NOSTRADAMUS · Position Analytics Engine
SIMULATOR India vs Pakistan Winner?
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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-kxwt20match-26jun140930pakind-pak page.
▲ YES EDGE · +0.019 · f★ 2.1% · deploy 1.1% · net 1.15pp
§1 · Position economics
YES · Expected P/L per share +0.0190@ model P(YES) = 0.129
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 2.13% · g(f★) = 0.175%deploy 1.07% · g = 0.133%
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 @ 0.110 · EV +$46stake $266 · 1.07% of bankroll
Deployed stakestake
$266
1.07% of bankroll
Sharesunits
2,421
each pays $1 if YES
Max payoutwin
$2,421
gross, if win
Max profitwin
+$2,155
net of cost
Max losslose
-$266
binary settles to $0
Payout multiple×
×9.09
$1 → $9.09
Risk:RewardR:R
8.09 : 1
win $8.09 per $1
Expected P/LE[P/L]
+$46
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 12.9% | +$2,155 | +$278 |
| Resolves against (lose) | 87.1% | -$266 | -$232 |
| Expected value | 100.0% | — | +$46 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +1.9 pprelative edge +17.2%
Required win ratebreak-even
11.0%
price = implied probability
Model win rateP(win)
12.9%
what you forecast
Cushionedge
+1.9 pp
margin of safety
Fair pricemodel
0.129
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
11.0%
= price
Decimal oddsEU
9.091
total return per $1
AmericanUS
+809
$100 wins $809
FractionalUK
8.09 / 1
profit per $1 risked
Profit per $100stake
+$809.09
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 300% · APY 1487%ROI 17.2% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+17.2%
APR (simple)scaled
+300%
ROI × 365/days
APY (compounded)if redeployed
+1487%
(1+ROI)^(365/d) − 1
Daily expectedper day
+0.76%
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 +1.15 pperosion 40% · break-even w/ fees 11.8%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$533
2.13% · g = 0.175%
Half Kelly½ f★
$266
1.07% · g = 0.133%
Quarter Kelly¼ f★
$133
0.53% · g = 0.079%
Flat 1%1%
$250
1.00% · g = 0.128%
Flat 2%2%
$500
2.00% · g = 0.175%
Flat 5%5%
$1,250
5.00% · g = -0.087%
Recommended¼ f★
$133
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.500 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.555 bit
Δ +0.055 bit vs market
Surprise · YES−log₂ p
3.18 bit
self-information
Surprise · NO−log₂(1−p)
0.17 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0018 nat (0.0025 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 0.129 · CI [0.04, 0.27] · κ 30.2
Posterior meanE[θ]
0.129
Beta(3.9, 26.3)
95% credible intervalHDI
[0.04, 0.27]
price INSIDE → weak edge
Concentrationκ
30.2
pseudo-obs behind belief
Disagreementvs crowd
+1.9 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] +0.0% · P(YES) 11.0% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+0.00%
P(YES) empiricalq
11.0%
Best pathmax
+809.1%
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 0.17% · ruin rate 0.3%400 paths × 120 bets · f deploy 1.07%
Sharpe / betμ/σ
0.060
μ 0.20% · σ 3.3%
Sortino / betμ/σ↓
0.183
downside-only denominator
VaR 95%5%
-1.1%
per-bet worst-case
CVaR 95%ES
-1.1%
mean tail loss
Max drawdownMDD
-9.2%
Calmar 0.02
Ruin rate≤50%
0.3%
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 -38.5pp · crowd gap -40.4pp
Anchor gapmodel − base
-38.5 pp
Crowd gapprice − base
-40.4 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 21.7% · AUC 0.774out-of-sample BSS (5-fold) 21.7% ± 2.3% · Brier 0.1958 · log-loss 0.5835 · n 1600✓ n = 1600
BrierBS
0.1958
lower = better · ō 0.50
BSSvs base
21.7%
improvement over base rate
ReliabilityREL
0.0030
miscalibration · want ↓
ResolutionRES
0.0585
decisiveness · want ↑
Log lossLL
0.5835
cross-entropy
AUCROC
0.774
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 +0.034R180 trades · win 53.9% · Sharpe 0.030
Total P/Lnet
+$1,512
on $45,000 cycled
Win ratehit %
53.9%
97 W / 83 L
Profit factorPF
1.07
$ won / $ lost
Expectancyper trade
+$8.40
avg $ per position
R-expectancyper risk
+0.034R
in units of risk taken
Avg win / losspayoff
$229.51 / -$250.00
ratio 0.92 : 1
Sharpe / traderisk-adj
0.030
μR / σR
Closing line valueCLV
+2.82 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.