NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Bitcoin reach $72,500 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-reach-72pt5k-in-june-2026 page.
▲ YES EDGE · +0.011 · f★ 1.1% · deploy 0.6% · net 0.34pp
§1 · Position economics
YES · Expected P/L per share +0.0109@ model P(YES) = 0.052
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 1.13% · g(f★) = 0.137%deploy 0.57% · g = 0.105%
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 @ 0.042 · EV +$37stake $142 · 0.57% of bankroll
Deployed stakestake
$142
0.57% of bankroll
Sharesunits
3,410
each pays $1 if YES
Max payoutwin
$3,410
gross, if win
Max profitwin
+$3,268
net of cost
Max losslose
-$142
binary settles to $0
Payout multiple×
×24.10
$1 → $24.10
Risk:RewardR:R
23.10 : 1
win $23.10 per $1
Expected P/LE[P/L]
+$37
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 5.2% | +$3,268 | +$171 |
| Resolves against (lose) | 94.8% | -$142 | -$134 |
| Expected value | 100.0% | — | +$37 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +1.1 pprelative edge +26.1%
Required win ratebreak-even
4.2%
price = implied probability
Model win rateP(win)
5.2%
what you forecast
Cushionedge
+1.1 pp
margin of safety
Fair pricemodel
0.052
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
4.2%
= price
Decimal oddsEU
24.096
total return per $1
AmericanUS
+2310
$100 wins $2310
FractionalUK
23.10 / 1
profit per $1 risked
Profit per $100stake
+$2309.64
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 454% · APY 5566%ROI 26.1% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+26.1%
APR (simple)scaled
+454%
ROI × 365/days
APY (compounded)if redeployed
+5566%
(1+ROI)^(365/d) − 1
Daily expectedper day
+1.11%
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 +0.34 pperosion 69% · break-even w/ fees 4.9%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$283
1.13% · g = 0.137%
Half Kelly½ f★
$142
0.57% · g = 0.105%
Quarter Kelly¼ f★
$71
0.28% · g = 0.063%
Flat 1%1%
$250
1.00% · g = 0.135%
Flat 2%2%
$500
2.00% · g = 0.074%
Flat 5%5%
$1,250
5.00% · g = -0.842%
Recommended¼ f★
$71
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.249 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.296 bit
Δ +0.047 bit vs market
Surprise · YES−log₂ p
4.59 bit
self-information
Surprise · NO−log₂(1−p)
0.06 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0014 nat (0.0020 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 0.052 · CI [0.00, 0.22] · κ 12.8
Posterior meanE[θ]
0.052
Beta(0.7, 12.1)
95% credible intervalHDI
[0.00, 0.22]
price INSIDE → weak edge
Concentrationκ
12.8
pseudo-obs behind belief
Disagreementvs crowd
+1.1 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] +14.5% · P(YES) 4.8% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+14.46%
P(YES) empiricalq
4.8%
Best pathmax
+2309.6%
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 0.18% · ruin rate 0.0%400 paths × 120 bets · f deploy 0.57%
Sharpe / betμ/σ
0.089
μ 0.29% · σ 3.3%
Sortino / betμ/σ↓
0.520
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%
0.0%
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 -46.1pp · crowd gap -47.2pp
Anchor gapmodel − base
-46.1 pp
Crowd gapprice − base
-47.2 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 17.4% · AUC 0.754out-of-sample BSS (5-fold) 17.5% ± 1.6% · Brier 0.2065 · log-loss 0.6164 · n 1600✓ n = 1600
BrierBS
0.2065
lower = better · ō 0.51
BSSvs base
17.4%
improvement over base rate
ReliabilityREL
0.0055
miscalibration · want ↓
ResolutionRES
0.0486
decisiveness · want ↑
Log lossLL
0.6164
cross-entropy
AUCROC
0.754
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 1.33 · expectancy +0.136R180 trades · win 58.3% · Sharpe 0.125
Total P/Lnet
+$6,116
on $45,000 cycled
Win ratehit %
58.3%
105 W / 75 L
Profit factorPF
1.33
$ won / $ lost
Expectancyper trade
+$33.98
avg $ per position
R-expectancyper risk
+0.136R
in units of risk taken
Avg win / losspayoff
$236.82 / -$250.00
ratio 0.95 : 1
Sharpe / traderisk-adj
0.125
μR / σR
Closing line valueCLV
+3.19 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.