
  • The highest balance in this window was $5.13M on 13 August; the lowest balance in this window was $38.8K on 20 August.
Analysis readoutA plain-language interpretation layer from the trader analysis. Use the cards and tables below for the raw evidence.Strengths & weaknesses
  • One visible strength: The opening short ETH trade on 12 August was clean—entry, exit, profit, no averaging, no revenge. The account demonstrated it could execute a disciplined trade.
  • One visible weakness: Position sizing was completely uncontrolled. The three largest losses were 21×, 7.39×, and 3.53× the median loss. The account opened positions with $100M+ notional on a $3.58M starting balance, then averaged down into them. No position had a working stop.
  • One visible weakness: Revenge trading was systematic. After the -$370K short loss, the account immediately opened a $100.78M long position. After the -$2.21M long loss, it opened a $61.5M long BTC position. Both were closed at losses within hours.
  • Data scope caveat: Only the most recent 10,000 fills are visible. Earlier account history is not available. The data covered spans 11 days and 12 closed episodes; this is sufficient to identify structural failures but not sufficient to assess whether these patterns are account-wide or window-specific.
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. This account lost $3.58M in the data covered, a -100% realisation on an estimated $3.58M starting balance. The highest balance in this window was $5.13M on 13 August; the lowest balance in this window was $38.8K on 20 August. The deepest decline in this window was -99.24%. The core failure is structural: the account opened with a profitable short ETH trade on 12 August (+$190K), then immediately reversed into oversized long positions, averaged down aggressively across both ETH and BTC, and closed out three catastrophic losses totalling $2.36M in a 36-hour window. Revenge trading and position sizing without stops destroyed an account that briefly held $5M in equity.

What the data shows

The account opened on 12 August with a clean short ETH trade: entry 4618.65, exit 4579.53 in 2 hours, +$190K on a $23M notional position. This was the only trade executed with discipline. Immediately after, the account reversed into a long ETH position at 4589.35 on 12 August, which was averaged down 20 times to a maximum size of 10,000 ETH, closing at 4569.5 for -$105K. This was flagged as averaging down but the loss was contained.

The critical breakdown occurred on 13 August. After the short ETH loss of -$370K (entry 4694.55, exit 4724.47 in 4.4 hours on a $110M notional position), the account opened a revenge trade: a long ETH position at 4727.0 on 13 August at 19:15 UTC with a $100.78M notional size. This position was held for 19.3 hours and closed at 4712.98 on 14 August for -$2.21M. This was the single largest loss and is flagged as both an oversized loser (21× the median loss) and a revenge trade.

Simultaneously, after the ETH short loss, the account opened a long BTC position at 122,925.89 on 13 August at 21:31 UTC with a $61.5M notional size, averaged down 438 times, and closed at 122,980.59 after 1.17 hours for -$269K. This was flagged as both averaging down and a revenge trade.

On 14 August, a third oversized loss materialised: a long ETH position closed at 4506.25 for -$776K on a $33.3M notional, the second-largest loss and 7.39× the median.

By 20 August, the account had declined from $5.13M to $38.8K. The remaining activity (14 August to 24 August) shows two small short BTC wins (+$46.5K and +$404) but these are noise against the structural damage.

Fees paid were $173.7K on $769.9M gross volume. The net fee drag of $173.7K is material but secondary to the position-sizing and revenge-trading catastrophe. Realised PnL was -$3.42M; fees consumed an additional $173.7K, for a total realised loss of -$3.58M.

Trade quality

Win rate was 25% (3 wins from 12 closed episodes). Profit factor was 0.06, meaning losses were 16.7× larger than wins. Expectancy was -$298K per trade. The win/loss ratio was 0.19: average loss was -$423.8K, average win was +$79K. These numbers describe an account with no edge, no discipline, and no risk management.

The longest losing streak was 7 consecutive closed trades. The longest winning streak was 1 trade. There were no consecutive wins.

Post-mortems

ETH long, 13–14 August, revenge trade, -$2.21M:

Opened at 4727.0 on 13 August at 19:15 UTC following a -$370K short loss. Maximum notional exposure was $100.78M. Closed at 4712.98 on 14 August after 19.3 hours for -$2.21M. This position was sized at 21× the median loss and was explicitly a revenge trade. The structural stop was set at 3% distance but was not respected; the position was held through a 0.3% adverse move and closed at a loss. This is the defining trade of the account's collapse.

