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Section III · Trade tracker
Refreshed 2h 17m ago
Shadow book.
Every play the engine emits, paper-traded at realistic size — the quantitative trial-and-error lab the live suggestions are calibrated against.
21 open · 229 closes since inception · active signals7-day default view
P&L · 7d
-$17.6K
++$12.4K vs prior 7d
Win rate · 7d
47%
18W / 20L
Open P&L
+$974
21 open · +$28.5K deployed
All-time (active)
+$33.9K
55% wr · 229 closes
Earned vs lost · 7dnet -$17.6K
earned
+$5.6K
lost
-$23.2K
profit factor
0.24
Earned vs lost · all-timenet +$33.9K
earned
+$151.0K
lost
-$117.1K
profit factor
1.29
Performance & analytics — expectancy, equity curve, P&L attribution, entry timingclick to expand
Deploy-grade read · net of slippage + commission
ruleset 2026-06-01.v2NOT YET
Live system, retired signals excluded
Expectancy / trade
+$191
across 226 closes
Win rate (95% CI)
50%
CI 43–56% · 112W/114L
Profit factor
1.24
payoff 1.27×
Net P&L (after costs)
+$43.2K
gross +$91.5K − +$48.3K costs
Sample: established (n≥30)Avg win +$2.0K · avg loss +$1.6Kcost model: $0.65/ct
Signal concentration (open book)HHI 0.35
Top signal GEX_FLIP = 41% of deployed risk. Diversified enough (HHI≤0.5).
Sizing is normalized to what we'd actually deploy. Index options (SPX/NDX/RUT) are scaled to the liquid ETF they'd really be traded through (SPY/QQQ/IWM) — one raw NDX contract is ~$242K, which nobody deploys. Position-management notes (scale-ins, size-up/exit) are excluded from capital. Both cost and P&L scale by the same factor, so ROI stays honest. This is the whole point of the shadow book: the dollar figures here are the realistic trial-and-error the live play suggestions are tuned against.
Performance — paper book
Equity curve, active strategies only
229 closes since inception
Last 7d38 closes
$-17.6K/ $54K cap
Last 30d202 closes
+$39.4K/ $406K cap
All time229 closes
+$33.9K/ $476K cap
Currently deployed
$28.5K
cost basis across open shadows
Open P&L (live)
+$974
7.1% lifetime ROI on deployed
Notes
Numbers show paper-book performance — what you'd have earned taking every active-signal shadow at the engine's suggested size. Only live, deploy-grade signals are counted; retired strategies are fully excluded.
P&L attribution — paper book
Where the money came from
active signals · proxy-normalized · all-time
By signal
net realized P&L per alpha source
GEX_FLIP
+$32.5K
108
UW_FLOW
+$22.9K
12
MANUAL
+$1.1K
3
TRIPLE_CONFIRM_LONG
+$643
2
IV_RANK
+$469
4
UW_PUT_FLOW
-$121
12
CREDIT_SPREAD
-$577
32
CSP_INCOME
-$2.0K
18
CC_INCOME
-$21.1K
38
By week
net realized P&L per Monday-anchored week
May 4
+$9.1K
15
May 11
+$2.7K
6
May 18
+$8.5K
32
May 25
+$22.0K
32
Jun 1
+$14.9K
89
Jun 8
-$8.4K
27
Jun 15
-$14.9K
28
By conviction
net realized P&L per entry conviction
HIGH
+$3.2K
102
MED
+$33.5K
107
LOW
-$1.3K
8
—
-$1.5K
12
Avg max favorable
+33%
144 fwd-captured
Avg max adverse
-47%
worst drawdown pre-close
Capture fraction
57%
realized ÷ peak (winners)
Round-tripped
1
hit +50% then closed flat/down
Entry timing — realized edge
Chase vs pullback — which actually pays?
32 closes with entry-day context
↓ Pullback (red-day entry)
+$418
expectancy
56%
win · 9n
+$3.8K
total P&L
bought into weakness — the playbook-preferred entry
↑ Chase (green-day entry)better edge
+$1.7K
expectancy
65%
win · 23n
+$39.5K
total P&L
bought into strength — momentum continuation bet
Entry day classified from the underlying's move on the open date (red = down day = pullback, green = up day = chase). The higher expectancy-per-trade column is the empirically better entry style for the current book — the live scout uses this to bias entry-timing badges.
