NOSTRADAMUS · Position Analytics Engine
SIMULATOR Sinaloa Gov. Ruben Rocha extradited to US by June 30?
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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-sinaloa-gov-ruben-rocha-extradited-to-us-by-june-30 page.
▲ YES EDGE · +0.060 · f★ 8.6% · deploy 4.3% · net 5.25pp
§1 · Position economics
YES · Expected P/L per share +0.0600@ model P(YES) = 0.362
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 8.60% · g(f★) = 0.825%deploy 4.30% · g = 0.625%
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 @ 0.302 · EV +$213stake $1,075 · 4.30% of bankroll
Deployed stakestake
$1,075
4.30% of bankroll
Sharesunits
3,555
each pays $1 if YES
Max payoutwin
$3,555
gross, if win
Max profitwin
+$2,479
net of cost
Max losslose
-$1,075
binary settles to $0
Payout multiple×
×3.31
$1 → $3.31
Risk:RewardR:R
2.31 : 1
win $2.31 per $1
Expected P/LE[P/L]
+$213
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 36.2% | +$2,479 | +$899 |
| Resolves against (lose) | 63.8% | -$1,075 | -$685 |
| Expected value | 100.0% | — | +$213 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +6.0 pprelative edge +19.8%
Required win ratebreak-even
30.3%
price = implied probability
Model win rateP(win)
36.2%
what you forecast
Cushionedge
+6.0 pp
margin of safety
Fair pricemodel
0.362
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
30.3%
= price
Decimal oddsEU
3.306
total return per $1
AmericanUS
+231
$100 wins $231
FractionalUK
2.31 / 1
profit per $1 risked
Profit per $100stake
+$230.58
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 345% · APY 2222%ROI 19.8% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+19.8%
APR (simple)scaled
+345%
ROI × 365/days
APY (compounded)if redeployed
+2222%
(1+ROI)^(365/d) − 1
Daily expectedper day
+0.87%
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 +5.25 pperosion 13% · break-even w/ fees 31.0%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$2,151
8.60% · g = 0.825%
Half Kelly½ f★
$1,075
4.30% · g = 0.625%
Quarter Kelly¼ f★
$538
2.15% · g = 0.368%
Flat 1%1%
$250
1.00% · g = 0.186%
Flat 2%2%
$500
2.00% · g = 0.346%
Flat 5%5%
$1,250
5.00% · g = 0.685%
Recommended¼ f★
$538
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.884 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.945 bit
Δ +0.060 bit vs market
Surprise · YES−log₂ p
1.72 bit
self-information
Surprise · NO−log₂(1−p)
0.52 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0082 nat (0.0119 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 0.362 · CI [0.25, 0.48] · κ 63.2
Posterior meanE[θ]
0.362
Beta(22.9, 40.3)
95% credible intervalHDI
[0.25, 0.48]
price INSIDE → weak edge
Concentrationκ
63.2
pseudo-obs behind belief
Disagreementvs crowd
+6.0 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] +29.8% · P(YES) 39.3% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+29.75%
P(YES) empiricalq
39.3%
Best pathmax
+230.6%
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 0.69% · ruin rate 9.0%400 paths × 120 bets · f deploy 4.30%
Sharpe / betμ/σ
0.125
μ 0.85% · σ 6.8%
Sortino / betμ/σ↓
0.198
downside-only denominator
VaR 95%5%
-4.3%
per-bet worst-case
CVaR 95%ES
-4.3%
mean tail loss
Max drawdownMDD
-12.4%
Calmar 0.06
Ruin rate≤50%
9.0%
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 -20.2pp · crowd gap -26.1pp
Anchor gapmodel − base
-20.2 pp
Crowd gapprice − base
-26.1 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 19.3% · AUC 0.763out-of-sample BSS (5-fold) 19.4% ± 1.7% · Brier 0.2018 · log-loss 0.5985 · n 1600✓ n = 1600
BrierBS
0.2018
lower = better · ō 0.49
BSSvs base
19.3%
improvement over base rate
ReliabilityREL
0.0049
miscalibration · want ↓
ResolutionRES
0.0528
decisiveness · want ↑
Log lossLL
0.5985
cross-entropy
AUCROC
0.763
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 1.03 · expectancy +0.014R180 trades · win 50.6% · Sharpe 0.012
Total P/Lnet
+$622
on $45,000 cycled
Win ratehit %
50.6%
91 W / 89 L
Profit factorPF
1.03
$ won / $ lost
Expectancyper trade
+$3.45
avg $ per position
R-expectancyper risk
+0.014R
in units of risk taken
Avg win / losspayoff
$251.34 / -$250.00
ratio 1.01 : 1
Sharpe / traderisk-adj
0.012
μR / σR
Closing line valueCLV
+2.72 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.