NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will the price of Ethereum be above $1,900 on June 15?
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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-ethereum-above-1900-on-june-15-2026 page.
▲ YES EDGE · +0.035 · f★ 3.5% · deploy 1.7% · net 2.72pp
§1 · Position economics
YES · Expected P/L per share +0.0347@ model P(YES) = 0.041
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 3.49% · g(f★) = 4.200%deploy 1.75% · g = 3.667%
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 @ 0.006 · EV +$2,331stake $437 · 1.75% of bankroll
Deployed stakestake
$437
1.75% of bankroll
Sharesunits
67,171
each pays $1 if YES
Max payoutwin
$67,171
gross, if win
Max profitwin
+$66,734
net of cost
Max losslose
-$437
binary settles to $0
Payout multiple×
×153.85
$1 → $153.85
Risk:RewardR:R
152.85 : 1
win $152.85 per $1
Expected P/LE[P/L]
+$2,331
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 4.1% | +$66,734 | +$2,750 |
| Resolves against (lose) | 95.9% | -$437 | -$419 |
| Expected value | 100.0% | — | +$2,331 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +3.5 pprelative edge +533.9%
Required win ratebreak-even
0.7%
price = implied probability
Model win rateP(win)
4.1%
what you forecast
Cushionedge
+3.5 pp
margin of safety
Fair pricemodel
0.041
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
0.7%
= price
Decimal oddsEU
153.846
total return per $1
AmericanUS
+15285
$100 wins $15285
FractionalUK
152.85 / 1
profit per $1 risked
Profit per $100stake
+$15284.62
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 9279% · APY 8701095314809533%ROI 533.9% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+533.9%
APR (simple)scaled
+9279%
ROI × 365/days
APY (compounded)if redeployed
+8701095314809533%
(1+ROI)^(365/d) − 1
Daily expectedper day
+9.19%
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 +2.72 pperosion 22% · break-even w/ fees 1.4%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$873
3.49% · g = 4.200%
Half Kelly½ f★
$437
1.75% · g = 3.667%
Quarter Kelly¼ f★
$218
0.87% · g = 2.652%
Flat 1%1%
$250
1.00% · g = 2.858%
Flat 2%2%
$500
2.00% · g = 3.833%
Flat 5%5%
$1,250
5.00% · g = 3.968%
Recommended¼ f★
$218
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.057 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.248 bit
Δ +0.191 bit vs market
Surprise · YES−log₂ p
7.27 bit
self-information
Surprise · NO−log₂(1−p)
0.01 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
SIGNAL · D_KL(q ‖ p) = 0.0420 nat (0.0606 bit)exploitable edge present
YES contributionNO contributionbelief ‖ marketsignal
Zero KL ⇒ you know nothing the crowd doesn't.
§8 · Bayesian inference
MARKET PRICE INSIDE 95% CIposterior μ 0.041 · CI [0.00, 0.22] · κ 10.0
Posterior meanE[θ]
0.041
Beta(0.4, 9.6)
95% credible intervalHDI
[0.00, 0.22]
price INSIDE → weak edge
Concentrationκ
10.0
pseudo-obs behind belief
Disagreementvs crowd
+2.1 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] +284.6% · P(YES) 2.5% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+284.62%
P(YES) empiricalq
2.5%
Best pathmax
+15284.6%
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 4.94% · ruin rate 11.8%400 paths × 120 bets · f deploy 1.75%
Sharpe / betμ/σ
0.206
μ 12.34% · σ 59.9%
Sortino / betμ/σ↓
7.064
downside-only denominator
VaR 95%5%
-1.7%
per-bet worst-case
CVaR 95%ES
-1.7%
mean tail loss
Max drawdownMDD
-32.1%
Calmar 0.15
Ruin rate≤50%
11.8%
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 -48.6pp · crowd gap -52.1pp
Anchor gapmodel − base
-48.6 pp
Crowd gapprice − base
-52.1 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 21.6% · AUC 0.776out-of-sample BSS (5-fold) 21.8% ± 1.6% · Brier 0.1958 · log-loss 0.5914 · n 1600✓ n = 1600
BrierBS
0.1958
lower = better · ō 0.48
BSSvs base
21.6%
improvement over base rate
ReliabilityREL
0.0043
miscalibration · want ↓
ResolutionRES
0.0580
decisiveness · want ↑
Log lossLL
0.5914
cross-entropy
AUCROC
0.776
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)
BLEEDING · PF 0.94 · expectancy -0.031R180 trades · win 50.0% · Sharpe -0.029
Total P/Lnet
-$1,380
on $45,000 cycled
Win ratehit %
50.0%
90 W / 90 L
Profit factorPF
0.94
$ won / $ lost
Expectancyper trade
-$7.67
avg $ per position
R-expectancyper risk
-0.031R
in units of risk taken
Avg win / losspayoff
$234.66 / -$250.00
ratio 0.94 : 1
Sharpe / traderisk-adj
-0.029
μR / σR
Closing line valueCLV
+2.93 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.