NOSTRADAMUS · Position Analytics Engine
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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-will-google-have-the-best-ai-model-at-the-end-of-june-2026 page.
▲ YES EDGE · +0.038 · f★ 4.0% · deploy 2.0% · net 3.09pp
§1 · Position economics
YES · Expected P/L per share +0.0384@ model P(YES) = 0.076
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 3.99% · g(f★) = 1.587%deploy 1.99% · g = 1.274%
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 @ 0.037 · EV +$510stake $498 · 1.99% of bankroll
Deployed stakestake
$498
1.99% of bankroll
Sharesunits
13,287
each pays $1 if YES
Max payoutwin
$13,287
gross, if win
Max profitwin
+$12,789
net of cost
Max losslose
-$498
binary settles to $0
Payout multiple×
×26.67
$1 → $26.67
Risk:RewardR:R
25.67 : 1
win $25.67 per $1
Expected P/LE[P/L]
+$510
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 7.6% | +$12,789 | +$970 |
| Resolves against (lose) | 92.4% | -$498 | -$460 |
| Expected value | 100.0% | — | +$510 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +3.8 pprelative edge +102.3%
Required win ratebreak-even
3.8%
price = implied probability
Model win rateP(win)
7.6%
what you forecast
Cushionedge
+3.8 pp
margin of safety
Fair pricemodel
0.076
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
3.8%
= price
Decimal oddsEU
26.667
total return per $1
AmericanUS
+2567
$100 wins $2567
FractionalUK
25.67 / 1
profit per $1 risked
Profit per $100stake
+$2566.67
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 1778% · APY 20837145%ROI 102.3% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+102.3%
APR (simple)scaled
+1778%
ROI × 365/days
APY (compounded)if redeployed
+20837145%
(1+ROI)^(365/d) − 1
Daily expectedper day
+3.41%
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 +3.09 pperosion 20% · break-even w/ fees 4.5%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$997
3.99% · g = 1.587%
Half Kelly½ f★
$498
1.99% · g = 1.274%
Quarter Kelly¼ f★
$249
1.00% · g = 0.802%
Flat 1%1%
$250
1.00% · g = 0.804%
Flat 2%2%
$500
2.00% · g = 1.276%
Flat 5%5%
$1,250
5.00% · g = 1.524%
Recommended¼ f★
$249
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.231 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.387 bit
Δ +0.157 bit vs market
Surprise · YES−log₂ p
4.74 bit
self-information
Surprise · NO−log₂(1−p)
0.06 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0159 nat (0.0229 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 0.076 · CI [0.01, 0.23] · κ 18.5
Posterior meanE[θ]
0.076
Beta(1.4, 17.1)
95% credible intervalHDI
[0.01, 0.23]
price INSIDE → weak edge
Concentrationκ
18.5
pseudo-obs behind belief
Disagreementvs crowd
+3.8 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] +113.3% · P(YES) 8.0% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+113.33%
P(YES) empiricalq
8.0%
Best pathmax
+2566.7%
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 1.24% · ruin rate 12.0%400 paths × 120 bets · f deploy 1.99%
Sharpe / betμ/σ
0.155
μ 2.22% · σ 14.4%
Sortino / betμ/σ↓
1.114
downside-only denominator
VaR 95%5%
-2.0%
per-bet worst-case
CVaR 95%ES
-2.0%
mean tail loss
Max drawdownMDD
-26.1%
Calmar 0.05
Ruin rate≤50%
12.0%
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 -40.3pp · crowd gap -44.1pp
Anchor gapmodel − base
-40.3 pp
Crowd gapprice − base
-44.1 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 17.3% · AUC 0.752out-of-sample BSS (5-fold) 17.4% ± 0.8% · Brier 0.2067 · log-loss 0.6189 · n 1600✓ n = 1600
BrierBS
0.2067
lower = better · ō 0.50
BSSvs base
17.3%
improvement over base rate
ReliabilityREL
0.0075
miscalibration · want ↓
ResolutionRES
0.0490
decisiveness · want ↑
Log lossLL
0.6189
cross-entropy
AUCROC
0.752
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 1.22 · expectancy +0.104R180 trades · win 52.8% · Sharpe 0.088
Total P/Lnet
+$4,661
on $45,000 cycled
Win ratehit %
52.8%
95 W / 85 L
Profit factorPF
1.22
$ won / $ lost
Expectancyper trade
+$25.90
avg $ per position
R-expectancyper risk
+0.104R
in units of risk taken
Avg win / losspayoff
$272.75 / -$250.00
ratio 1.09 : 1
Sharpe / traderisk-adj
0.088
μR / σR
Closing line valueCLV
+3.06 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.