NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Elon Musk post 120-139 tweets from June 9 to June 16, 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-9-june-16-120-139 page.
▲ YES EDGE · +0.060 · f★ 6.6% · deploy 3.3% · net 5.21pp
§1 · Position economics
YES · Expected P/L per share +0.0596@ model P(YES) = 0.154
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 6.58% · g(f★) = 1.786%deploy 3.29% · g = 1.401%
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 @ 0.094 · EV +$522stake $823 · 3.29% of bankroll
Deployed stakestake
$823
3.29% of bankroll
Sharesunits
8,754
each pays $1 if YES
Max payoutwin
$8,754
gross, if win
Max profitwin
+$7,932
net of cost
Max losslose
-$823
binary settles to $0
Payout multiple×
×10.64
$1 → $10.64
Risk:RewardR:R
9.64 : 1
win $9.64 per $1
Expected P/LE[P/L]
+$522
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 15.4% | +$7,932 | +$1,219 |
| Resolves against (lose) | 84.6% | -$823 | -$696 |
| Expected value | 100.0% | — | +$522 |
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 +63.5%
Required win ratebreak-even
9.4%
price = implied probability
Model win rateP(win)
15.4%
what you forecast
Cushionedge
+6.0 pp
margin of safety
Fair pricemodel
0.154
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
9.4%
= price
Decimal oddsEU
10.638
total return per $1
AmericanUS
+964
$100 wins $964
FractionalUK
9.64 / 1
profit per $1 risked
Profit per $100stake
+$963.83
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 1103% · APY 511494%ROI 63.5% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+63.5%
APR (simple)scaled
+1103%
ROI × 365/days
APY (compounded)if redeployed
+511494%
(1+ROI)^(365/d) − 1
Daily expectedper day
+2.37%
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 +5.21 pperosion 13% · break-even w/ fees 10.2%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$1,646
6.58% · g = 1.786%
Half Kelly½ f★
$823
3.29% · g = 1.401%
Quarter Kelly¼ f★
$411
1.65% · g = 0.858%
Flat 1%1%
$250
1.00% · g = 0.563%
Flat 2%2%
$500
2.00% · g = 0.999%
Flat 5%5%
$1,250
5.00% · g = 1.702%
Recommended¼ f★
$411
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.450 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.619 bit
Δ +0.169 bit vs market
Surprise · YES−log₂ p
3.41 bit
self-information
Surprise · NO−log₂(1−p)
0.14 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0179 nat (0.0258 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 0.154 · CI [0.06, 0.29] · κ 35.1
Posterior meanE[θ]
0.154
Beta(5.4, 29.7)
95% credible intervalHDI
[0.06, 0.29]
price INSIDE → weak edge
Concentrationκ
35.1
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] +62.2% · P(YES) 15.3% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+62.23%
P(YES) empiricalq
15.3%
Best pathmax
+963.8%
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 1.30% · ruin rate 11.3%400 paths × 120 bets · f deploy 3.29%
Sharpe / betμ/σ
0.162
μ 2.04% · σ 12.6%
Sortino / betμ/σ↓
0.621
downside-only denominator
VaR 95%5%
-3.3%
per-bet worst-case
CVaR 95%ES
-3.3%
mean tail loss
Max drawdownMDD
-20.9%
Calmar 0.06
Ruin rate≤50%
11.3%
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 -28.6pp · crowd gap -34.6pp
Anchor gapmodel − base
-28.6 pp
Crowd gapprice − base
-34.6 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 20.2% · AUC 0.768out-of-sample BSS (5-fold) 20.4% ± 1.1% · Brier 0.1993 · log-loss 0.5868 · n 1600✓ n = 1600
BrierBS
0.1993
lower = better · ō 0.51
BSSvs base
20.2%
improvement over base rate
ReliabilityREL
0.0043
miscalibration · want ↓
ResolutionRES
0.0547
decisiveness · want ↑
Log lossLL
0.5868
cross-entropy
AUCROC
0.768
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 0.96 · expectancy -0.021R180 trades · win 48.3% · Sharpe -0.018
Total P/Lnet
-$923
on $45,000 cycled
Win ratehit %
48.3%
87 W / 93 L
Profit factorPF
0.96
$ won / $ lost
Expectancyper trade
-$5.13
avg $ per position
R-expectancyper risk
-0.021R
in units of risk taken
Avg win / losspayoff
$256.64 / -$250.00
ratio 1.03 : 1
Sharpe / traderisk-adj
-0.018
μR / σR
Closing line valueCLV
+2.71 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.