NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Anhelina Kalinina win the Sun vs Kalinina: Qualification Round 1 match?
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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-kxwtamatch-26jun13sunkal-kal page.
▲ YES EDGE · +0.021 · f★ 19.1% · deploy 9.5% · net 1.35pp
§1 · Position economics
YES · Expected P/L per share +0.0210@ model P(YES) = 0.911
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 19.10% · g(f★) = 0.239%deploy 9.55% · g = 0.176%
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 @ 0.890 · EV +$56stake $2,387 · 9.55% of bankroll
Deployed stakestake
$2,387
9.55% of bankroll
Sharesunits
2,682
each pays $1 if YES
Max payoutwin
$2,682
gross, if win
Max profitwin
+$295
net of cost
Max losslose
-$2,387
binary settles to $0
Payout multiple×
×1.12
$1 → $1.12
Risk:RewardR:R
0.12 : 1
win $0.12 per $1
Expected P/LE[P/L]
+$56
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 91.1% | +$295 | +$269 |
| Resolves against (lose) | 8.9% | -$2,387 | -$212 |
| Expected value | 100.0% | — | +$56 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +2.1 pprelative edge +2.4%
Required win ratebreak-even
89.0%
price = implied probability
Model win rateP(win)
91.1%
what you forecast
Cushionedge
+2.1 pp
margin of safety
Fair pricemodel
0.911
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
89.0%
= price
Decimal oddsEU
1.124
total return per $1
AmericanUS
-809
risk $809 to win $100
FractionalUK
0.12 / 1
profit per $1 risked
Profit per $100stake
+$12.36
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 41% · APY 50%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
+41%
ROI × 365/days
APY (compounded)if redeployed
+50%
(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 +1.35 pperosion 36% · break-even w/ fees 89.8%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$4,774
19.10% · g = 0.239%
Half Kelly½ f★
$2,387
9.55% · g = 0.176%
Quarter Kelly¼ f★
$1,194
4.77% · g = 0.101%
Flat 1%1%
$250
1.00% · g = 0.023%
Flat 2%2%
$500
2.00% · g = 0.045%
Flat 5%5%
$1,250
5.00% · g = 0.105%
Recommended¼ f★
$1,194
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)
0.433 bit
Δ -0.067 bit vs market
Surprise · YES−log₂ p
0.17 bit
self-information
Surprise · NO−log₂(1−p)
3.18 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0024 nat (0.0035 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 0.911 · CI [0.76, 0.99] · κ 21.5
Posterior meanE[θ]
0.911
Beta(19.6, 1.9)
95% credible intervalHDI
[0.76, 0.99]
price INSIDE → weak edge
Concentrationκ
21.5
pseudo-obs behind belief
Disagreementvs crowd
+2.1 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] +1.1% · P(YES) 90.0% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+1.12%
P(YES) empiricalq
90.0%
Best pathmax
+12.4%
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 0.15% · ruin rate 2.8%400 paths × 120 bets · f deploy 9.55%
Sharpe / betμ/σ
0.064
μ 0.20% · σ 3.1%
Sortino / betμ/σ↓
0.021
downside-only denominator
VaR 95%5%
-9.5%
per-bet worst-case
CVaR 95%ES
-9.5%
mean tail loss
Max drawdownMDD
-10.1%
Calmar 0.01
Ruin rate≤50%
2.8%
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 +39.4pp · crowd gap +37.3pp
Anchor gapmodel − base
+39.4 pp
Crowd gapprice − base
+37.3 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 15.7% · AUC 0.744out-of-sample BSS (5-fold) 15.7% ± 1.9% · Brier 0.2108 · log-loss 0.6278 · n 1600✓ n = 1600
BrierBS
0.2108
lower = better · ō 0.49
BSSvs base
15.7%
improvement over base rate
ReliabilityREL
0.0076
miscalibration · want ↓
ResolutionRES
0.0462
decisiveness · want ↑
Log lossLL
0.6278
cross-entropy
AUCROC
0.744
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 0.84 · expectancy -0.087R180 trades · win 43.9% · Sharpe -0.076
Total P/Lnet
-$3,927
on $45,000 cycled
Win ratehit %
43.9%
79 W / 101 L
Profit factorPF
0.84
$ won / $ lost
Expectancyper trade
-$21.82
avg $ per position
R-expectancyper risk
-0.087R
in units of risk taken
Avg win / losspayoff
$269.91 / -$250.00
ratio 1.08 : 1
Sharpe / traderisk-adj
-0.076
μR / σR
Closing line valueCLV
+3.26 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.