NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Justin Rose 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-justin-rose-win page.
▲ YES EDGE · +0.034 · f★ 3.4% · deploy 1.7% · net 2.61pp
§1 · Position economics
YES · Expected P/L per share +0.0336@ model P(YES) = 0.049
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 3.41% · g(f★) = 2.357%deploy 1.71% · g = 1.966%
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 @ 0.015 · EV +$924stake $426 · 1.71% of bankroll
Deployed stakestake
$426
1.71% of bankroll
Sharesunits
27,505
each pays $1 if YES
Max payoutwin
$27,505
gross, if win
Max profitwin
+$27,079
net of cost
Max losslose
-$426
binary settles to $0
Payout multiple×
×64.52
$1 → $64.52
Risk:RewardR:R
63.52 : 1
win $63.52 per $1
Expected P/LE[P/L]
+$924
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 4.9% | +$27,079 | +$1,329 |
| Resolves against (lose) | 95.1% | -$426 | -$405 |
| Expected value | 100.0% | — | +$924 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +3.4 pprelative edge +216.6%
Required win ratebreak-even
1.6%
price = implied probability
Model win rateP(win)
4.9%
what you forecast
Cushionedge
+3.4 pp
margin of safety
Fair pricemodel
0.049
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
1.6%
= price
Decimal oddsEU
64.516
total return per $1
AmericanUS
+6352
$100 wins $6352
FractionalUK
63.52 / 1
profit per $1 risked
Profit per $100stake
+$6351.61
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 3765% · APY 50135568875%ROI 216.6% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+216.6%
APR (simple)scaled
+3765%
ROI × 365/days
APY (compounded)if redeployed
+50135568875%
(1+ROI)^(365/d) − 1
Daily expectedper day
+5.64%
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 +2.61 pperosion 22% · break-even w/ fees 2.3%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$853
3.41% · g = 2.357%
Half Kelly½ f★
$426
1.71% · g = 1.966%
Quarter Kelly¼ f★
$213
0.85% · g = 1.310%
Flat 1%1%
$250
1.00% · g = 1.458%
Flat 2%2%
$500
2.00% · g = 2.103%
Flat 5%5%
$1,250
5.00% · g = 2.137%
Recommended¼ f★
$213
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.115 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.282 bit
Δ +0.167 bit vs market
Surprise · YES−log₂ p
6.01 bit
self-information
Surprise · NO−log₂(1−p)
0.02 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
SIGNAL · D_KL(q ‖ p) = 0.0236 nat (0.0340 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 0.049 · CI [0.00, 0.22] · κ 12.0
Posterior meanE[θ]
0.049
Beta(0.6, 11.4)
95% credible intervalHDI
[0.00, 0.22]
price INSIDE → weak edge
Concentrationκ
12.0
pseudo-obs behind belief
Disagreementvs crowd
+2.9 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] +141.9% · P(YES) 3.8% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+141.94%
P(YES) empiricalq
3.8%
Best pathmax
+6351.6%
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 2.70% · ruin rate 8.3%400 paths × 120 bets · f deploy 1.71%
Sharpe / betμ/σ
0.191
μ 5.05% · σ 26.4%
Sortino / betμ/σ↓
2.964
downside-only denominator
VaR 95%5%
-1.7%
per-bet worst-case
CVaR 95%ES
-1.7%
mean tail loss
Max drawdownMDD
-24.1%
Calmar 0.11
Ruin rate≤50%
8.3%
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 -50.6pp · crowd gap -54.0pp
Anchor gapmodel − base
-50.6 pp
Crowd gapprice − base
-54.0 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 17.7% · AUC 0.754out-of-sample BSS (5-fold) 17.8% ± 2.8% · Brier 0.2054 · log-loss 0.6113 · n 1600✓ n = 1600
BrierBS
0.2054
lower = better · ō 0.52
BSSvs base
17.7%
improvement over base rate
ReliabilityREL
0.0050
miscalibration · want ↓
ResolutionRES
0.0490
decisiveness · want ↑
Log lossLL
0.6113
cross-entropy
AUCROC
0.754
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 1.71 · expectancy +0.271R180 trades · win 61.7% · Sharpe 0.237
Total P/Lnet
+$12,178
on $45,000 cycled
Win ratehit %
61.7%
111 W / 69 L
Profit factorPF
1.71
$ won / $ lost
Expectancyper trade
+$67.66
avg $ per position
R-expectancyper risk
+0.271R
in units of risk taken
Avg win / losspayoff
$265.12 / -$250.00
ratio 1.06 : 1
Sharpe / traderisk-adj
0.237
μR / σR
Closing line valueCLV
+2.84 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.