NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Tom Kim win the 2026 U.S. Open?
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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-2026-us-open-winner-tom-kim-win page.
▲ YES EDGE · +0.022 · f★ 2.2% · deploy 1.1% · net 1.46pp
§1 · Position economics
YES · Expected P/L per share +0.0221@ model P(YES) = 0.026
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 2.22% · g(f★) = 2.910%deploy 1.11% · g = 2.563%
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 @ 0.004 · EV +$1,752stake $277 · 1.11% of bankroll
Deployed stakestake
$277
1.11% of bankroll
Sharesunits
79,238
each pays $1 if YES
Max payoutwin
$79,238
gross, if win
Max profitwin
+$78,961
net of cost
Max losslose
-$277
binary settles to $0
Payout multiple×
×285.71
$1 → $285.71
Risk:RewardR:R
284.71 : 1
win $284.71 per $1
Expected P/LE[P/L]
+$1,752
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 2.6% | +$78,961 | +$2,022 |
| Resolves against (lose) | 97.4% | -$277 | -$270 |
| Expected value | 100.0% | — | +$1,752 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +2.2 pprelative edge +631.7%
Required win ratebreak-even
0.4%
price = implied probability
Model win rateP(win)
2.6%
what you forecast
Cushionedge
+2.2 pp
margin of safety
Fair pricemodel
0.026
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
0.4%
= price
Decimal oddsEU
285.714
total return per $1
AmericanUS
+28471
$100 wins $28471
FractionalUK
284.71 / 1
profit per $1 risked
Profit per $100stake
+$28471.43
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 10979% · APY 105385067115612736%ROI 631.7% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+631.7%
APR (simple)scaled
+10979%
ROI × 365/days
APY (compounded)if redeployed
+105385067115612736%
(1+ROI)^(365/d) − 1
Daily expectedper day
+9.94%
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 +1.46 pperosion 34% · break-even w/ fees 1.1%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$555
2.22% · g = 2.910%
Half Kelly½ f★
$277
1.11% · g = 2.563%
Quarter Kelly¼ f★
$139
0.55% · g = 1.884%
Flat 1%1%
$250
1.00% · g = 2.471%
Flat 2%2%
$500
2.00% · g = 2.900%
Flat 5%5%
$1,250
5.00% · g = 1.977%
Recommended¼ f★
$139
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.034 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.172 bit
Δ +0.138 bit vs market
Surprise · YES−log₂ p
8.16 bit
self-information
Surprise · NO−log₂(1−p)
0.01 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
SIGNAL · D_KL(q ‖ p) = 0.0291 nat (0.0420 bit)exploitable edge present
YES contributionNO contributionbelief ‖ marketsignal
Zero KL ⇒ you know nothing the crowd doesn't.
§8 · Bayesian inference
MARKET PRICE INSIDE 95% CIposterior μ 0.026 · CI [0.00, 0.26] · κ 5.9
Posterior meanE[θ]
0.026
Beta(0.2, 5.8)
95% credible intervalHDI
[0.00, 0.26]
price INSIDE → weak edge
Concentrationκ
5.9
pseudo-obs behind belief
Disagreementvs crowd
+0.6 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] +828.6% · P(YES) 3.3% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+828.57%
P(YES) empiricalq
3.3%
Best pathmax
+28471.4%
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 4.99% · ruin rate 8.8%400 paths × 120 bets · f deploy 1.11%
Sharpe / betμ/σ
0.194
μ 12.45% · σ 64.1%
Sortino / betμ/σ↓
11.226
downside-only denominator
VaR 95%5%
-1.1%
per-bet worst-case
CVaR 95%ES
-1.1%
mean tail loss
Max drawdownMDD
-24.3%
Calmar 0.21
Ruin rate≤50%
8.8%
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 -48.2pp · crowd gap -50.5pp
Anchor gapmodel − base
-48.2 pp
Crowd gapprice − base
-50.5 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 17.3% · AUC 0.756out-of-sample BSS (5-fold) 17.4% ± 1.9% · Brier 0.2063 · log-loss 0.6131 · n 1600✓ n = 1600
BrierBS
0.2063
lower = better · ō 0.52
BSSvs base
17.3%
improvement over base rate
ReliabilityREL
0.0065
miscalibration · want ↓
ResolutionRES
0.0490
decisiveness · want ↑
Log lossLL
0.6131
cross-entropy
AUCROC
0.756
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 0.89 · expectancy -0.063R180 trades · win 43.3% · Sharpe -0.049
Total P/Lnet
-$2,826
on $45,000 cycled
Win ratehit %
43.3%
78 W / 102 L
Profit factorPF
0.89
$ won / $ lost
Expectancyper trade
-$15.70
avg $ per position
R-expectancyper risk
-0.063R
in units of risk taken
Avg win / losspayoff
$290.69 / -$250.00
ratio 1.16 : 1
Sharpe / traderisk-adj
-0.049
μR / σR
Closing line valueCLV
+2.75 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.