NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Elon Musk post 180-199 tweets from June 12 to June 19, 2026?
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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-elon-musk-of-tweets-june-12-june-19-180-199 page.
▲ YES EDGE · +0.008 · f★ 1.5% · deploy 0.7% · net 0.01pp
§1 · Position economics
YES · Expected P/L per share +0.0076@ model P(YES) = 0.483
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 1.45% · g(f★) = 0.012%deploy 0.73% · g = 0.009%
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 @ 0.475 · EV +$3stake $182 · 0.73% of bankroll
Deployed stakestake
$182
0.73% of bankroll
Sharesunits
383
each pays $1 if YES
Max payoutwin
$383
gross, if win
Max profitwin
+$201
net of cost
Max losslose
-$182
binary settles to $0
Payout multiple×
×2.11
$1 → $2.11
Risk:RewardR:R
1.11 : 1
win $1.11 per $1
Expected P/LE[P/L]
+$3
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 48.3% | +$201 | +$97 |
| Resolves against (lose) | 51.7% | -$182 | -$94 |
| Expected value | 100.0% | — | +$3 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +0.8 pprelative edge +1.6%
Required win ratebreak-even
47.5%
price = implied probability
Model win rateP(win)
48.3%
what you forecast
Cushionedge
+0.8 pp
margin of safety
Fair pricemodel
0.483
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
47.5%
= price
Decimal oddsEU
2.105
total return per $1
AmericanUS
+111
$100 wins $111
FractionalUK
1.11 / 1
profit per $1 risked
Profit per $100stake
+$110.53
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 28% · APY 32%ROI 1.6% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+1.6%
APR (simple)scaled
+28%
ROI × 365/days
APY (compounded)if redeployed
+32%
(1+ROI)^(365/d) − 1
Daily expectedper day
+0.08%
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 +0.01 pperosion 98% · break-even w/ fees 48.3%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$364
1.45% · g = 0.012%
Half Kelly½ f★
$182
0.73% · g = 0.009%
Quarter Kelly¼ f★
$91
0.36% · g = 0.005%
Flat 1%1%
$250
1.00% · g = 0.011%
Flat 2%2%
$500
2.00% · g = 0.010%
Flat 5%5%
$1,250
5.00% · g = -0.058%
Recommended¼ f★
$91
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.998 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.999 bit
Δ +0.001 bit vs market
Surprise · YES−log₂ p
1.07 bit
self-information
Surprise · NO−log₂(1−p)
0.93 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0001 nat (0.0002 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 0.483 · CI [0.37, 0.60] · κ 68.4
Posterior meanE[θ]
0.483
Beta(33.0, 35.4)
95% credible intervalHDI
[0.37, 0.60]
price INSIDE → weak edge
Concentrationκ
68.4
pseudo-obs behind belief
Disagreementvs crowd
+0.8 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] -0.0% · P(YES) 47.5% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
-0.00%
P(YES) empiricalq
47.5%
Best pathmax
+110.5%
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 -0.00% · ruin rate 0.0%400 paths × 120 bets · f deploy 0.73%
Sharpe / betμ/σ
0.010
μ 0.01% · σ 0.8%
Sortino / betμ/σ↓
0.010
downside-only denominator
VaR 95%5%
-0.7%
per-bet worst-case
CVaR 95%ES
-0.7%
mean tail loss
Max drawdownMDD
-2.0%
Calmar -0.00
Ruin rate≤50%
0.0%
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 -10.8pp · crowd gap -11.6pp
Anchor gapmodel − base
-10.8 pp
Crowd gapprice − base
-11.6 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 20.8% · AUC 0.771out-of-sample BSS (5-fold) 20.8% ± 1.6% · Brier 0.1978 · log-loss 0.5951 · n 1600✓ n = 1600
BrierBS
0.1978
lower = better · ō 0.52
BSSvs base
20.8%
improvement over base rate
ReliabilityREL
0.0039
miscalibration · want ↓
ResolutionRES
0.0562
decisiveness · want ↑
Log lossLL
0.5951
cross-entropy
AUCROC
0.771
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 1.44 · expectancy +0.187R180 trades · win 57.8% · Sharpe 0.157
Total P/Lnet
+$8,407
on $45,000 cycled
Win ratehit %
57.8%
104 W / 76 L
Profit factorPF
1.44
$ won / $ lost
Expectancyper trade
+$46.70
avg $ per position
R-expectancyper risk
+0.187R
in units of risk taken
Avg win / losspayoff
$263.53 / -$250.00
ratio 1.05 : 1
Sharpe / traderisk-adj
0.157
μR / σR
Closing line valueCLV
+2.53 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.