NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Robert Kenyon win the 2026 Makerfield by-election?
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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-robert-kenyon-win-the-2026-makerfield-by-election page.
▲ YES EDGE · +0.002 · f★ 0.3% · deploy 0.1% · net -0.55pp
§1 · Position economics
YES · Expected P/L per share +0.0020@ model P(YES) = 0.267
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 0.27% · g(f★) = 0.001%deploy 0.13% · g = 0.001%
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 @ 0.265 · EV +$0stake $33 · 0.13% of bankroll
Deployed stakestake
$33
0.13% of bankroll
Sharesunits
126
each pays $1 if YES
Max payoutwin
$126
gross, if win
Max profitwin
+$93
net of cost
Max losslose
-$33
binary settles to $0
Payout multiple×
×3.77
$1 → $3.77
Risk:RewardR:R
2.77 : 1
win $2.77 per $1
Expected P/LE[P/L]
+$0
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 26.7% | +$93 | +$25 |
| Resolves against (lose) | 73.3% | -$33 | -$24 |
| Expected value | 100.0% | — | +$0 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +0.2 pprelative edge +0.7%
Required win ratebreak-even
26.5%
price = implied probability
Model win rateP(win)
26.7%
what you forecast
Cushionedge
+0.2 pp
margin of safety
Fair pricemodel
0.267
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
26.5%
= price
Decimal oddsEU
3.774
total return per $1
AmericanUS
+277
$100 wins $277
FractionalUK
2.77 / 1
profit per $1 risked
Profit per $100stake
+$277.36
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 13% · APY 14%ROI 0.7% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+0.7%
APR (simple)scaled
+13%
ROI × 365/days
APY (compounded)if redeployed
+14%
(1+ROI)^(365/d) − 1
Daily expectedper day
+0.04%
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 -0.55 pperosion 382% · break-even w/ fees 27.3%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$67
0.27% · g = 0.001%
Half Kelly½ f★
$33
0.13% · g = 0.001%
Quarter Kelly¼ f★
$17
0.07% · g = 0.000%
Flat 1%1%
$250
1.00% · g = -0.006%
Flat 2%2%
$500
2.00% · g = -0.040%
Flat 5%5%
$1,250
5.00% · g = -0.293%
Recommended¼ f★
$17
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.834 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.837 bit
Δ +0.003 bit vs market
Surprise · YES−log₂ p
1.92 bit
self-information
Surprise · NO−log₂(1−p)
0.44 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0000 nat (0.0000 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 0.267 · CI [0.16, 0.39] · κ 53.4
Posterior meanE[θ]
0.267
Beta(14.2, 39.1)
95% credible intervalHDI
[0.16, 0.39]
price INSIDE → weak edge
Concentrationκ
53.4
pseudo-obs behind belief
Disagreementvs crowd
+0.2 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] -13.2% · P(YES) 23.0% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
-13.21%
P(YES) empiricalq
23.0%
Best pathmax
+277.4%
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 -0.00% · ruin rate 0.0%400 paths × 120 bets · f deploy 0.50%
Sharpe / betμ/σ
0.011
μ 0.01% · σ 0.8%
Sortino / betμ/σ↓
0.019
downside-only denominator
VaR 95%5%
-0.5%
per-bet worst-case
CVaR 95%ES
-0.5%
mean tail loss
Max drawdownMDD
-2.1%
Calmar -0.00
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 -29.8pp · crowd gap -30.0pp
Anchor gapmodel − base
-29.8 pp
Crowd gapprice − base
-30.0 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 20.5% · AUC 0.770out-of-sample BSS (5-fold) 20.5% ± 2.0% · Brier 0.1987 · log-loss 0.5936 · n 1600✓ n = 1600
BrierBS
0.1987
lower = better · ō 0.50
BSSvs base
20.5%
improvement over base rate
ReliabilityREL
0.0043
miscalibration · want ↓
ResolutionRES
0.0563
decisiveness · want ↑
Log lossLL
0.5936
cross-entropy
AUCROC
0.770
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 1.39 · expectancy +0.173R180 trades · win 56.1% · Sharpe 0.148
Total P/Lnet
+$7,781
on $45,000 cycled
Win ratehit %
56.1%
101 W / 79 L
Profit factorPF
1.39
$ won / $ lost
Expectancyper trade
+$43.23
avg $ per position
R-expectancyper risk
+0.173R
in units of risk taken
Avg win / losspayoff
$272.58 / -$250.00
ratio 1.09 : 1
Sharpe / traderisk-adj
0.148
μR / σR
Closing line valueCLV
+2.15 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.