NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Bitcoin dip to $50,000 in June?
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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-will-bitcoin-dip-to-50k-in-june-2026-212 page.
▲ YES EDGE · +0.012 · f★ 1.3% · deploy 0.6% · net 0.46pp
§1 · Position economics
YES · Expected P/L per share +0.0121@ model P(YES) = 0.061
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 1.28% · g(f★) = 0.148%deploy 0.64% · g = 0.114%
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 @ 0.049 · EV +$40stake $160 · 0.64% of bankroll
Deployed stakestake
$160
0.64% of bankroll
Sharesunits
3,289
each pays $1 if YES
Max payoutwin
$3,289
gross, if win
Max profitwin
+$3,130
net of cost
Max losslose
-$160
binary settles to $0
Payout multiple×
×20.62
$1 → $20.62
Risk:RewardR:R
19.62 : 1
win $19.62 per $1
Expected P/LE[P/L]
+$40
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 6.1% | +$3,130 | +$190 |
| Resolves against (lose) | 93.9% | -$160 | -$150 |
| Expected value | 100.0% | — | +$40 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +1.2 pprelative edge +25.0%
Required win ratebreak-even
4.9%
price = implied probability
Model win rateP(win)
6.1%
what you forecast
Cushionedge
+1.2 pp
margin of safety
Fair pricemodel
0.061
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
4.9%
= price
Decimal oddsEU
20.619
total return per $1
AmericanUS
+1962
$100 wins $1962
FractionalUK
19.62 / 1
profit per $1 risked
Profit per $100stake
+$1961.86
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 435% · APY 4760%ROI 25.0% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+25.0%
APR (simple)scaled
+435%
ROI × 365/days
APY (compounded)if redeployed
+4760%
(1+ROI)^(365/d) − 1
Daily expectedper day
+1.07%
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 +0.46 pperosion 62% · break-even w/ fees 5.6%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$319
1.28% · g = 0.148%
Half Kelly½ f★
$160
0.64% · g = 0.114%
Quarter Kelly¼ f★
$80
0.32% · g = 0.068%
Flat 1%1%
$250
1.00% · g = 0.142%
Flat 2%2%
$500
2.00% · g = 0.110%
Flat 5%5%
$1,250
5.00% · g = -0.673%
Recommended¼ f★
$80
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.280 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.330 bit
Δ +0.050 bit vs market
Surprise · YES−log₂ p
4.37 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).
NOISE · D_KL(q ‖ p) = 0.0015 nat (0.0021 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 0.061 · CI [0.00, 0.22] · κ 14.8
Posterior meanE[θ]
0.061
Beta(0.9, 13.9)
95% credible intervalHDI
[0.00, 0.22]
price INSIDE → weak edge
Concentrationκ
14.8
pseudo-obs behind belief
Disagreementvs crowd
+1.2 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] +13.4% · P(YES) 5.5% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+13.40%
P(YES) empiricalq
5.5%
Best pathmax
+1961.9%
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 0.19% · ruin rate 0.5%400 paths × 120 bets · f deploy 0.64%
Sharpe / betμ/σ
0.076
μ 0.25% · σ 3.3%
Sortino / betμ/σ↓
0.396
downside-only denominator
VaR 95%5%
-0.6%
per-bet worst-case
CVaR 95%ES
-0.6%
mean tail loss
Max drawdownMDD
-9.2%
Calmar 0.02
Ruin rate≤50%
0.5%
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 -52.1pp · crowd gap -53.4pp
Anchor gapmodel − base
-52.1 pp
Crowd gapprice − base
-53.4 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 18.8% · AUC 0.761out-of-sample BSS (5-fold) 18.8% ± 2.6% · Brier 0.2030 · log-loss 0.6088 · n 1600✓ n = 1600
BrierBS
0.2030
lower = better · ō 0.50
BSSvs base
18.8%
improvement over base rate
ReliabilityREL
0.0050
miscalibration · want ↓
ResolutionRES
0.0520
decisiveness · want ↑
Log lossLL
0.6088
cross-entropy
AUCROC
0.761
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 1.47 · expectancy +0.186R180 trades · win 60.6% · Sharpe 0.173
Total P/Lnet
+$8,375
on $45,000 cycled
Win ratehit %
60.6%
109 W / 71 L
Profit factorPF
1.47
$ won / $ lost
Expectancyper trade
+$46.53
avg $ per position
R-expectancyper risk
+0.186R
in units of risk taken
Avg win / losspayoff
$239.68 / -$250.00
ratio 0.96 : 1
Sharpe / traderisk-adj
0.173
μR / σR
Closing line valueCLV
+3.02 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.