ETH short, 13 August, averaging down, -$370K:

Opened at 4694.55 on 13 August at 12:51 UTC. Averaged down 1,197 times to a maximum size of 23,500 ETH. Closed at 4724.47 after 4.4 hours for -$370K on a $110.3M notional. The position moved 30 basis points against the entry and was closed without recovery. This loss triggered the revenge trade that followed 4.5 hours later.

BTC long, 13 August, averaging down and revenge trade, -$269K:

Opened at 122,925.89 on 13 August at 21:31 UTC following the -$2.21M ETH loss. Averaged down 438 times to a maximum size of 500 BTC. Closed at 122,980.59 after 1.17 hours for -$269K on a $61.5M notional. This was a revenge trade opened after the largest loss of the window. The position was closed at a 55-basis-point loss.

What the risk simulation reveals

Under a 1% stop-loss rule applied historically, the account would have realised -$951.60 with a maximum decline of -0.04%. Under a 2% rule, the loss would have been -$1,903.21 with a maximum decline of -0.09%. Under a 4% rule, the loss would have been -$3,806.41 with a maximum decline of -0.18%. All three simulations show 40% win rate and 1 episode stopped early. These counterfactuals demonstrate that even a basic 1% hard stop would have reduced losses by 99.97% in the data covered. The account's actual losses were 940× larger than what a 1% stop would have permitted.

Open positions

No open positions at the time of the latest fill.

Honest summary

  • One visible strength: The opening short ETH trade on 12 August was clean—entry, exit, profit, no averaging, no revenge. The account demonstrated it could execute a disciplined trade.
  • One visible weakness: Position sizing was completely uncontrolled. The three largest losses were 21×, 7.39×, and 3.53× the median loss. The account opened positions with $100M+ notional on a $3.58M starting balance, then averaged down into them. No position had a working stop.
  • One visible weakness: Revenge trading was systematic. After the -$370K short loss, the account immediately opened a $100.78M long position. After the -$2.21M long loss, it opened a $61.5M long BTC position. Both were closed at losses within hours.
  • Data scope caveat: Only the most recent 10,000 fills are visible. Earlier account history is not available. The data covered spans 11 days and 12 closed episodes; this is sufficient to identify structural failures but not sufficient to assess whether these patterns are account-wide or window-specific.

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.
3
Examples
  • ETH on Aug 12, 2025: added to the position; while it was already moving against entry; outcome -$105,072.
  • ETH on Aug 13, 2025: added to the position; while it was already moving against entry; outcome -$370,599.
+1 more matching cycle
Oversized loserA losing position cycle more than 3x the wallet's median closed loss.
3
Examples
  • ETH: -$370,599 realised loss; 3.5x median closed loss.
  • ETH: -$2,212,011 realised loss; 21.1x median closed loss.
+1 more matching cycle
Revenge tradeOpened a larger-than-normal position within one hour after a closed loss.
2
Examples
  • ETH on Aug 13, 2025: followed a -$370,599 loss; larger-than-normal size.
  • BTC on Aug 13, 2025: followed a -$2,212,011 loss; larger-than-normal size.
ExpectancyAverage result per closed position cycle after wins and losses are blended. Positive means each completed cycle added money on average.-$298,055.07
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.+15.4%

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.-$952
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.
1
2% account-risk ruleThis scenario limits each eligible position cycle to about 2% of account value at the simulated stop.-$1,903
Max drawdownLargest high-to-low account-value drop inside this simulated replay.
-0.1%
Stopped earlyHow many historical position cycles would have exited before the real close because the simulated stop was hit.
1
4% account-risk ruleThis scenario limits each eligible position cycle to about 4% of account value at the simulated stop.-$3,806
Max drawdownLargest high-to-low account-value drop inside this simulated replay.
-0.2%
Stopped earlyHow many historical position cycles would have exited before the real close because the simulated stop was hit.
1

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 Aug 12 with $2.8M and ends at Aug 13 with $2.8M.Account value (USD)Date$2.8M$2.8M$2.8MAug 12Aug 13Aug 13

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.
ETHshort$23,054,685$190,1642025-08-12
BTCshort$14,746,539$46,5772025-08-13
BTCshort$2,339,129$4042025-08-23

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.
ETH7+14.3%-$3,318,805
BTC5+40.0%-$257,855
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