NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Iran close its airspace by July 31?
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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-will-iran-close-its-airspace-by-july-31-20260609184136056 page.
▲ YES EDGE · +0.045 · f★ 5.7% · deploy 2.8% · net 3.71pp
§1 · Position economics
YES · Expected P/L per share +0.0446@ model P(YES) = 0.260
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 5.68% · g(f★) = 0.563%deploy 2.84% · g = 0.429%
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 @ 0.215 · EV +$147stake $711 · 2.84% of bankroll
Deployed stakestake
$711
2.84% of bankroll
Sharesunits
3,305
each pays $1 if YES
Max payoutwin
$3,305
gross, if win
Max profitwin
+$2,595
net of cost
Max losslose
-$711
binary settles to $0
Payout multiple×
×4.65
$1 → $4.65
Risk:RewardR:R
3.65 : 1
win $3.65 per $1
Expected P/LE[P/L]
+$147
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 26.0% | +$2,595 | +$674 |
| Resolves against (lose) | 74.0% | -$711 | -$526 |
| Expected value | 100.0% | — | +$147 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +4.5 pprelative edge +20.8%
Required win ratebreak-even
21.5%
price = implied probability
Model win rateP(win)
26.0%
what you forecast
Cushionedge
+4.5 pp
margin of safety
Fair pricemodel
0.260
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
21.5%
= price
Decimal oddsEU
4.651
total return per $1
AmericanUS
+365
$100 wins $365
FractionalUK
3.65 / 1
profit per $1 risked
Profit per $100stake
+$365.12
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 361% · APY 2553%ROI 20.8% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+20.8%
APR (simple)scaled
+361%
ROI × 365/days
APY (compounded)if redeployed
+2553%
(1+ROI)^(365/d) − 1
Daily expectedper day
+0.90%
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 +3.71 pperosion 17% · break-even w/ fees 22.3%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$1,421
5.68% · g = 0.563%
Half Kelly½ f★
$711
2.84% · g = 0.429%
Quarter Kelly¼ f★
$355
1.42% · g = 0.254%
Flat 1%1%
$250
1.00% · g = 0.187%
Flat 2%2%
$500
2.00% · g = 0.334%
Flat 5%5%
$1,250
5.00% · g = 0.556%
Recommended¼ f★
$355
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.751 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.826 bit
Δ +0.075 bit vs market
Surprise · YES−log₂ p
2.22 bit
self-information
Surprise · NO−log₂(1−p)
0.35 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0056 nat (0.0081 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 0.260 · CI [0.15, 0.39] · κ 52.4
Posterior meanE[θ]
0.260
Beta(13.6, 38.8)
95% credible intervalHDI
[0.15, 0.39]
price INSIDE → weak edge
Concentrationκ
52.4
pseudo-obs behind belief
Disagreementvs crowd
+4.5 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] +20.9% · P(YES) 26.0% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+20.93%
P(YES) empiricalq
26.0%
Best pathmax
+365.1%
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 0.41% · ruin rate 7.2%400 paths × 120 bets · f deploy 2.84%
Sharpe / betμ/σ
0.097
μ 0.56% · σ 5.8%
Sortino / betμ/σ↓
0.196
downside-only denominator
VaR 95%5%
-2.8%
per-bet worst-case
CVaR 95%ES
-2.8%
mean tail loss
Max drawdownMDD
-10.9%
Calmar 0.04
Ruin rate≤50%
7.2%
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 -30.4pp · crowd gap -34.9pp
Anchor gapmodel − base
-30.4 pp
Crowd gapprice − base
-34.9 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 18.4% · AUC 0.758out-of-sample BSS (5-fold) 18.5% ± 3.3% · Brier 0.2040 · log-loss 0.6077 · n 1600✓ n = 1600
BrierBS
0.2040
lower = better · ō 0.51
BSSvs base
18.4%
improvement over base rate
ReliabilityREL
0.0046
miscalibration · want ↓
ResolutionRES
0.0504
decisiveness · want ↑
Log lossLL
0.6077
cross-entropy
AUCROC
0.758
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 1.05 · expectancy +0.026R180 trades · win 51.1% · Sharpe 0.022
Total P/Lnet
+$1,149
on $45,000 cycled
Win ratehit %
51.1%
92 W / 88 L
Profit factorPF
1.05
$ won / $ lost
Expectancyper trade
+$6.39
avg $ per position
R-expectancyper risk
+0.026R
in units of risk taken
Avg win / losspayoff
$251.62 / -$250.00
ratio 1.01 : 1
Sharpe / traderisk-adj
0.022
μR / σR
Closing line valueCLV
+3.57 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.