NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Keir Starmer be the next leader out before 2027?
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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-keir-starmer-be-the-next-leader-out-before-2027-565 page.
▲ YES EDGE · +0.016 · f★ 5.2% · deploy 2.6% · net 0.90pp
§1 · Position economics
YES · Expected P/L per share +0.0165@ model P(YES) = 0.701
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 5.24% · g(f★) = 0.064%deploy 2.62% · g = 0.048%
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 @ 0.685 · EV +$16stake $655 · 2.62% of bankroll
Deployed stakestake
$655
2.62% of bankroll
Sharesunits
955
each pays $1 if YES
Max payoutwin
$955
gross, if win
Max profitwin
+$301
net of cost
Max losslose
-$655
binary settles to $0
Payout multiple×
×1.46
$1 → $1.46
Risk:RewardR:R
0.46 : 1
win $0.46 per $1
Expected P/LE[P/L]
+$16
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 70.1% | +$301 | +$211 |
| Resolves against (lose) | 29.9% | -$655 | -$195 |
| Expected value | 100.0% | — | +$16 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +1.6 pprelative edge +2.4%
Required win ratebreak-even
68.5%
price = implied probability
Model win rateP(win)
70.1%
what you forecast
Cushionedge
+1.6 pp
margin of safety
Fair pricemodel
0.701
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
68.5%
= price
Decimal oddsEU
1.460
total return per $1
AmericanUS
-217
risk $217 to win $100
FractionalUK
0.46 / 1
profit per $1 risked
Profit per $100stake
+$45.99
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 42% · APY 51%ROI 2.4% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+2.4%
APR (simple)scaled
+42%
ROI × 365/days
APY (compounded)if redeployed
+51%
(1+ROI)^(365/d) − 1
Daily expectedper day
+0.11%
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 +0.90 pperosion 45% · break-even w/ fees 69.3%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$1,309
5.24% · g = 0.064%
Half Kelly½ f★
$655
2.62% · g = 0.048%
Quarter Kelly¼ f★
$327
1.31% · g = 0.028%
Flat 1%1%
$250
1.00% · g = 0.022%
Flat 2%2%
$500
2.00% · g = 0.039%
Flat 5%5%
$1,250
5.00% · g = 0.064%
Recommended¼ f★
$327
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.899 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.879 bit
Δ -0.019 bit vs market
Surprise · YES−log₂ p
0.55 bit
self-information
Surprise · NO−log₂(1−p)
1.67 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0006 nat (0.0009 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 0.701 · CI [0.58, 0.81] · κ 57.2
Posterior meanE[θ]
0.701
Beta(40.1, 17.1)
95% credible intervalHDI
[0.58, 0.81]
price INSIDE → weak edge
Concentrationκ
57.2
pseudo-obs behind belief
Disagreementvs crowd
+1.6 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] -1.1% · P(YES) 67.8% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
-1.09%
P(YES) empiricalq
67.8%
Best pathmax
+46.0%
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 0.04% · ruin rate 0.0%400 paths × 120 bets · f deploy 2.62%
Sharpe / betμ/σ
0.033
μ 0.06% · σ 1.8%
Sortino / betμ/σ↓
0.022
downside-only denominator
VaR 95%5%
-2.6%
per-bet worst-case
CVaR 95%ES
-2.6%
mean tail loss
Max drawdownMDD
-4.3%
Calmar 0.01
Ruin rate≤50%
0.0%
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 +13.6pp · crowd gap +12.0pp
Anchor gapmodel − base
+13.6 pp
Crowd gapprice − base
+12.0 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 20.3% · AUC 0.767out-of-sample BSS (5-fold) 20.6% ± 1.5% · Brier 0.1991 · log-loss 0.5946 · n 1600✓ n = 1600
BrierBS
0.1991
lower = better · ō 0.52
BSSvs base
20.3%
improvement over base rate
ReliabilityREL
0.0042
miscalibration · want ↓
ResolutionRES
0.0548
decisiveness · want ↑
Log lossLL
0.5946
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 0.86 · expectancy -0.076R180 trades · win 45.6% · Sharpe -0.067
Total P/Lnet
-$3,435
on $45,000 cycled
Win ratehit %
45.6%
82 W / 98 L
Profit factorPF
0.86
$ won / $ lost
Expectancyper trade
-$19.08
avg $ per position
R-expectancyper risk
-0.076R
in units of risk taken
Avg win / losspayoff
$256.89 / -$250.00
ratio 1.03 : 1
Sharpe / traderisk-adj
-0.067
μR / σR
Closing line valueCLV
+2.44 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.