NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Bitcoin reach $66,000 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-will-bitcoin-reach-66k-on-june-14 page.
▲ YES EDGE · +0.056 · f★ 15.1% · deploy 7.6% · net 4.89pp
§1 · Position economics
YES · Expected P/L per share +0.0564@ model P(YES) = 0.683
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 15.11% · g(f★) = 0.695%deploy 7.55% · g = 0.517%
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 @ 0.627 · EV +$170stake $1,889 · 7.55% of bankroll
Deployed stakestake
$1,889
7.55% of bankroll
Sharesunits
3,012
each pays $1 if YES
Max payoutwin
$3,012
gross, if win
Max profitwin
+$1,124
net of cost
Max losslose
-$1,889
binary settles to $0
Payout multiple×
×1.59
$1 → $1.59
Risk:RewardR:R
0.59 : 1
win $0.59 per $1
Expected P/LE[P/L]
+$170
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 68.3% | +$1,124 | +$768 |
| Resolves against (lose) | 31.7% | -$1,889 | -$598 |
| Expected value | 100.0% | — | +$170 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +5.6 pprelative edge +9.0%
Required win ratebreak-even
62.7%
price = implied probability
Model win rateP(win)
68.3%
what you forecast
Cushionedge
+5.6 pp
margin of safety
Fair pricemodel
0.683
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
62.7%
= price
Decimal oddsEU
1.595
total return per $1
AmericanUS
-168
risk $168 to win $100
FractionalUK
0.59 / 1
profit per $1 risked
Profit per $100stake
+$59.49
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 156% · APY 346%ROI 9.0% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+9.0%
APR (simple)scaled
+156%
ROI × 365/days
APY (compounded)if redeployed
+346%
(1+ROI)^(365/d) − 1
Daily expectedper day
+0.41%
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 +4.89 pperosion 13% · break-even w/ fees 63.4%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$3,777
15.11% · g = 0.695%
Half Kelly½ f★
$1,889
7.55% · g = 0.517%
Quarter Kelly¼ f★
$944
3.78% · g = 0.299%
Flat 1%1%
$250
1.00% · g = 0.087%
Flat 2%2%
$500
2.00% · g = 0.169%
Flat 5%5%
$1,250
5.00% · g = 0.379%
Recommended¼ f★
$944
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.953 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.901 bit
Δ -0.052 bit vs market
Surprise · YES−log₂ p
0.67 bit
self-information
Surprise · NO−log₂(1−p)
1.42 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0070 nat (0.0100 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 0.683 · CI [0.56, 0.79] · κ 59.1
Posterior meanE[θ]
0.683
Beta(40.4, 18.7)
95% credible intervalHDI
[0.56, 0.79]
price INSIDE → weak edge
Concentrationκ
59.1
pseudo-obs behind belief
Disagreementvs crowd
+5.6 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] +13.6% · P(YES) 71.3% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+13.64%
P(YES) empiricalq
71.3%
Best pathmax
+59.5%
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 0.52% · ruin rate 6.3%400 paths × 120 bets · f deploy 7.55%
Sharpe / betμ/σ
0.119
μ 0.67% · σ 5.6%
Sortino / betμ/σ↓
0.088
downside-only denominator
VaR 95%5%
-7.6%
per-bet worst-case
CVaR 95%ES
-7.6%
mean tail loss
Max drawdownMDD
-10.7%
Calmar 0.05
Ruin rate≤50%
6.3%
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 +12.5pp · crowd gap +6.9pp
Anchor gapmodel − base
+12.5 pp
Crowd gapprice − base
+6.9 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 18.2% · AUC 0.758out-of-sample BSS (5-fold) 18.4% ± 1.4% · Brier 0.2046 · log-loss 0.6189 · n 1600✓ n = 1600
BrierBS
0.2046
lower = better · ō 0.50
BSSvs base
18.2%
improvement over base rate
ReliabilityREL
0.0058
miscalibration · want ↓
ResolutionRES
0.0514
decisiveness · want ↑
Log lossLL
0.6189
cross-entropy
AUCROC
0.758
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 1.61 · expectancy +0.242R180 trades · win 60.6% · Sharpe 0.197
Total P/Lnet
+$10,906
on $45,000 cycled
Win ratehit %
60.6%
109 W / 71 L
Profit factorPF
1.61
$ won / $ lost
Expectancyper trade
+$60.59
avg $ per position
R-expectancyper risk
+0.242R
in units of risk taken
Avg win / losspayoff
$262.90 / -$250.00
ratio 1.05 : 1
Sharpe / traderisk-adj
0.197
μR / σR
Closing line valueCLV
+3.28 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.