NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Steve Witkoff attend the next US x Iran diplomatic meeting?
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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-steve-witkoff-attend-the-next-us-x-iran-diplomatic-meeting page.
▲ YES EDGE · +0.049 · f★ 16.7% · deploy 8.4% · net 4.11pp
§1 · Position economics
YES · Expected P/L per share +0.0486@ model P(YES) = 0.758
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 16.74% · g(f★) = 0.595%deploy 8.37% · g = 0.441%
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 @ 0.710 · EV +$143stake $2,093 · 8.37% of bankroll
Deployed stakestake
$2,093
8.37% of bankroll
Sharesunits
2,950
each pays $1 if YES
Max payoutwin
$2,950
gross, if win
Max profitwin
+$857
net of cost
Max losslose
-$2,093
binary settles to $0
Payout multiple×
×1.41
$1 → $1.41
Risk:RewardR:R
0.41 : 1
win $0.41 per $1
Expected P/LE[P/L]
+$143
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 75.8% | +$857 | +$650 |
| Resolves against (lose) | 24.2% | -$2,093 | -$506 |
| Expected value | 100.0% | — | +$143 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +4.9 pprelative edge +6.9%
Required win ratebreak-even
71.0%
price = implied probability
Model win rateP(win)
75.8%
what you forecast
Cushionedge
+4.9 pp
margin of safety
Fair pricemodel
0.758
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
71.0%
= price
Decimal oddsEU
1.409
total return per $1
AmericanUS
-244
risk $244 to win $100
FractionalUK
0.41 / 1
profit per $1 risked
Profit per $100stake
+$40.94
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 119% · APY 217%ROI 6.9% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+6.9%
APR (simple)scaled
+119%
ROI × 365/days
APY (compounded)if redeployed
+217%
(1+ROI)^(365/d) − 1
Daily expectedper day
+0.32%
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 +4.11 pperosion 15% · break-even w/ fees 71.7%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$4,186
16.74% · g = 0.595%
Half Kelly½ f★
$2,093
8.37% · g = 0.441%
Quarter Kelly¼ f★
$1,046
4.19% · g = 0.254%
Flat 1%1%
$250
1.00% · g = 0.067%
Flat 2%2%
$500
2.00% · g = 0.130%
Flat 5%5%
$1,250
5.00% · g = 0.296%
Recommended¼ f★
$1,046
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.869 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.798 bit
Δ -0.071 bit vs market
Surprise · YES−log₂ p
0.50 bit
self-information
Surprise · NO−log₂(1−p)
1.78 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0060 nat (0.0086 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 0.758 · CI [0.63, 0.87] · κ 49.9
Posterior meanE[θ]
0.758
Beta(37.9, 12.1)
95% credible intervalHDI
[0.63, 0.87]
price INSIDE → weak edge
Concentrationκ
49.9
pseudo-obs behind belief
Disagreementvs crowd
+4.9 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] +10.6% · P(YES) 78.5% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+10.64%
P(YES) empiricalq
78.5%
Best pathmax
+40.9%
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 0.44% · ruin rate 7.8%400 paths × 120 bets · f deploy 8.37%
Sharpe / betμ/σ
0.108
μ 0.55% · σ 5.1%
Sortino / betμ/σ↓
0.065
downside-only denominator
VaR 95%5%
-8.4%
per-bet worst-case
CVaR 95%ES
-8.4%
mean tail loss
Max drawdownMDD
-10.2%
Calmar 0.04
Ruin rate≤50%
7.8%
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 +27.4pp · crowd gap +22.6pp
Anchor gapmodel − base
+27.4 pp
Crowd gapprice − base
+22.6 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 19.4% · AUC 0.764out-of-sample BSS (5-fold) 19.5% ± 2.3% · Brier 0.2013 · log-loss 0.6008 · n 1600✓ n = 1600
BrierBS
0.2013
lower = better · ō 0.52
BSSvs base
19.4%
improvement over base rate
ReliabilityREL
0.0054
miscalibration · want ↓
ResolutionRES
0.0532
decisiveness · want ↑
Log lossLL
0.6008
cross-entropy
AUCROC
0.764
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 0.91 · expectancy -0.043R180 trades · win 50.6% · Sharpe -0.041
Total P/Lnet
-$1,922
on $45,000 cycled
Win ratehit %
50.6%
91 W / 89 L
Profit factorPF
0.91
$ won / $ lost
Expectancyper trade
-$10.68
avg $ per position
R-expectancyper risk
-0.043R
in units of risk taken
Avg win / losspayoff
$223.39 / -$250.00
ratio 0.89 : 1
Sharpe / traderisk-adj
-0.041
μR / σR
Closing line valueCLV
+3.52 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.