NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Elon Musk post 60-79 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-23-60-79 page.
▲ YES EDGE · +0.023 · f★ 2.3% · deploy 1.1% · net 1.53pp
§1 · Position economics
YES · Expected P/L per share +0.0228@ model P(YES) = 0.027
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 2.29% · g(f★) = 2.667%deploy 1.14% · g = 2.325%
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 @ 0.004 · EV +$1,450stake $286 · 1.14% of bankroll
Deployed stakestake
$286
1.14% of bankroll
Sharesunits
63,611
each pays $1 if YES
Max payoutwin
$63,611
gross, if win
Max profitwin
+$63,325
net of cost
Max losslose
-$286
binary settles to $0
Payout multiple×
×222.22
$1 → $222.22
Risk:RewardR:R
221.22 : 1
win $221.22 per $1
Expected P/LE[P/L]
+$1,450
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 2.7% | +$63,325 | +$1,729 |
| Resolves against (lose) | 97.3% | -$286 | -$278 |
| Expected value | 100.0% | — | +$1,450 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +2.3 pprelative edge +506.6%
Required win ratebreak-even
0.4%
price = implied probability
Model win rateP(win)
2.7%
what you forecast
Cushionedge
+2.3 pp
margin of safety
Fair pricemodel
0.027
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
0.4%
= price
Decimal oddsEU
222.222
total return per $1
AmericanUS
+22122
$100 wins $22122
FractionalUK
221.22 / 1
profit per $1 risked
Profit per $100stake
+$22122.22
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 8805% · APY 4051093053929044%ROI 506.6% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+506.6%
APR (simple)scaled
+8805%
ROI × 365/days
APY (compounded)if redeployed
+4051093053929044%
(1+ROI)^(365/d) − 1
Daily expectedper day
+8.96%
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 +1.53 pperosion 33% · break-even w/ fees 1.2%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$572
2.29% · g = 2.667%
Half Kelly½ f★
$286
1.14% · g = 2.325%
Quarter Kelly¼ f★
$143
0.57% · g = 1.675%
Flat 1%1%
$250
1.00% · g = 2.208%
Flat 2%2%
$500
2.00% · g = 2.651%
Flat 5%5%
$1,250
5.00% · g = 1.808%
Recommended¼ f★
$143
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.042 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.181 bit
Δ +0.139 bit vs market
Surprise · YES−log₂ p
7.80 bit
self-information
Surprise · NO−log₂(1−p)
0.01 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
SIGNAL · D_KL(q ‖ p) = 0.0267 nat (0.0385 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 0.027 · CI [0.00, 0.25] · κ 6.4
Posterior meanE[θ]
0.027
Beta(0.2, 6.2)
95% credible intervalHDI
[0.00, 0.25]
price INSIDE → weak edge
Concentrationκ
6.4
pseudo-obs behind belief
Disagreementvs crowd
+0.7 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] +1233.3% · P(YES) 6.0% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+1233.33%
P(YES) empiricalq
6.0%
Best pathmax
+22122.2%
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 4.24% · ruin rate 8.3%400 paths × 120 bets · f deploy 1.14%
Sharpe / betμ/σ
0.189
μ 9.77% · σ 51.6%
Sortino / betμ/σ↓
8.532
downside-only denominator
VaR 95%5%
-1.1%
per-bet worst-case
CVaR 95%ES
-1.1%
mean tail loss
Max drawdownMDD
-24.1%
Calmar 0.18
Ruin rate≤50%
8.3%
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 -48.1pp · crowd gap -50.4pp
Anchor gapmodel − base
-48.1 pp
Crowd gapprice − base
-50.4 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 21.4% · AUC 0.773out-of-sample BSS (5-fold) 21.6% ± 1.0% · Brier 0.1964 · log-loss 0.5847 · n 1600✓ n = 1600
BrierBS
0.1964
lower = better · ō 0.52
BSSvs base
21.4%
improvement over base rate
ReliabilityREL
0.0034
miscalibration · want ↓
ResolutionRES
0.0568
decisiveness · want ↑
Log lossLL
0.5847
cross-entropy
AUCROC
0.773
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 0.99 · expectancy -0.005R180 trades · win 51.1% · Sharpe -0.005
Total P/Lnet
-$223
on $45,000 cycled
Win ratehit %
51.1%
92 W / 88 L
Profit factorPF
0.99
$ won / $ lost
Expectancyper trade
-$1.24
avg $ per position
R-expectancyper risk
-0.005R
in units of risk taken
Avg win / losspayoff
$236.71 / -$250.00
ratio 0.95 : 1
Sharpe / traderisk-adj
-0.005
μR / σR
Closing line valueCLV
+3.16 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.