NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Iran close its airspace by June 15?
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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-june-15-20260609184136053 page.
▲ YES EDGE · +0.060 · f★ 8.0% · deploy 4.0% · net 5.25pp
§1 · Position economics
YES · Expected P/L per share +0.0600@ model P(YES) = 0.306
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 7.96% · g(f★) = 0.924%deploy 3.98% · g = 0.703%
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 @ 0.246 · EV +$243stake $995 · 3.98% of bankroll
Deployed stakestake
$995
3.98% of bankroll
Sharesunits
4,043
each pays $1 if YES
Max payoutwin
$4,043
gross, if win
Max profitwin
+$3,049
net of cost
Max losslose
-$995
binary settles to $0
Payout multiple×
×4.07
$1 → $4.07
Risk:RewardR:R
3.07 : 1
win $3.07 per $1
Expected P/LE[P/L]
+$243
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 30.6% | +$3,049 | +$933 |
| Resolves against (lose) | 69.4% | -$995 | -$690 |
| Expected value | 100.0% | — | +$243 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +6.0 pprelative edge +24.4%
Required win ratebreak-even
24.6%
price = implied probability
Model win rateP(win)
30.6%
what you forecast
Cushionedge
+6.0 pp
margin of safety
Fair pricemodel
0.306
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
24.6%
= price
Decimal oddsEU
4.065
total return per $1
AmericanUS
+307
$100 wins $307
FractionalUK
3.07 / 1
profit per $1 risked
Profit per $100stake
+$306.50
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 424% · APY 4341%ROI 24.4% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+24.4%
APR (simple)scaled
+424%
ROI × 365/days
APY (compounded)if redeployed
+4341%
(1+ROI)^(365/d) − 1
Daily expectedper day
+1.04%
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 +5.25 pperosion 13% · break-even w/ fees 25.4%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$1,989
7.96% · g = 0.924%
Half Kelly½ f★
$995
3.98% · g = 0.703%
Quarter Kelly¼ f★
$497
1.99% · g = 0.417%
Flat 1%1%
$250
1.00% · g = 0.226%
Flat 2%2%
$500
2.00% · g = 0.418%
Flat 5%5%
$1,250
5.00% · g = 0.803%
Recommended¼ f★
$497
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.805 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.889 bit
Δ +0.084 bit vs market
Surprise · YES−log₂ p
2.02 bit
self-information
Surprise · NO−log₂(1−p)
0.41 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0092 nat (0.0133 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 0.306 · CI [0.20, 0.43] · κ 58.0
Posterior meanE[θ]
0.306
Beta(17.7, 40.2)
95% credible intervalHDI
[0.20, 0.43]
price INSIDE → weak edge
Concentrationκ
58.0
pseudo-obs behind belief
Disagreementvs crowd
+6.0 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] +30.1% · P(YES) 32.0% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+30.08%
P(YES) empiricalq
32.0%
Best pathmax
+306.5%
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 0.74% · ruin rate 10.0%400 paths × 120 bets · f deploy 3.98%
Sharpe / betμ/σ
0.129
μ 0.96% · σ 7.4%
Sortino / betμ/σ↓
0.241
downside-only denominator
VaR 95%5%
-4.0%
per-bet worst-case
CVaR 95%ES
-4.0%
mean tail loss
Max drawdownMDD
-12.1%
Calmar 0.06
Ruin rate≤50%
10.0%
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 -20.3pp · crowd gap -26.3pp
Anchor gapmodel − base
-20.3 pp
Crowd gapprice − base
-26.3 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 19.4% · AUC 0.766out-of-sample BSS (5-fold) 19.4% ± 1.4% · Brier 0.2008 · log-loss 0.5991 · n 1600✓ n = 1600
BrierBS
0.2008
lower = better · ō 0.47
BSSvs base
19.4%
improvement over base rate
ReliabilityREL
0.0072
miscalibration · want ↓
ResolutionRES
0.0553
decisiveness · want ↑
Log lossLL
0.5991
cross-entropy
AUCROC
0.766
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 1.24 · expectancy +0.108R180 trades · win 55.0% · Sharpe 0.096
Total P/Lnet
+$4,848
on $45,000 cycled
Win ratehit %
55.0%
99 W / 81 L
Profit factorPF
1.24
$ won / $ lost
Expectancyper trade
+$26.94
avg $ per position
R-expectancyper risk
+0.108R
in units of risk taken
Avg win / losspayoff
$253.52 / -$250.00
ratio 1.01 : 1
Sharpe / traderisk-adj
0.096
μR / σR
Closing line valueCLV
+1.94 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.