NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Bitcoin dip to $63,000 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-dip-to-63k-on-june-14 page.
▲ YES EDGE · +0.015 · f★ 1.5% · deploy 0.7% · net 0.72pp
§1 · Position economics
YES · Expected P/L per share +0.0147@ model P(YES) = 0.027
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 1.49% · g(f★) = 0.675%deploy 0.74% · g = 0.548%
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 @ 0.012 · EV +$227stake $186 · 0.74% of bankroll
Deployed stakestake
$186
0.74% of bankroll
Sharesunits
15,478
each pays $1 if YES
Max payoutwin
$15,478
gross, if win
Max profitwin
+$15,293
net of cost
Max losslose
-$186
binary settles to $0
Payout multiple×
×83.33
$1 → $83.33
Risk:RewardR:R
82.33 : 1
win $82.33 per $1
Expected P/LE[P/L]
+$227
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 2.7% | +$15,293 | +$408 |
| Resolves against (lose) | 97.3% | -$186 | -$181 |
| Expected value | 100.0% | — | +$227 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +1.5 pprelative edge +122.3%
Required win ratebreak-even
1.2%
price = implied probability
Model win rateP(win)
2.7%
what you forecast
Cushionedge
+1.5 pp
margin of safety
Fair pricemodel
0.027
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
1.2%
= price
Decimal oddsEU
83.333
total return per $1
AmericanUS
+8233
$100 wins $8233
FractionalUK
82.33 / 1
profit per $1 risked
Profit per $100stake
+$8233.33
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 2126% · APY 107521943%ROI 122.3% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+122.3%
APR (simple)scaled
+2126%
ROI × 365/days
APY (compounded)if redeployed
+107521943%
(1+ROI)^(365/d) − 1
Daily expectedper day
+3.88%
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 +0.72 pperosion 51% · break-even w/ fees 1.9%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$371
1.49% · g = 0.675%
Half Kelly½ f★
$186
0.74% · g = 0.548%
Quarter Kelly¼ f★
$93
0.37% · g = 0.350%
Flat 1%1%
$250
1.00% · g = 0.624%
Flat 2%2%
$500
2.00% · g = 0.630%
Flat 5%5%
$1,250
5.00% · g = -0.637%
Recommended¼ f★
$93
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.094 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.177 bit
Δ +0.084 bit vs market
Surprise · YES−log₂ p
6.38 bit
self-information
Surprise · NO−log₂(1−p)
0.02 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0067 nat (0.0097 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 0.027 · CI [0.00, 0.25] · κ 6.2
Posterior meanE[θ]
0.027
Beta(0.2, 6.0)
95% credible intervalHDI
[0.00, 0.25]
price INSIDE → weak edge
Concentrationκ
6.2
pseudo-obs behind belief
Disagreementvs crowd
+0.7 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] +108.3% · P(YES) 2.5% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+108.33%
P(YES) empiricalq
2.5%
Best pathmax
+8233.3%
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 1.28% · ruin rate 2.0%400 paths × 120 bets · f deploy 0.74%
Sharpe / betμ/σ
0.157
μ 2.00% · σ 12.7%
Sortino / betμ/σ↓
2.698
downside-only denominator
VaR 95%5%
-0.7%
per-bet worst-case
CVaR 95%ES
-0.7%
mean tail loss
Max drawdownMDD
-15.8%
Calmar 0.08
Ruin rate≤50%
2.0%
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 -55.4pp · crowd gap -56.9pp
Anchor gapmodel − base
-55.4 pp
Crowd gapprice − base
-56.9 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 18.0% · AUC 0.757out-of-sample BSS (5-fold) 18.1% ± 1.8% · Brier 0.2049 · log-loss 0.6128 · n 1600✓ n = 1600
BrierBS
0.2049
lower = better · ō 0.51
BSSvs base
18.0%
improvement over base rate
ReliabilityREL
0.0052
miscalibration · want ↓
ResolutionRES
0.0492
decisiveness · want ↑
Log lossLL
0.6128
cross-entropy
AUCROC
0.757
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 1.25 · expectancy +0.112R180 trades · win 55.0% · Sharpe 0.090
Total P/Lnet
+$5,041
on $45,000 cycled
Win ratehit %
55.0%
99 W / 81 L
Profit factorPF
1.25
$ won / $ lost
Expectancyper trade
+$28.00
avg $ per position
R-expectancyper risk
+0.112R
in units of risk taken
Avg win / losspayoff
$255.46 / -$250.00
ratio 1.02 : 1
Sharpe / traderisk-adj
0.090
μR / σR
Closing line valueCLV
+3.16 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.