NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Iran close its airspace by July 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-july-15-20260609184136055 page.
▲ YES EDGE · +0.055 · f★ 6.4% · deploy 3.2% · net 4.76pp
§1 · Position economics
YES · Expected P/L per share +0.0551@ model P(YES) = 0.200
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 6.45% · g(f★) = 1.117%deploy 3.22% · g = 0.862%
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 @ 0.145 · EV +$306stake $806 · 3.22% of bankroll
Deployed stakestake
$806
3.22% of bankroll
Sharesunits
5,558
each pays $1 if YES
Max payoutwin
$5,558
gross, if win
Max profitwin
+$4,752
net of cost
Max losslose
-$806
binary settles to $0
Payout multiple×
×6.90
$1 → $6.90
Risk:RewardR:R
5.90 : 1
win $5.90 per $1
Expected P/LE[P/L]
+$306
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 20.0% | +$4,752 | +$951 |
| Resolves against (lose) | 80.0% | -$806 | -$645 |
| Expected value | 100.0% | — | +$306 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +5.5 pprelative edge +38.0%
Required win ratebreak-even
14.5%
price = implied probability
Model win rateP(win)
20.0%
what you forecast
Cushionedge
+5.5 pp
margin of safety
Fair pricemodel
0.200
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
14.5%
= price
Decimal oddsEU
6.897
total return per $1
AmericanUS
+590
$100 wins $590
FractionalUK
5.90 / 1
profit per $1 risked
Profit per $100stake
+$589.66
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 661% · APY 26941%ROI 38.0% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+38.0%
APR (simple)scaled
+661%
ROI × 365/days
APY (compounded)if redeployed
+26941%
(1+ROI)^(365/d) − 1
Daily expectedper day
+1.55%
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 +4.76 pperosion 14% · break-even w/ fees 15.3%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$1,612
6.45% · g = 1.117%
Half Kelly½ f★
$806
3.22% · g = 0.862%
Quarter Kelly¼ f★
$403
1.61% · g = 0.517%
Flat 1%1%
$250
1.00% · g = 0.343%
Flat 2%2%
$500
2.00% · g = 0.615%
Flat 5%5%
$1,250
5.00% · g = 1.068%
Recommended¼ f★
$403
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.597 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.722 bit
Δ +0.125 bit vs market
Surprise · YES−log₂ p
2.79 bit
self-information
Surprise · NO−log₂(1−p)
0.23 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0112 nat (0.0161 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 0.200 · CI [0.10, 0.33] · κ 43.5
Posterior meanE[θ]
0.200
Beta(8.7, 34.8)
95% credible intervalHDI
[0.10, 0.33]
price INSIDE → weak edge
Concentrationκ
43.5
pseudo-obs behind belief
Disagreementvs crowd
+5.5 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] +24.1% · P(YES) 18.0% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+24.14%
P(YES) empiricalq
18.0%
Best pathmax
+589.7%
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 0.86% · ruin rate 10.8%400 paths × 120 bets · f deploy 3.22%
Sharpe / betμ/σ
0.138
μ 1.23% · σ 8.9%
Sortino / betμ/σ↓
0.382
downside-only denominator
VaR 95%5%
-3.2%
per-bet worst-case
CVaR 95%ES
-3.2%
mean tail loss
Max drawdownMDD
-15.1%
Calmar 0.06
Ruin rate≤50%
10.8%
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 -32.9pp · crowd gap -38.4pp
Anchor gapmodel − base
-32.9 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 19.5% · AUC 0.763out-of-sample BSS (5-fold) 19.6% ± 2.1% · Brier 0.2013 · log-loss 0.5992 · n 1600✓ n = 1600
BrierBS
0.2013
lower = better · ō 0.50
BSSvs base
19.5%
improvement over base rate
ReliabilityREL
0.0041
miscalibration · want ↓
ResolutionRES
0.0526
decisiveness · want ↑
Log lossLL
0.5992
cross-entropy
AUCROC
0.763
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 1.15 · expectancy +0.074R180 trades · win 51.7% · Sharpe 0.063
Total P/Lnet
+$3,314
on $45,000 cycled
Win ratehit %
51.7%
93 W / 87 L
Profit factorPF
1.15
$ won / $ lost
Expectancyper trade
+$18.41
avg $ per position
R-expectancyper risk
+0.074R
in units of risk taken
Avg win / losspayoff
$269.51 / -$250.00
ratio 1.08 : 1
Sharpe / traderisk-adj
0.063
μR / σR
Closing line valueCLV
+2.54 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.