NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Germany score over 0.5 goals?
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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/kalshi-kxwcteamtotal-26jun14gercuw-ger1 page.
▲ YES EDGE · +0.001 · f★ 2.5% · deploy 1.3% · net -0.67pp
§1 · Position economics
YES · Expected P/L per share +0.0008@ model P(YES) = 0.971
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 2.50% · g(f★) = 0.001%deploy 1.25% · 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 @ 0.970 · EV +$0stake $313 · 1.25% of bankroll
Deployed stakestake
$313
1.25% of bankroll
Sharesunits
322
each pays $1 if YES
Max payoutwin
$322
gross, if win
Max profitwin
+$10
net of cost
Max losslose
-$313
binary settles to $0
Payout multiple×
×1.03
$1 → $1.03
Risk:RewardR:R
0.03 : 1
win $0.03 per $1
Expected P/LE[P/L]
+$0
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 97.1% | +$10 | +$9 |
| Resolves against (lose) | 2.9% | -$313 | -$9 |
| 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 +0.1 pprelative edge +0.1%
Required win ratebreak-even
97.0%
price = implied probability
Model win rateP(win)
97.1%
what you forecast
Cushionedge
+0.1 pp
margin of safety
Fair pricemodel
0.971
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
97.0%
= price
Decimal oddsEU
1.031
total return per $1
AmericanUS
-3233
risk $3233 to win $100
FractionalUK
0.03 / 1
profit per $1 risked
Profit per $100stake
+$3.09
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 1% · APY 1%ROI 0.1% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+0.1%
APR (simple)scaled
+1%
ROI × 365/days
APY (compounded)if redeployed
+1%
(1+ROI)^(365/d) − 1
Daily expectedper day
+0.00%
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 -0.67 pperosion 999% · break-even w/ fees 97.7%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$626
2.50% · g = 0.001%
Half Kelly½ f★
$313
1.25% · g = 0.001%
Quarter Kelly¼ f★
$156
0.63% · g = 0.000%
Flat 1%1%
$250
1.00% · g = 0.001%
Flat 2%2%
$500
2.00% · g = 0.001%
Flat 5%5%
$1,250
5.00% · g = -0.000%
Recommended¼ f★
$156
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.194 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.191 bit
Δ -0.004 bit vs market
Surprise · YES−log₂ p
0.04 bit
self-information
Surprise · NO−log₂(1−p)
5.06 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 0.971 · CI [0.76, 1.00] · κ 6.9
Posterior meanE[θ]
0.971
Beta(6.7, 0.2)
95% credible intervalHDI
[0.76, 1.00]
price INSIDE → weak edge
Concentrationκ
6.9
pseudo-obs behind belief
Disagreementvs crowd
+0.1 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] +1.5% · P(YES) 98.5% · VaR₉₅ -3.1%400 paths · 504 bars to resolution
Expected P/Lper $1
+1.55%
P(YES) empiricalq
98.5%
Best pathmax
+3.1%
Worst pathmin
-100.0%
VaR 95%5%
-3.1%
CVaR 95%ES
26.4%
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 1.25%
Sharpe / betμ/σ
-0.074
μ -0.02% · σ 0.3%
Sortino / betμ/σ↓
-0.016
downside-only denominator
VaR 95%5%
0.0%
per-bet worst-case
CVaR 95%ES
-0.0%
mean tail loss
Max drawdownMDD
-3.0%
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 +38.9pp · crowd gap +38.8pp
Anchor gapmodel − base
+38.9 pp
Crowd gapprice − base
+38.8 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 18.9% · AUC 0.763out-of-sample BSS (5-fold) 19.2% ± 2.2% · Brier 0.2023 · log-loss 0.6078 · n 1600✓ n = 1600
BrierBS
0.2023
lower = better · ō 0.52
BSSvs base
18.9%
improvement over base rate
ReliabilityREL
0.0047
miscalibration · want ↓
ResolutionRES
0.0517
decisiveness · want ↑
Log lossLL
0.6078
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 1.07 · expectancy +0.035R180 trades · win 51.1% · Sharpe 0.029
Total P/Lnet
+$1,567
on $45,000 cycled
Win ratehit %
51.1%
92 W / 88 L
Profit factorPF
1.07
$ won / $ lost
Expectancyper trade
+$8.71
avg $ per position
R-expectancyper risk
+0.035R
in units of risk taken
Avg win / losspayoff
$256.17 / -$250.00
ratio 1.02 : 1
Sharpe / traderisk-adj
0.029
μR / σR
Closing line valueCLV
+2.90 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.