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 · +0.053 · f★ 5.4% · deploy 2.7% · net 4.55pp
§1 · Position economics
YES · Expected P/L per share +0.0530@ model P(YES) = 0.070
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 5.39% · g(f★) = 4.846%deploy 2.70% · g = 4.122%
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 @ 0.017 · EV +$2,168stake $674 · 2.70% of bankroll
Deployed stakestake
$674
2.70% of bankroll
Sharesunits
40,862
each pays $1 if YES
Max payoutwin
$40,862
gross, if win
Max profitwin
+$40,188
net of cost
Max losslose
-$674
binary settles to $0
Payout multiple×
×60.61
$1 → $60.61
Risk:RewardR:R
59.61 : 1
win $59.61 per $1
Expected P/LE[P/L]
+$2,168
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 7.0% | +$40,188 | +$2,795 |
| Resolves against (lose) | 93.0% | -$674 | -$627 |
| Expected value | 100.0% | — | +$2,168 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +5.3 pprelative edge +321.5%
Required win ratebreak-even
1.7%
price = implied probability
Model win rateP(win)
7.0%
what you forecast
Cushionedge
+5.3 pp
margin of safety
Fair pricemodel
0.070
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
1.7%
= price
Decimal oddsEU
60.606
total return per $1
AmericanUS
+5961
$100 wins $5961
FractionalUK
59.61 / 1
profit per $1 risked
Profit per $100stake
+$5960.61
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 5588% · APY 7237878054963%ROI 321.5% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+321.5%
APR (simple)scaled
+5588%
ROI × 365/days
APY (compounded)if redeployed
+7237878054963%
(1+ROI)^(365/d) − 1
Daily expectedper day
+7.09%
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 +4.55 pperosion 14% · break-even w/ fees 2.4%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$1,348
5.39% · g = 4.846%
Half Kelly½ f★
$674
2.70% · g = 4.122%
Quarter Kelly¼ f★
$337
1.35% · g = 2.839%
Flat 1%1%
$250
1.00% · g = 2.316%
Flat 2%2%
$500
2.00% · g = 3.579%
Flat 5%5%
$1,250
5.00% · g = 4.834%
Recommended¼ f★
$337
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.121 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.364 bit
Δ +0.243 bit vs market
Surprise · YES−log₂ p
5.92 bit
self-information
Surprise · NO−log₂(1−p)
0.02 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
SIGNAL · D_KL(q ‖ p) = 0.0485 nat (0.0699 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 0.070 · CI [0.00, 0.23] · κ 17.0
Posterior meanE[θ]
0.070
Beta(1.2, 15.8)
95% credible intervalHDI
[0.00, 0.23]
price INSIDE → weak edge
Concentrationκ
17.0
pseudo-obs behind belief
Disagreementvs crowd
+5.0 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] +263.6% · P(YES) 6.0% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+263.64%
P(YES) empiricalq
6.0%
Best pathmax
+5960.6%
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 3.91% · ruin rate 16.3%400 paths × 120 bets · f deploy 2.70%
Sharpe / betμ/σ
0.217
μ 9.19% · σ 42.5%
Sortino / betμ/σ↓
3.409
downside-only denominator
VaR 95%5%
-2.7%
per-bet worst-case
CVaR 95%ES
-2.7%
mean tail loss
Max drawdownMDD
-33.6%
Calmar 0.12
Ruin rate≤50%
16.3%
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 -37.0pp · crowd gap -42.4pp
Anchor gapmodel − base
-37.0 pp
Crowd gapprice − base
-42.4 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.