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 · +0.018 · f★ 13.0% · deploy 6.5% · net 1.07pp
§1 · Position economics
YES · Expected P/L per share +0.0182@ model P(YES) = 0.878
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 13.03% · g(f★) = 0.144%deploy 6.52% · g = 0.106%
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 @ 0.860 · EV +$35stake $1,629 · 6.52% of bankroll
Deployed stakestake
$1,629
6.52% of bankroll
Sharesunits
1,894
each pays $1 if YES
Max payoutwin
$1,894
gross, if win
Max profitwin
+$265
net of cost
Max losslose
-$1,629
binary settles to $0
Payout multiple×
×1.16
$1 → $1.16
Risk:RewardR:R
0.16 : 1
win $0.16 per $1
Expected P/LE[P/L]
+$35
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 87.8% | +$265 | +$233 |
| Resolves against (lose) | 12.2% | -$1,629 | -$198 |
| Expected value | 100.0% | — | +$35 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +1.8 pprelative edge +2.1%
Required win ratebreak-even
86.0%
price = implied probability
Model win rateP(win)
87.8%
what you forecast
Cushionedge
+1.8 pp
margin of safety
Fair pricemodel
0.878
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
86.0%
= price
Decimal oddsEU
1.163
total return per $1
AmericanUS
-614
risk $614 to win $100
FractionalUK
0.16 / 1
profit per $1 risked
Profit per $100stake
+$16.28
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 37% · APY 44%ROI 2.1% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+2.1%
APR (simple)scaled
+37%
ROI × 365/days
APY (compounded)if redeployed
+44%
(1+ROI)^(365/d) − 1
Daily expectedper day
+0.10%
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 +1.07 pperosion 41% · break-even w/ fees 86.8%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$3,258
13.03% · g = 0.144%
Half Kelly½ f★
$1,629
6.52% · g = 0.106%
Quarter Kelly¼ f★
$814
3.26% · g = 0.061%
Flat 1%1%
$250
1.00% · g = 0.020%
Flat 2%2%
$500
2.00% · g = 0.039%
Flat 5%5%
$1,250
5.00% · g = 0.087%
Recommended¼ f★
$814
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.584 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.534 bit
Δ -0.050 bit vs market
Surprise · YES−log₂ p
0.22 bit
self-information
Surprise · NO−log₂(1−p)
2.84 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0014 nat (0.0021 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 0.878 · CI [0.74, 0.97] · κ 28.7
Posterior meanE[θ]
0.878
Beta(25.2, 3.5)
95% credible intervalHDI
[0.74, 0.97]
price INSIDE → weak edge
Concentrationκ
28.7
pseudo-obs behind belief
Disagreementvs crowd
+1.8 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) 84.8% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
-1.45%
P(YES) empiricalq
84.8%
Best pathmax
+16.3%
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 0.08% · ruin rate 0.8%400 paths × 120 bets · f deploy 6.52%
Sharpe / betμ/σ
0.052
μ 0.13% · σ 2.5%
Sortino / betμ/σ↓
0.020
downside-only denominator
VaR 95%5%
-6.5%
per-bet worst-case
CVaR 95%ES
-6.5%
mean tail loss
Max drawdownMDD
-7.9%
Calmar 0.01
Ruin rate≤50%
0.8%
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 +36.1pp · crowd gap +34.3pp
Anchor gapmodel − base
+36.1 pp
Crowd gapprice − base
+34.3 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.