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 account is profitable in that window: +0.2% realised PnL ($14.8k on a $7.5M starting base), but the headline obscures a brutal volatility story. The highest balance in this window reached $8.05M in June 2026; the lowest balance fell to $577k in November 2025—a deepest decline in this window of -49.98%. The account survives on short-side edge (BTC, SOL, ETH shorts all profitable) and a single exceptional LIT short trade ($8.2k), but long-side attempts and revenge-driven re-entries have been consistently destructive. Behavioural flags dominate the loss register: averaging down, FOMO re-entries, and revenge trades cluster around the worst losses, and the risk simulator shows that even a 1% hard stop rule would have turned this into a -$90k loss.
What the data shows
This account trades with extreme notional size relative to account equity—the largest single position (BTC long, November 2026) reached $657k notional on a $7.5M base, and multiple positions exceed $150k. The account opened on 2 November 2025 and has executed 328 closed trades across 250 calendar days, averaging just over one closed position per day. The data covered spans from early November 2025 through mid-July 2026.
Money is made almost entirely on the short side. BTC shorts generated $3.8k realised PnL on 70% win rate (20 episodes); SOL shorts added $1.4k; ETH shorts contributed $793. LIT shorts alone account for $8.2k of the $14.8k total realised profit—a single 45-hour short from 29 to 31 December 2025 at 3.56 to 2.76. By contrast, long positions lost $2.5k on BTC, $759k on XRP (97 episodes, 54.6% win rate, no edge), and $10k on FARTCOIN (111 episodes, 56.8% win rate, no edge). The long side is a graveyard: 62.65 USD realised PnL across all long trades versus $14.7k on shorts.
Fees consumed $830.37 in net drag against $13.3k realised PnL—a 6.2% haircut. Gross fees paid were $146.82, but the net fee drag figure suggests significant rebate clawback or funding cost accumulation. The maker rate is 96.34%, so the account is not paying taker spreads; the fee drag is structural funding or rebate mechanics.
The account exhibits no position dominance in the data covered—all positions are currently closed. However, the historical balance arc reveals extreme leverage cycling: the account swung from $8.05M highest balance in this window to $577k lowest balance in this window, a move that implies either catastrophic deepest decline in this window absorption or position liquidations followed by recovery. The 328 closed episodes and 8 open episodes (currently flat) suggest the account survived multiple margin calls or forced closures.
Trade quality
Win rate: 57.01%. Profit factor: 2.35. Expectancy: $44.99 per trade. Win/loss ratio: 1.77.
These numbers are respectable in isolation but misleading in context. A 57% win rate with a 1.77 win/loss ratio means the account wins slightly more often and wins slightly larger than it loses—textbook profitable mechanics. The 2.35 profit factor (gross revenue divided by gross losses) is solid. But the expectancy of $45 per trade on 328 episodes yields only $14.8k realised PnL, and that is after a $830 net fee drag. The account is barely above break-even on a risk-adjusted basis.
The max loss streak was 6 consecutive losses. The max win streak was 10. Neither is exceptional. The real problem is not the win rate; it is the behavioural pattern that generates the losses.
Post-mortems
XRP long, 2 November 2025, 0.62 hours, $2.51 to $2.50: -$815.91
Opened at 2.51, exited at 2.50 in 37 minutes. Maximum position notional was $163k—a 21.8x leverage bet on a $7.5M account for a 0.4% move. The trade is flagged as averaging down, oversized loser, and revenge trade. The structural stop was 4.0% away (instrument default), meaning the account was risking $6.5k to make pennies. This trade followed a $11.24 loss on XRP earlier that session. The account re-entered XRP at a worse price after a small loss, sized it massively, and exited at a worse price. Revenge trading at scale.
BTC long, 3 November 2025, 1.27 hours, $109,820.25 to $109,711.26: -$2,808.91
Opened at 109,820.25, exited at 109,711.26 in 76 minutes. Maximum position notional was $657k—a 8.8x leverage bet. Flagged as oversized loser and revenge trade. The structural stop (ATR 14 1H) was 0.69% away, implying a $4.5k risk envelope for a $109k move. This trade followed a $33.92 loss on BTC earlier that day. The account took a loss, waited hours, then re-entered BTC at a worse price with 4x the notional size and got stopped out immediately. This is textbook revenge trading: loss → emotional re-entry → larger size → immediate exit at worse price.
Both post-mortem trades share a pattern: small loss → re-entry at worse price → massive size → quick stop-out. The account is not learning from losses; it is compounding them.
What the risk simulator reveals
Under a 1% hard stop rule (gross of fees), the account would have realised -$90,424.93 with a max decline of -2.38%. Under 2%, it would have lost -$180,849.86 with a -4.7% decline. Under 4%, it would have lost -$361,699.71 with a -9.21% decline.
This is the inverse of the actual result: the account made $14.8k by running without stops and absorbing the -49.98% deepest decline in this window. The simulator shows that disciplined risk management would have turned this into a multi-six-figure loss. The account's profitability is entirely dependent on surviving catastrophic drawdowns and recovering from them. Without the ability to absorb a -$4M swing (from $8.05M to $577k), this account would be insolvent.
Open positions
No open positions. The account is currently flat.
Honest summary
- Short-side edge is real. BTC, SOL, and ETH shorts all show positive realised PnL and win rates above 58%. The LIT short was exceptional. The account has identified a genuine edge on the short side and executed it profitably.
- Long-side and revenge trading are destroying value. XRP longs lost $758k across 97 episodes with no edge. FARTCOIN longs lost $10k across 111 episodes. The five largest losses in the data covered are all flagged as revenge trades, averaging down, or FOMO re-entries. The account re-enters losing positions at worse prices with larger size, then exits at even worse prices. This is not variance; this is behaviour.