NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will the price of Ethereum be above $1,700 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-1700-on-june-15-2026 page.
▲ YES EDGE · +0.060 · f★ 24.9% · deploy 12.5% · net 5.24pp
§1 · Position economics
YES · Expected P/L per share +0.0599@ model P(YES) = 0.820
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 24.95% · g(f★) = 1.048%deploy 12.47% · g = 0.768%
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 @ 0.760 · EV +$246stake $3,119 · 12.47% of bankroll
Deployed stakestake
$3,119
12.47% of bankroll
Sharesunits
4,103
each pays $1 if YES
Max payoutwin
$4,103
gross, if win
Max profitwin
+$985
net of cost
Max losslose
-$3,119
binary settles to $0
Payout multiple×
×1.32
$1 → $1.32
Risk:RewardR:R
0.32 : 1
win $0.32 per $1
Expected P/LE[P/L]
+$246
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 82.0% | +$985 | +$807 |
| Resolves against (lose) | 18.0% | -$3,119 | -$562 |
| Expected value | 100.0% | — | +$246 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +6.0 pprelative edge +7.9%
Required win ratebreak-even
76.0%
price = implied probability
Model win rateP(win)
82.0%
what you forecast
Cushionedge
+6.0 pp
margin of safety
Fair pricemodel
0.820
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
76.0%
= price
Decimal oddsEU
1.316
total return per $1
AmericanUS
-317
risk $317 to win $100
FractionalUK
0.32 / 1
profit per $1 risked
Profit per $100stake
+$31.58
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 137% · APY 274%ROI 7.9% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+7.9%
APR (simple)scaled
+137%
ROI × 365/days
APY (compounded)if redeployed
+274%
(1+ROI)^(365/d) − 1
Daily expectedper day
+0.36%
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 +5.24 pperosion 13% · break-even w/ fees 76.8%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$6,237
24.95% · g = 1.048%
Half Kelly½ f★
$3,119
12.47% · g = 0.768%
Quarter Kelly¼ f★
$1,559
6.24% · g = 0.439%
Flat 1%1%
$250
1.00% · g = 0.077%
Flat 2%2%
$500
2.00% · g = 0.152%
Flat 5%5%
$1,250
5.00% · g = 0.361%
Recommended¼ f★
$1,559
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.795 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.680 bit
Δ -0.115 bit vs market
Surprise · YES−log₂ p
0.40 bit
self-information
Surprise · NO−log₂(1−p)
2.06 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0105 nat (0.0151 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 0.820 · CI [0.69, 0.92] · κ 40.0
Posterior meanE[θ]
0.820
Beta(32.8, 7.2)
95% credible intervalHDI
[0.69, 0.92]
price INSIDE → weak edge
Concentrationκ
40.0
pseudo-obs behind belief
Disagreementvs crowd
+6.0 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] +6.9% · P(YES) 81.3% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+6.91%
P(YES) empiricalq
81.3%
Best pathmax
+31.6%
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 0.86% · ruin rate 6.3%400 paths × 120 bets · f deploy 12.47%
Sharpe / betμ/σ
0.157
μ 0.99% · σ 6.3%
Sortino / betμ/σ↓
0.079
downside-only denominator
VaR 95%5%
-12.5%
per-bet worst-case
CVaR 95%ES
-12.5%
mean tail loss
Max drawdownMDD
-12.5%
Calmar 0.07
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 +35.1pp · crowd gap +29.1pp
Anchor gapmodel − base
+35.1 pp
Crowd gapprice − base
+29.1 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 15.9% · AUC 0.747out-of-sample BSS (5-fold) 15.9% ± 3.0% · Brier 0.2101 · log-loss 0.6328 · n 1600✓ n = 1600
BrierBS
0.2101
lower = better · ō 0.49
BSSvs base
15.9%
improvement over base rate
ReliabilityREL
0.0070
miscalibration · want ↓
ResolutionRES
0.0465
decisiveness · want ↑
Log lossLL
0.6328
cross-entropy
AUCROC
0.747
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 1.28 · expectancy +0.126R180 trades · win 54.4% · Sharpe 0.111
Total P/Lnet
+$5,686
on $45,000 cycled
Win ratehit %
54.4%
98 W / 82 L
Profit factorPF
1.28
$ won / $ lost
Expectancyper trade
+$31.59
avg $ per position
R-expectancyper risk
+0.126R
in units of risk taken
Avg win / losspayoff
$267.20 / -$250.00
ratio 1.07 : 1
Sharpe / traderisk-adj
0.111
μR / σR
Closing line valueCLV
+3.10 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.