Looking for fresh trade ideas? Today's UW + Triple-Confirm candidates moved to /scout with full paragraph reasoning per card.open /scout →
Closed · last 7d · 19 of 38
last 7d P&L -$506 · 58% win rate · page 1/1 (active signals, proxy-normalized)
| Trade | Signal | Opened | Closed | Hold | P&L | % | Why |
|---|---|---|---|---|---|---|---|
✗CALL CBRS $200 exp Jul 2 | CREDIT_SPREAD | Jun 2 | Jun 17 | 15d | -$5 | -2% | stop: spread near max width (d |
✓CALL GEV $995 exp Jul 10 | CREDIT_SPREAD | Jun 15 | Jun 17 | 2d | +$40 | +16% | stop: loss reached credit coll |
✗CALL TLN $380 exp Jul 10 | CREDIT_SPREAD | Jun 15 | Jun 17 | 2d | -$30 | -11% | stop: loss reached credit coll |
✗CALL USO $118 exp Jul 10 | CREDIT_SPREAD | Jun 15 | Jun 17 | 2d | +$0 | 0% | stop: loss reached credit coll |
✓CALL PLTR $136 exp Jul 10 | CREDIT_SPREAD | Jun 15 | Jun 17 | 2d | +$7 | +17% | stop: loss reached credit coll |
✓CALL TSM $450 exp Jul 10 | CREDIT_SPREAD | Jun 15 | Jun 17 | 2d | +$5 | +3% | stop: loss reached credit coll |
✗CALL VST $155 exp Jul 10 | CREDIT_SPREAD | Jun 15 | Jun 17 | 2d | -$68 | -34% | stop: loss reached credit coll |
✓PUT AAOI $177.5 exp Jun 18 | CSP_INCOME | Jun 15 | Jun 16 | 1d | +$75 | +16% | DTE ≤ 7 — force exit (theta cr |
✓CALL USO $133 exp Jul 10 | CREDIT_SPREAD | Jun 15 | Jun 16 | 1d | +$36 | +95% | BTC target (50% of max profit) |
✗PUT AXTI $102 exp Jun 26 | CSP_INCOME | Jun 15 | Jun 16 | 1d | -$660 | -86% | premium hit 1.5x entry (50% lo |
✓CALL LLY $1200 exp Jul 10 | CREDIT_SPREAD | Jun 15 | Jun 16 | 1d | +$115 | +60% | BTC target (50% of max profit) |
✓PUT OKLO $55 exp Jul 2 | CSP_INCOME | Jun 8 | Jun 15 | 7d | +$205 | +52% | BTC target (50% profit) hit |
✓PUT OKLO $51 exp Jul 2 | CSP_INCOME | Jun 10 | Jun 15 | 5d | +$198 | +63% | BTC target (50% profit) hit |
✓PUT VST $135 exp Jul 2 | CSP_INCOME | Jun 10 | Jun 15 | 5d | +$302 | +78% | BTC target (50% profit) hit |
✓PUT ANET $150 exp Jun 26 | CSP_INCOME | Jun 12 | Jun 15 | 3d | +$262 | +71% | BTC target (50% profit) hit |
✗CALL AOSL $40 exp Jul 17 | CREDIT_SPREAD | Jun 2 | Jun 11 | 9d | -$115 | -121% | stop: loss reached credit coll |
✗PUT ANET $147 exp Jun 18 | CSP_INCOME | Jun 8 | Jun 11 | 3d | -$58 | -18% | DTE ≤ 7 — force exit (theta cr |
✗CALL ASML $1740 exp Jun 26 | CREDIT_SPREAD | Jun 1 | Jun 11 | 10d | -$905 | -132% | stop: loss reached credit coll |
✓CALL BWXT $175 exp Jul 17 | CREDIT_SPREAD | Jun 2 | Jun 11 | 9d | +$90 | +55% | BTC target (50% of max profit) |
Fill quality · backtest vs actual
How far do actual fills drift from the model?
347 closes analysed
refreshed 3h 40m ago
| Signal | Trades | Target % | Median slip | p90 slip | Median hold | Verdict |
|---|---|---|---|---|---|---|
| GEX_FLIP | 109 | 57% | 573 bps | 2972 bps | 7d | WIDE |
| CC_INCOME | 38 | 18% | 1529 bps | 7531 bps | 1d | WIDE |
| CREDIT_SPREAD | 29 | 48% | 4565 bps | 11511 bps | 2d | WIDE |
| CSP_INCOME | 18 | 28% | 1731 bps | 3426 bps | 3d | WIDE |
| UW_FLOW | 12 | 42% | 597 bps | 2489 bps | 4.5d | WIDE |
| UW_PUT_FLOW | 12 | 67% | 1001 bps | 3241 bps | 4d | WIDE |
| MANUAL | 3 | 33% | 1161 bps | 1161 bps | 4d | WIDE |
| TRIPLE_CONFIRM_LONG | 2 | 50% | 377 bps | 566 bps | 3.5d | OK |
Slippage measures how far the actual realised return drifted from the model's +50% target / -50% stop benchmark. TIGHT<200bp = model trustworthy. OK 200–800bp = adjust expectations. WIDE>800bp = re-calibrate. DTE force-close + expirations are excluded (no clean benchmark to measure against).
target hit
144 closes · med 822.1bp · WIDE
stop hit
161 closes · med 675.7bp · WIDE
dte force
39 closes · med —bp · TIGHT
other
3 closes · med —bp · TIGHT
Signal performance · last 30d
202 closes · only signals with 30d activity shown (inactive ones suppressed)
| Signal | Trades | Win rate | Avg P&L | Total P&L | Open |
|---|---|---|---|---|---|
| GEX_FLIP | 89 | 60% | +$299 | +$26.6K | 4 |
| UW_FLOW | 8 | 63% | +$2.8K | +$22.6K | 2 |
| TRIPLE_CONFIRM_LONG | 2 | 50% | +$321 | +$643 | 0 |
| MANUAL | 1 | 100% | +$268 | +$268 | 0 |
| GEX_FLIP_DOWN | 4 | 50% | +$53 | +$213 | 2 |
| UW_PUT_FLOW | 12 | 67% | -$10 | -$121 | 1 |
| CREDIT_SPREAD | 32 | 53% | -$18 | -$577 | 5 |
| CSP_INCOME | 18 | 39% | -$111 | -$2.0K | 7 |
| IV_RANK | 11 | 18% | -$908 | -$10.0K | 0 |
| CC_INCOME | 38 | 45% | -$555 | -$21.1K | 2 |
Want all-time history? See /system. Want lifecycle stages? See /regime.