NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Elon Musk post 140-159 tweets from June 9 to June 16, 2026?
← Back to live dashboardEmbed cardOG previewTop moversArb
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-elon-musk-of-tweets-june-9-june-16-140-159 page.
▲ YES EDGE · +0.060 · f★ 6.9% · deploy 3.4% · net 5.25pp
§1 · Position economics
YES · Expected P/L per share +0.0600@ model P(YES) = 0.189
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 6.89% · g(f★) = 1.430%deploy 3.44% · g = 1.109%
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 @ 0.129 · EV +$400stake $861 · 3.44% of bankroll
Deployed stakestake
$861
3.44% of bankroll
Sharesunits
6,675
each pays $1 if YES
Max payoutwin
$6,675
gross, if win
Max profitwin
+$5,814
net of cost
Max losslose
-$861
binary settles to $0
Payout multiple×
×7.75
$1 → $7.75
Risk:RewardR:R
6.75 : 1
win $6.75 per $1
Expected P/LE[P/L]
+$400
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 18.9% | +$5,814 | +$1,099 |
| Resolves against (lose) | 81.1% | -$861 | -$698 |
| Expected value | 100.0% | — | +$400 |
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 +46.5%
Required win ratebreak-even
12.9%
price = implied probability
Model win rateP(win)
18.9%
what you forecast
Cushionedge
+6.0 pp
margin of safety
Fair pricemodel
0.189
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
12.9%
= price
Decimal oddsEU
7.752
total return per $1
AmericanUS
+675
$100 wins $675
FractionalUK
6.75 / 1
profit per $1 risked
Profit per $100stake
+$675.19
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 808% · APY 76283%ROI 46.5% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+46.5%
APR (simple)scaled
+808%
ROI × 365/days
APY (compounded)if redeployed
+76283%
(1+ROI)^(365/d) − 1
Daily expectedper day
+1.84%
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 13.7%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$1,722
6.89% · g = 1.430%
Half Kelly½ f★
$861
3.44% · g = 1.109%
Quarter Kelly¼ f★
$431
1.72% · g = 0.670%
Flat 1%1%
$250
1.00% · g = 0.420%
Flat 2%2%
$500
2.00% · g = 0.756%
Flat 5%5%
$1,250
5.00% · g = 1.338%
Recommended¼ f★
$431
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.555 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.699 bit
Δ +0.145 bit vs market
Surprise · YES−log₂ p
2.95 bit
self-information
Surprise · NO−log₂(1−p)
0.20 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0143 nat (0.0206 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 0.189 · CI [0.09, 0.32] · κ 41.6
Posterior meanE[θ]
0.189
Beta(7.9, 33.7)
95% credible intervalHDI
[0.09, 0.32]
price INSIDE → weak edge
Concentrationκ
41.6
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] +22.1% · P(YES) 15.8% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+22.09%
P(YES) empiricalq
15.8%
Best pathmax
+675.2%
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 1.08% · ruin rate 13.3%400 paths × 120 bets · f deploy 3.44%
Sharpe / betμ/σ
0.156
μ 1.63% · σ 10.5%
Sortino / betμ/σ↓
0.474
downside-only denominator
VaR 95%5%
-3.4%
per-bet worst-case
CVaR 95%ES
-3.4%
mean tail loss
Max drawdownMDD
-16.1%
Calmar 0.07
Ruin rate≤50%
13.3%
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 -21.5pp · crowd gap -27.5pp
Anchor gapmodel − base
-21.5 pp
Crowd gapprice − base
-27.5 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 17.6% · AUC 0.755out-of-sample BSS (5-fold) 17.6% ± 1.8% · Brier 0.2059 · log-loss 0.6168 · n 1600✓ n = 1600
BrierBS
0.2059
lower = better · ō 0.52
BSSvs base
17.6%
improvement over base rate
ReliabilityREL
0.0060
miscalibration · want ↓
ResolutionRES
0.0494
decisiveness · want ↑
Log lossLL
0.6168
cross-entropy
AUCROC
0.755
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 +0.016R180 trades · win 51.1% · Sharpe 0.014
Total P/Lnet
+$721
on $45,000 cycled
Win ratehit %
51.1%
92 W / 88 L
Profit factorPF
1.03
$ won / $ lost
Expectancyper trade
+$4.00
avg $ per position
R-expectancyper risk
+0.016R
in units of risk taken
Avg win / losspayoff
$246.96 / -$250.00
ratio 0.99 : 1
Sharpe / traderisk-adj
0.014
μR / σR
Closing line valueCLV
+3.16 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.