NOSTRADAMUS · Position Analytics Engine
SIMULATOR Israel withdraws from Lebanon by June 30, 2026?
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A live, interactive instrument for dissecting a single binary position. Sweep the inputs and watch every indicator recompute — payoff geometry, Kelly growth, Bayesian posterior, KL divergence, cost waterfall, Monte-Carlo equity fan, forecast calibration. Companion to the live /feed/pm-israel-withdraws-from-lebanon-by-june-30-2026 page.
▲ YES EDGE · +0.027 · f★ 3.1% · deploy 1.5% · net 1.95pp
§1 · Position economics
YES · Expected P/L per share +0.0270@ model P(YES) = 0.147
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 3.07% · g(f★) = 0.326%deploy 1.54% · g = 0.249%
g(f)f★ optimumdeployed fgrowth zone
Underbet leaves growth on the table; overbet destroys capital. The interior maximum is f★.
§2 · The trade ticket
YES @ 0.120 · EV +$86stake $384 · 1.54% of bankroll
Deployed stakestake
$384
1.54% of bankroll
Sharesunits
3,199
each pays $1 if YES
Max payoutwin
$3,199
gross, if win
Max profitwin
+$2,815
net of cost
Max losslose
-$384
binary settles to $0
Payout multiple×
×8.33
$1 → $8.33
Risk:RewardR:R
7.33 : 1
win $7.33 per $1
Expected P/LE[P/L]
+$86
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 14.7% | +$2,815 | +$414 |
| Resolves against (lose) | 85.3% | -$384 | -$327 |
| Expected value | 100.0% | — | +$86 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +2.7 pprelative edge +22.5%
Required win ratebreak-even
12.0%
price = implied probability
Model win rateP(win)
14.7%
what you forecast
Cushionedge
+2.7 pp
margin of safety
Fair pricemodel
0.147
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
12.0%
= price
Decimal oddsEU
8.333
total return per $1
AmericanUS
+733
$100 wins $733
FractionalUK
7.33 / 1
profit per $1 risked
Profit per $100stake
+$733.33
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 391% · APY 3312%ROI 22.5% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+22.5%
APR (simple)scaled
+391%
ROI × 365/days
APY (compounded)if redeployed
+3312%
(1+ROI)^(365/d) − 1
Daily expectedper day
+0.97%
geometric, per day held
Capital turns/yrvelocity
×17.4
how often this slot recycles
simple APRcompounded APYyour horizon
Rank positions by APR, not raw ROI. A thin edge tomorrow beats a fat edge next year.
§5 · Costs & net edge
Net edge +1.95 pperosion 28% · break-even w/ fees 12.8%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$768
3.07% · g = 0.326%
Half Kelly½ f★
$384
1.54% · g = 0.249%
Quarter Kelly¼ f★
$192
0.77% · g = 0.148%
Flat 1%1%
$250
1.00% · g = 0.183%
Flat 2%2%
$500
2.00% · g = 0.289%
Flat 5%5%
$1,250
5.00% · g = 0.217%
Recommended¼ f★
$192
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.529 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.602 bit
Δ +0.073 bit vs market
Surprise · YES−log₂ p
3.06 bit
self-information
Surprise · NO−log₂(1−p)
0.18 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0033 nat (0.0047 bit)belief ≈ market — stand down
YES contributionNO contributionbelief ‖ marketnoise
Zero KL ⇒ you know nothing the crowd doesn't.
§8 · Bayesian inference
MARKET PRICE INSIDE 95% CIposterior μ 0.147 · CI [0.05, 0.28] · κ 33.8
Posterior meanE[θ]
0.147
Beta(5.0, 28.9)
95% credible intervalHDI
[0.05, 0.28]
price INSIDE → weak edge
Concentrationκ
33.8
pseudo-obs behind belief
Disagreementvs crowd
+2.7 pp
posterior − price
market prior (dashed)model posterior95% credible bandmarket price
When the market price falls outside the 95% credible interval, your disagreement is statistically meaningful.
§9 · Tail risk · Monte-Carlo (mode A · single position to resolution)
E[P/L] +2.1% · P(YES) 12.3% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+2.08%
P(YES) empiricalq
12.3%
Best pathmax
+733.3%
Worst pathmin
-100.0%
VaR 95%5%
100.0%
CVaR 95%ES
100.0%
median path25/75 + 5/95 bandsentry pricemodel q
Logit-space mean-reverting walk + terminal flip with probability q. Answers: 'what happens to THIS one position'. Distinct from the repeated-edge fan below.
§9b · Tail risk · Monte-Carlo (mode B · repeated independent edges)
Median CAGR/bet 0.29% · ruin rate 4.3%400 paths × 120 bets · f deploy 1.54%
Sharpe / betμ/σ
0.075
μ 0.34% · σ 4.5%
Sortino / betμ/σ↓
0.220
downside-only denominator
VaR 95%5%
-1.5%
per-bet worst-case
CVaR 95%ES
-1.5%
mean tail loss
Max drawdownMDD
-10.3%
Calmar 0.03
Ruin rate≤50%
4.3%
P(equity ever ≤ 50%)
median25/75 band5/95 bandruin line
Answers a different question: 'if I could find this exact edge forever, what is the bankroll trajectory'. Compounds 120 sequential resolutions which is NOT what happens to a single position.
§10 · Base-rate & macro context
ANCHORED · supported by convictionanchor gap -36.8pp · crowd gap -39.5pp
Anchor gapmodel − base
-36.8 pp
Crowd gapprice − base
-39.5 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 20.8% · AUC 0.769out-of-sample BSS (5-fold) 20.9% ± 3.5% · Brier 0.1978 · log-loss 0.5893 · n 1600✓ n = 1600
BrierBS
0.1978
lower = better · ō 0.48
BSSvs base
20.8%
improvement over base rate
ReliabilityREL
0.0040
miscalibration · want ↓
ResolutionRES
0.0550
decisiveness · want ↑
Log lossLL
0.5893
cross-entropy
AUCROC
0.769
0.5 coin · 1.0 oracle
calibration curveROCUNC (irreducible)RES (skill, ↑)REL (miscalib, ↓)
Computed on a seeded synthetic forecast ledger. Reseed (⟳) to redraw.
§12 · Journal vitals (synthetic ledger)
PROFITABLE · PF 1.36 · expectancy +0.174R180 trades · win 51.7% · Sharpe 0.110
Total P/Lnet
+$7,845
on $45,000 cycled
Win ratehit %
51.7%
93 W / 87 L
Profit factorPF
1.36
$ won / $ lost
Expectancyper trade
+$43.59
avg $ per position
R-expectancyper risk
+0.174R
in units of risk taken
Avg win / losspayoff
$318.23 / -$250.00
ratio 1.27 : 1
Sharpe / traderisk-adj
0.110
μR / σR
Closing line valueCLV
+3.33 pp
avg edge vs close
cumulative P/Lprofitable zonered zonesynthetic · seeded from asset
The scorecard every trader checks. Synthetic ledger seeded from the asset slug — recomputes against your real fill history once wired.