NOSTRADAMUS · Position Analytics Engine
SIMULATOR Germany leading at halftime?
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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-fifwc-ger-kor-2026-06-14-halftime-result-home page.
▲ YES EDGE · +0.005 · f★ 3.0% · deploy 1.5% · net -0.26pp
§1 · Position economics
YES · Expected P/L per share +0.0049@ model P(YES) = 0.845
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 3.04% · g(f★) = 0.009%deploy 1.52% · g = 0.007%
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 @ 0.840 · EV +$2stake $380 · 1.52% of bankroll
Deployed stakestake
$380
1.52% of bankroll
Sharesunits
452
each pays $1 if YES
Max payoutwin
$452
gross, if win
Max profitwin
+$72
net of cost
Max losslose
-$380
binary settles to $0
Payout multiple×
×1.19
$1 → $1.19
Risk:RewardR:R
0.19 : 1
win $0.19 per $1
Expected P/LE[P/L]
+$2
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 84.5% | +$72 | +$61 |
| Resolves against (lose) | 15.5% | -$380 | -$59 |
| Expected value | 100.0% | — | +$2 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +0.5 pprelative edge +0.6%
Required win ratebreak-even
84.0%
price = implied probability
Model win rateP(win)
84.5%
what you forecast
Cushionedge
+0.5 pp
margin of safety
Fair pricemodel
0.845
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
84.0%
= price
Decimal oddsEU
1.190
total return per $1
AmericanUS
-525
risk $525 to win $100
FractionalUK
0.19 / 1
profit per $1 risked
Profit per $100stake
+$19.05
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 10% · APY 11%ROI 0.6% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+0.6%
APR (simple)scaled
+10%
ROI × 365/days
APY (compounded)if redeployed
+11%
(1+ROI)^(365/d) − 1
Daily expectedper day
+0.03%
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 -0.26 pperosion 154% · break-even w/ fees 84.7%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$759
3.04% · g = 0.009%
Half Kelly½ f★
$380
1.52% · g = 0.007%
Quarter Kelly¼ f★
$190
0.76% · g = 0.004%
Flat 1%1%
$250
1.00% · g = 0.005%
Flat 2%2%
$500
2.00% · g = 0.008%
Flat 5%5%
$1,250
5.00% · g = 0.005%
Recommended¼ f★
$190
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.634 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.623 bit
Δ -0.012 bit vs market
Surprise · YES−log₂ p
0.25 bit
self-information
Surprise · NO−log₂(1−p)
2.64 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0001 nat (0.0001 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 0.845 · CI [0.71, 0.94] · κ 35.4
Posterior meanE[θ]
0.845
Beta(29.9, 5.5)
95% credible intervalHDI
[0.71, 0.94]
price INSIDE → weak edge
Concentrationκ
35.4
pseudo-obs behind belief
Disagreementvs crowd
+0.5 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] +1.2% · P(YES) 85.0% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+1.19%
P(YES) empiricalq
85.0%
Best pathmax
+19.0%
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 0.02% · ruin rate 0.0%400 paths × 120 bets · f deploy 1.52%
Sharpe / betμ/σ
0.014
μ 0.01% · σ 0.7%
Sortino / betμ/σ↓
0.006
downside-only denominator
VaR 95%5%
-1.5%
per-bet worst-case
CVaR 95%ES
-1.5%
mean tail loss
Max drawdownMDD
-2.1%
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 +39.5pp · crowd gap +39.0pp
Anchor gapmodel − base
+39.5 pp
Crowd gapprice − base
+39.0 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 20.1% · AUC 0.767out-of-sample BSS (5-fold) 20.2% ± 2.2% · Brier 0.1997 · log-loss 0.5967 · n 1600✓ n = 1600
BrierBS
0.1997
lower = better · ō 0.50
BSSvs base
20.1%
improvement over base rate
ReliabilityREL
0.0039
miscalibration · want ↓
ResolutionRES
0.0530
decisiveness · want ↑
Log lossLL
0.5967
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)
PROFITABLE · PF 1.01 · expectancy +0.005R180 trades · win 50.6% · Sharpe 0.005
Total P/Lnet
+$242
on $45,000 cycled
Win ratehit %
50.6%
91 W / 89 L
Profit factorPF
1.01
$ won / $ lost
Expectancyper trade
+$1.35
avg $ per position
R-expectancyper risk
+0.005R
in units of risk taken
Avg win / losspayoff
$247.17 / -$250.00
ratio 0.99 : 1
Sharpe / traderisk-adj
0.005
μR / σR
Closing line valueCLV
+3.72 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.