NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Elon Musk post 100-119 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-19-100-119 page.
▲ YES EDGE · +0.018 · f★ 1.8% · deploy 0.9% · net 1.02pp
§1 · Position economics
YES · Expected P/L per share +0.0177@ model P(YES) = 0.048
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 1.83% · g(f★) = 0.452%deploy 0.91% · g = 0.355%
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 @ 0.030 · EV +$132stake $228 · 0.91% of bankroll
Deployed stakestake
$228
0.91% of bankroll
Sharesunits
7,482
each pays $1 if YES
Max payoutwin
$7,482
gross, if win
Max profitwin
+$7,254
net of cost
Max losslose
-$228
binary settles to $0
Payout multiple×
×32.79
$1 → $32.79
Risk:RewardR:R
31.79 : 1
win $31.79 per $1
Expected P/LE[P/L]
+$132
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 4.8% | +$7,254 | +$350 |
| Resolves against (lose) | 95.2% | -$228 | -$217 |
| Expected value | 100.0% | — | +$132 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +1.8 pprelative edge +58.0%
Required win ratebreak-even
3.0%
price = implied probability
Model win rateP(win)
4.8%
what you forecast
Cushionedge
+1.8 pp
margin of safety
Fair pricemodel
0.048
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
3.0%
= price
Decimal oddsEU
32.787
total return per $1
AmericanUS
+3179
$100 wins $3179
FractionalUK
31.79 / 1
profit per $1 risked
Profit per $100stake
+$3178.69
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 1009% · APY 284479%ROI 58.0% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+58.0%
APR (simple)scaled
+1009%
ROI × 365/days
APY (compounded)if redeployed
+284479%
(1+ROI)^(365/d) − 1
Daily expectedper day
+2.20%
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 +1.02 pperosion 42% · break-even w/ fees 3.8%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$456
1.83% · g = 0.452%
Half Kelly½ f★
$228
0.91% · g = 0.355%
Quarter Kelly¼ f★
$114
0.46% · g = 0.218%
Flat 1%1%
$250
1.00% · g = 0.374%
Flat 2%2%
$500
2.00% · g = 0.449%
Flat 5%5%
$1,250
5.00% · g = -0.296%
Recommended¼ f★
$114
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.197 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.279 bit
Δ +0.082 bit vs market
Surprise · YES−log₂ p
5.04 bit
self-information
Surprise · NO−log₂(1−p)
0.04 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0045 nat (0.0065 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 0.048 · CI [0.00, 0.22] · κ 11.7
Posterior meanE[θ]
0.048
Beta(0.6, 11.2)
95% credible intervalHDI
[0.00, 0.22]
price INSIDE → weak edge
Concentrationκ
11.7
pseudo-obs behind belief
Disagreementvs crowd
+1.8 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] +23.0% · P(YES) 3.8% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+22.95%
P(YES) empiricalq
3.8%
Best pathmax
+3178.7%
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 0.62% · ruin rate 2.3%400 paths × 120 bets · f deploy 0.91%
Sharpe / betμ/σ
0.117
μ 0.82% · σ 7.0%
Sortino / betμ/σ↓
0.898
downside-only denominator
VaR 95%5%
-0.9%
per-bet worst-case
CVaR 95%ES
-0.9%
mean tail loss
Max drawdownMDD
-14.4%
Calmar 0.04
Ruin rate≤50%
2.3%
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 -48.7pp · crowd gap -50.5pp
Anchor gapmodel − base
-48.7 pp
Crowd gapprice − base
-50.5 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 18.5% · AUC 0.759out-of-sample BSS (5-fold) 18.7% ± 1.2% · Brier 0.2032 · log-loss 0.6013 · n 1600✓ n = 1600
BrierBS
0.2032
lower = better · ō 0.52
BSSvs base
18.5%
improvement over base rate
ReliabilityREL
0.0058
miscalibration · want ↓
ResolutionRES
0.0519
decisiveness · want ↑
Log lossLL
0.6013
cross-entropy
AUCROC
0.759
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 1.32 · expectancy +0.144R180 trades · win 55.6% · Sharpe 0.117
Total P/Lnet
+$6,465
on $45,000 cycled
Win ratehit %
55.6%
100 W / 80 L
Profit factorPF
1.32
$ won / $ lost
Expectancyper trade
+$35.92
avg $ per position
R-expectancyper risk
+0.144R
in units of risk taken
Avg win / losspayoff
$264.65 / -$250.00
ratio 1.06 : 1
Sharpe / traderisk-adj
0.117
μR / σR
Closing line valueCLV
+2.87 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.