NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Elon Musk post 140-159 tweets from June 16 to June 23, 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-16-june-23-140-159 page.
▲ YES EDGE · +0.059 · f★ 6.2% · deploy 3.1% · net 5.17pp
§1 · Position economics
YES · Expected P/L per share +0.0592@ model P(YES) = 0.109
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 6.23% · g(f★) = 2.817%deploy 3.11% · g = 2.274%
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 @ 0.050 · EV +$930stake $778 · 3.11% of bankroll
Deployed stakestake
$778
3.11% of bankroll
Sharesunits
15,721
each pays $1 if YES
Max payoutwin
$15,721
gross, if win
Max profitwin
+$14,943
net of cost
Max losslose
-$778
binary settles to $0
Payout multiple×
×20.20
$1 → $20.20
Risk:RewardR:R
19.20 : 1
win $19.20 per $1
Expected P/LE[P/L]
+$930
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 10.9% | +$14,943 | +$1,624 |
| Resolves against (lose) | 89.1% | -$778 | -$694 |
| Expected value | 100.0% | — | +$930 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +5.9 pprelative edge +119.5%
Required win ratebreak-even
5.0%
price = implied probability
Model win rateP(win)
10.9%
what you forecast
Cushionedge
+5.9 pp
margin of safety
Fair pricemodel
0.109
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
5.0%
= price
Decimal oddsEU
20.202
total return per $1
AmericanUS
+1920
$100 wins $1920
FractionalUK
19.20 / 1
profit per $1 risked
Profit per $100stake
+$1920.20
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 2078% · APY 86291339%ROI 119.5% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+119.5%
APR (simple)scaled
+2078%
ROI × 365/days
APY (compounded)if redeployed
+86291339%
(1+ROI)^(365/d) − 1
Daily expectedper day
+3.82%
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 +5.17 pperosion 13% · break-even w/ fees 5.7%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$1,556
6.23% · g = 2.817%
Half Kelly½ f★
$778
3.11% · g = 2.274%
Quarter Kelly¼ f★
$389
1.56% · g = 1.444%
Flat 1%1%
$250
1.00% · g = 1.013%
Flat 2%2%
$500
2.00% · g = 1.731%
Flat 5%5%
$1,250
5.00% · g = 2.742%
Recommended¼ f★
$389
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.284 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.496 bit
Δ +0.212 bit vs market
Surprise · YES−log₂ p
4.34 bit
self-information
Surprise · NO−log₂(1−p)
0.07 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
SIGNAL · D_KL(q ‖ p) = 0.0282 nat (0.0406 bit)exploitable edge present
YES contributionNO contributionbelief ‖ marketsignal
Zero KL ⇒ you know nothing the crowd doesn't.
§8 · Bayesian inference
MARKET PRICE INSIDE 95% CIposterior μ 0.109 · CI [0.02, 0.25] · κ 25.9
Posterior meanE[θ]
0.109
Beta(2.8, 23.1)
95% credible intervalHDI
[0.02, 0.25]
price INSIDE → weak edge
Concentrationκ
25.9
pseudo-obs behind belief
Disagreementvs crowd
+5.9 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] +137.4% · P(YES) 11.8% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+137.37%
P(YES) empiricalq
11.8%
Best pathmax
+1920.2%
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 2.28% · ruin rate 14.5%400 paths × 120 bets · f deploy 3.11%
Sharpe / betμ/σ
0.192
μ 3.77% · σ 19.6%
Sortino / betμ/σ↓
1.211
downside-only denominator
VaR 95%5%
-3.1%
per-bet worst-case
CVaR 95%ES
-3.1%
mean tail loss
Max drawdownMDD
-29.4%
Calmar 0.08
Ruin rate≤50%
14.5%
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 -43.1pp · crowd gap -49.1pp
Anchor gapmodel − base
-43.1 pp
Crowd gapprice − base
-49.1 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 19.3% · AUC 0.764out-of-sample BSS (5-fold) 19.4% ± 2.2% · Brier 0.2017 · log-loss 0.6014 · n 1600✓ n = 1600
BrierBS
0.2017
lower = better · ō 0.50
BSSvs base
19.3%
improvement over base rate
ReliabilityREL
0.0047
miscalibration · want ↓
ResolutionRES
0.0516
decisiveness · want ↑
Log lossLL
0.6014
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)
PROFITABLE · PF 1.40 · expectancy +0.165R180 trades · win 58.3% · Sharpe 0.141
Total P/Lnet
+$7,432
on $45,000 cycled
Win ratehit %
58.3%
105 W / 75 L
Profit factorPF
1.40
$ won / $ lost
Expectancyper trade
+$41.29
avg $ per position
R-expectancyper risk
+0.165R
in units of risk taken
Avg win / losspayoff
$249.35 / -$250.00
ratio 1.00 : 1
Sharpe / traderisk-adj
0.141
μR / σR
Closing line valueCLV
+3.74 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.