NOSTRADAMUS · Position Analytics Engine
SIMULATOR Starmer out 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-starmer-out-by-june-30-2026-862-594-548-219-739-726 page.
▲ YES EDGE · +0.032 · f★ 7.3% · deploy 3.6% · net 2.41pp
§1 · Position economics
YES · Expected P/L per share +0.0316@ model P(YES) = 0.597
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 7.26% · g(f★) = 0.204%deploy 3.63% · g = 0.153%
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 @ 0.565 · EV +$51stake $907 · 3.63% of bankroll
Deployed stakestake
$907
3.63% of bankroll
Sharesunits
1,606
each pays $1 if YES
Max payoutwin
$1,606
gross, if win
Max profitwin
+$699
net of cost
Max losslose
-$907
binary settles to $0
Payout multiple×
×1.77
$1 → $1.77
Risk:RewardR:R
0.77 : 1
win $0.77 per $1
Expected P/LE[P/L]
+$51
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 59.7% | +$699 | +$417 |
| Resolves against (lose) | 40.3% | -$907 | -$366 |
| Expected value | 100.0% | — | +$51 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +3.2 pprelative edge +5.6%
Required win ratebreak-even
56.5%
price = implied probability
Model win rateP(win)
59.7%
what you forecast
Cushionedge
+3.2 pp
margin of safety
Fair pricemodel
0.597
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
56.5%
= price
Decimal oddsEU
1.770
total return per $1
AmericanUS
-130
risk $130 to win $100
FractionalUK
0.77 / 1
profit per $1 risked
Profit per $100stake
+$76.99
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 97% · APY 157%ROI 5.6% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+5.6%
APR (simple)scaled
+97%
ROI × 365/days
APY (compounded)if redeployed
+157%
(1+ROI)^(365/d) − 1
Daily expectedper day
+0.26%
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 +2.41 pperosion 24% · break-even w/ fees 57.2%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$1,815
7.26% · g = 0.204%
Half Kelly½ f★
$907
3.63% · g = 0.153%
Quarter Kelly¼ f★
$454
1.81% · g = 0.089%
Flat 1%1%
$250
1.00% · g = 0.052%
Flat 2%2%
$500
2.00% · g = 0.097%
Flat 5%5%
$1,250
5.00% · g = 0.184%
Recommended¼ f★
$454
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.988 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.973 bit
Δ -0.015 bit vs market
Surprise · YES−log₂ p
0.82 bit
self-information
Surprise · NO−log₂(1−p)
1.20 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0020 nat (0.0029 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 0.597 · CI [0.48, 0.71] · κ 65.9
Posterior meanE[θ]
0.597
Beta(39.3, 26.6)
95% credible intervalHDI
[0.48, 0.71]
price INSIDE → weak edge
Concentrationκ
65.9
pseudo-obs behind belief
Disagreementvs crowd
+3.2 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] +4.4% · P(YES) 59.0% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+4.42%
P(YES) empiricalq
59.0%
Best pathmax
+77.0%
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 0.12% · ruin rate 2.0%400 paths × 120 bets · f deploy 3.63%
Sharpe / betμ/σ
0.061
μ 0.19% · σ 3.2%
Sortino / betμ/σ↓
0.053
downside-only denominator
VaR 95%5%
-3.6%
per-bet worst-case
CVaR 95%ES
-3.6%
mean tail loss
Max drawdownMDD
-6.3%
Calmar 0.02
Ruin rate≤50%
2.0%
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 +0.3pp · crowd gap -2.9pp
Anchor gapmodel − base
+0.3 pp
Crowd gapprice − base
-2.9 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 20.0% · AUC 0.767out-of-sample BSS (5-fold) 20.4% ± 2.3% · Brier 0.2000 · log-loss 0.5930 · n 1600✓ n = 1600
BrierBS
0.2000
lower = better · ō 0.49
BSSvs base
20.0%
improvement over base rate
ReliabilityREL
0.0047
miscalibration · want ↓
ResolutionRES
0.0545
decisiveness · want ↑
Log lossLL
0.5930
cross-entropy
AUCROC
0.767
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)
BLEEDING · PF 0.95 · expectancy -0.023R180 trades · win 53.3% · Sharpe -0.023
Total P/Lnet
-$1,017
on $45,000 cycled
Win ratehit %
53.3%
96 W / 84 L
Profit factorPF
0.95
$ won / $ lost
Expectancyper trade
-$5.65
avg $ per position
R-expectancyper risk
-0.023R
in units of risk taken
Avg win / losspayoff
$208.15 / -$250.00
ratio 0.83 : 1
Sharpe / traderisk-adj
-0.023
μR / σR
Closing line valueCLV
+2.63 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.