NOSTRADAMUS · Position Analytics Engine
SIMULATOR Israel withdraws from Lebanon by July 31, 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-july-31-2026 page.
▲ YES EDGE · +0.023 · f★ 2.9% · deploy 1.5% · net 1.57pp
§1 · Position economics
YES · Expected P/L per share +0.0232@ model P(YES) = 0.223
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 2.91% · g(f★) = 0.164%deploy 1.45% · g = 0.124%
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 @ 0.200 · EV +$42stake $363 · 1.45% of bankroll
Deployed stakestake
$363
1.45% of bankroll
Sharesunits
1,816
each pays $1 if YES
Max payoutwin
$1,816
gross, if win
Max profitwin
+$1,453
net of cost
Max losslose
-$363
binary settles to $0
Payout multiple×
×5.00
$1 → $5.00
Risk:RewardR:R
4.00 : 1
win $4.00 per $1
Expected P/LE[P/L]
+$42
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 22.3% | +$1,453 | +$324 |
| Resolves against (lose) | 77.7% | -$363 | -$282 |
| Expected value | 100.0% | — | +$42 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +2.3 pprelative edge +11.6%
Required win ratebreak-even
20.0%
price = implied probability
Model win rateP(win)
22.3%
what you forecast
Cushionedge
+2.3 pp
margin of safety
Fair pricemodel
0.223
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
20.0%
= price
Decimal oddsEU
5.000
total return per $1
AmericanUS
+400
$100 wins $400
FractionalUK
4.00 / 1
profit per $1 risked
Profit per $100stake
+$400.00
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 202% · APY 576%ROI 11.6% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+11.6%
APR (simple)scaled
+202%
ROI × 365/days
APY (compounded)if redeployed
+576%
(1+ROI)^(365/d) − 1
Daily expectedper day
+0.53%
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 +1.57 pperosion 32% · break-even w/ fees 20.8%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$727
2.91% · g = 0.164%
Half Kelly½ f★
$363
1.45% · g = 0.124%
Quarter Kelly¼ f★
$182
0.73% · g = 0.073%
Flat 1%1%
$250
1.00% · g = 0.095%
Flat 2%2%
$500
2.00% · g = 0.149%
Flat 5%5%
$1,250
5.00% · g = 0.086%
Recommended¼ f★
$182
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.722 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.766 bit
Δ +0.044 bit vs market
Surprise · YES−log₂ p
2.32 bit
self-information
Surprise · NO−log₂(1−p)
0.32 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0016 nat (0.0024 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 0.223 · CI [0.12, 0.35] · κ 47.2
Posterior meanE[θ]
0.223
Beta(10.5, 36.6)
95% credible intervalHDI
[0.12, 0.35]
price INSIDE → weak edge
Concentrationκ
47.2
pseudo-obs behind belief
Disagreementvs crowd
+2.3 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] -8.8% · P(YES) 18.3% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
-8.75%
P(YES) empiricalq
18.3%
Best pathmax
+400.0%
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 0.08% · ruin rate 0.3%400 paths × 120 bets · f deploy 1.45%
Sharpe / betμ/σ
0.047
μ 0.14% · σ 3.0%
Sortino / betμ/σ↓
0.097
downside-only denominator
VaR 95%5%
-1.5%
per-bet worst-case
CVaR 95%ES
-1.5%
mean tail loss
Max drawdownMDD
-6.1%
Calmar 0.01
Ruin rate≤50%
0.3%
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 -36.1pp · crowd gap -38.4pp
Anchor gapmodel − base
-36.1 pp
Crowd gapprice − base
-38.4 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 18.1% · AUC 0.757out-of-sample BSS (5-fold) 18.2% ± 2.7% · Brier 0.2046 · log-loss 0.6099 · n 1600✓ n = 1600
BrierBS
0.2046
lower = better · ō 0.51
BSSvs base
18.1%
improvement over base rate
ReliabilityREL
0.0056
miscalibration · want ↓
ResolutionRES
0.0498
decisiveness · want ↑
Log lossLL
0.6099
cross-entropy
AUCROC
0.757
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 1.33 · expectancy +0.131R180 trades · win 60.6% · Sharpe 0.133
Total P/Lnet
+$5,916
on $45,000 cycled
Win ratehit %
60.6%
109 W / 71 L
Profit factorPF
1.33
$ won / $ lost
Expectancyper trade
+$32.87
avg $ per position
R-expectancyper risk
+0.131R
in units of risk taken
Avg win / losspayoff
$217.12 / -$250.00
ratio 0.87 : 1
Sharpe / traderisk-adj
0.133
μR / σR
Closing line valueCLV
+3.40 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.