NOSTRADAMUS · Position Analytics Engine
SIMULATOR Bitcoin Up or Down on June 14?
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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-bitcoin-up-or-down-on-june-14-2026 page.
▲ YES EDGE · +0.028 · f★ 12.1% · deploy 6.1% · net 2.09pp
§1 · Position economics
YES · Expected P/L per share +0.0284@ model P(YES) = 0.793
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 12.10% · g(f★) = 0.232%deploy 6.05% · g = 0.172%
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 @ 0.765 · EV +$56stake $1,513 · 6.05% of bankroll
Deployed stakestake
$1,513
6.05% of bankroll
Sharesunits
1,977
each pays $1 if YES
Max payoutwin
$1,977
gross, if win
Max profitwin
+$465
net of cost
Max losslose
-$1,513
binary settles to $0
Payout multiple×
×1.31
$1 → $1.31
Risk:RewardR:R
0.31 : 1
win $0.31 per $1
Expected P/LE[P/L]
+$56
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 79.3% | +$465 | +$369 |
| Resolves against (lose) | 20.7% | -$1,513 | -$312 |
| Expected value | 100.0% | — | +$56 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +2.8 pprelative edge +3.7%
Required win ratebreak-even
76.5%
price = implied probability
Model win rateP(win)
79.3%
what you forecast
Cushionedge
+2.8 pp
margin of safety
Fair pricemodel
0.793
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
76.5%
= price
Decimal oddsEU
1.307
total return per $1
AmericanUS
-326
risk $326 to win $100
FractionalUK
0.31 / 1
profit per $1 risked
Profit per $100stake
+$30.72
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 65% · APY 89%ROI 3.7% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+3.7%
APR (simple)scaled
+65%
ROI × 365/days
APY (compounded)if redeployed
+89%
(1+ROI)^(365/d) − 1
Daily expectedper day
+0.17%
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 +2.09 pperosion 26% · break-even w/ fees 77.3%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$3,025
12.10% · g = 0.232%
Half Kelly½ f★
$1,513
6.05% · g = 0.172%
Quarter Kelly¼ f★
$756
3.03% · g = 0.099%
Flat 1%1%
$250
1.00% · g = 0.036%
Flat 2%2%
$500
2.00% · g = 0.069%
Flat 5%5%
$1,250
5.00% · g = 0.150%
Recommended¼ f★
$756
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.787 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.735 bit
Δ -0.052 bit vs market
Surprise · YES−log₂ p
0.39 bit
self-information
Surprise · NO−log₂(1−p)
2.09 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0023 nat (0.0033 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 0.793 · CI [0.66, 0.90] · κ 44.5
Posterior meanE[θ]
0.793
Beta(35.3, 9.2)
95% credible intervalHDI
[0.66, 0.90]
price INSIDE → weak edge
Concentrationκ
44.5
pseudo-obs behind belief
Disagreementvs crowd
+2.8 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] +7.5% · P(YES) 82.3% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+7.52%
P(YES) empiricalq
82.3%
Best pathmax
+30.7%
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 0.23% · ruin rate 2.5%400 paths × 120 bets · f deploy 6.05%
Sharpe / betμ/σ
0.076
μ 0.24% · σ 3.2%
Sortino / betμ/σ↓
0.040
downside-only denominator
VaR 95%5%
-6.1%
per-bet worst-case
CVaR 95%ES
-6.1%
mean tail loss
Max drawdownMDD
-6.7%
Calmar 0.03
Ruin rate≤50%
2.5%
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 +20.6pp · crowd gap +17.8pp
Anchor gapmodel − base
+20.6 pp
Crowd gapprice − base
+17.8 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 25.5% · AUC 0.795out-of-sample BSS (5-fold) 25.5% ± 1.5% · Brier 0.1861 · log-loss 0.5613 · n 1600✓ n = 1600
BrierBS
0.1861
lower = better · ō 0.48
BSSvs base
25.5%
improvement over base rate
ReliabilityREL
0.0028
miscalibration · want ↓
ResolutionRES
0.0665
decisiveness · want ↑
Log lossLL
0.5613
cross-entropy
AUCROC
0.795
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 1.03 · expectancy +0.013R180 trades · win 50.6% · Sharpe 0.011
Total P/Lnet
+$601
on $45,000 cycled
Win ratehit %
50.6%
91 W / 89 L
Profit factorPF
1.03
$ won / $ lost
Expectancyper trade
+$3.34
avg $ per position
R-expectancyper risk
+0.013R
in units of risk taken
Avg win / losspayoff
$251.11 / -$250.00
ratio 1.00 : 1
Sharpe / traderisk-adj
0.011
μR / σR
Closing line valueCLV
+2.27 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.