NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Bitcoin reach $70,000 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-reach-70000-in-june-2026-from-june-2 page.
▲ YES EDGE · +0.010 · f★ 1.3% · deploy 0.7% · net 0.23pp
§1 · Position economics
YES · Expected P/L per share +0.0098@ model P(YES) = 0.285
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 1.35% · g(f★) = 0.024%deploy 0.67% · g = 0.018%
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 @ 0.275 · EV +$6stake $169 · 0.67% of bankroll
Deployed stakestake
$169
0.67% of bankroll
Sharesunits
613
each pays $1 if YES
Max payoutwin
$613
gross, if win
Max profitwin
+$444
net of cost
Max losslose
-$169
binary settles to $0
Payout multiple×
×3.64
$1 → $3.64
Risk:RewardR:R
2.64 : 1
win $2.64 per $1
Expected P/LE[P/L]
+$6
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 28.5% | +$444 | +$127 |
| Resolves against (lose) | 71.5% | -$169 | -$121 |
| Expected value | 100.0% | — | +$6 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +1.0 pprelative edge +3.6%
Required win ratebreak-even
27.5%
price = implied probability
Model win rateP(win)
28.5%
what you forecast
Cushionedge
+1.0 pp
margin of safety
Fair pricemodel
0.285
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
27.5%
= price
Decimal oddsEU
3.636
total return per $1
AmericanUS
+264
$100 wins $264
FractionalUK
2.64 / 1
profit per $1 risked
Profit per $100stake
+$263.64
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 62% · APY 84%ROI 3.6% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+3.6%
APR (simple)scaled
+62%
ROI × 365/days
APY (compounded)if redeployed
+84%
(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 +0.23 pperosion 77% · break-even w/ fees 28.3%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$337
1.35% · g = 0.024%
Half Kelly½ f★
$169
0.67% · g = 0.018%
Quarter Kelly¼ f★
$84
0.34% · g = 0.010%
Flat 1%1%
$250
1.00% · g = 0.022%
Flat 2%2%
$500
2.00% · g = 0.018%
Flat 5%5%
$1,250
5.00% · g = -0.142%
Recommended¼ f★
$84
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.849 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.862 bit
Δ +0.013 bit vs market
Surprise · YES−log₂ p
1.86 bit
self-information
Surprise · NO−log₂(1−p)
0.46 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0002 nat (0.0003 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 0.285 · CI [0.18, 0.41] · κ 55.6
Posterior meanE[θ]
0.285
Beta(15.8, 39.8)
95% credible intervalHDI
[0.18, 0.41]
price INSIDE → weak edge
Concentrationκ
55.6
pseudo-obs behind belief
Disagreementvs crowd
+1.0 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] -1.8% · P(YES) 27.0% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
-1.82%
P(YES) empiricalq
27.0%
Best pathmax
+263.6%
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 0.03% · ruin rate 0.0%400 paths × 120 bets · f deploy 0.67%
Sharpe / betμ/σ
0.028
μ 0.03% · σ 1.1%
Sortino / betμ/σ↓
0.046
downside-only denominator
VaR 95%5%
-0.7%
per-bet worst-case
CVaR 95%ES
-0.7%
mean tail loss
Max drawdownMDD
-2.5%
Calmar 0.01
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 -22.3pp · crowd gap -23.3pp
Anchor gapmodel − base
-22.3 pp
Crowd gapprice − base
-23.3 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 23.3% · AUC 0.783out-of-sample BSS (5-fold) 23.4% ± 1.8% · Brier 0.1914 · log-loss 0.5724 · n 1600✓ n = 1600
BrierBS
0.1914
lower = better · ō 0.52
BSSvs base
23.3%
improvement over base rate
ReliabilityREL
0.0029
miscalibration · want ↓
ResolutionRES
0.0608
decisiveness · want ↑
Log lossLL
0.5724
cross-entropy
AUCROC
0.783
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 1.15 · expectancy +0.066R180 trades · win 55.6% · Sharpe 0.058
Total P/Lnet
+$2,990
on $45,000 cycled
Win ratehit %
55.6%
100 W / 80 L
Profit factorPF
1.15
$ won / $ lost
Expectancyper trade
+$16.61
avg $ per position
R-expectancyper risk
+0.066R
in units of risk taken
Avg win / losspayoff
$229.90 / -$250.00
ratio 0.92 : 1
Sharpe / traderisk-adj
0.058
μR / σR
Closing line valueCLV
+2.54 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.