NOSTRADAMUS · Position Analytics Engine
SIMULATOR Ethereum Up or Down 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-up-or-down-on-june-15-2026 page.
▲ YES EDGE · +0.005 · f★ 20.0% · deploy 10.0% · net -0.25pp
§1 · Position economics
YES · Expected P/L per share +0.0050@ model P(YES) = 0.980
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 20.00% · g(f★) = 0.055%deploy 10.00% · g = 0.040%
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 @ 0.975 · EV +$13stake $2,500 · 10.00% of bankroll
Deployed stakestake
$2,500
10.00% of bankroll
Sharesunits
2,564
each pays $1 if YES
Max payoutwin
$2,564
gross, if win
Max profitwin
+$64
net of cost
Max losslose
-$2,500
binary settles to $0
Payout multiple×
×1.03
$1 → $1.03
Risk:RewardR:R
0.03 : 1
win $0.03 per $1
Expected P/LE[P/L]
+$13
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 98.0% | +$64 | +$63 |
| Resolves against (lose) | 2.0% | -$2,500 | -$50 |
| Expected value | 100.0% | — | +$13 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +0.5 pprelative edge +0.5%
Required win ratebreak-even
97.5%
price = implied probability
Model win rateP(win)
98.0%
what you forecast
Cushionedge
+0.5 pp
margin of safety
Fair pricemodel
0.980
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
97.5%
= price
Decimal oddsEU
1.026
total return per $1
AmericanUS
-3900
risk $3900 to win $100
FractionalUK
0.03 / 1
profit per $1 risked
Profit per $100stake
+$2.56
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 9% · APY 9%ROI 0.5% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+0.5%
APR (simple)scaled
+9%
ROI × 365/days
APY (compounded)if redeployed
+9%
(1+ROI)^(365/d) − 1
Daily expectedper day
+0.02%
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 -0.25 pperosion 150% · break-even w/ fees 98.3%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$5,000
20.00% · g = 0.055%
Half Kelly½ f★
$2,500
10.00% · g = 0.040%
Quarter Kelly¼ f★
$1,250
5.00% · g = 0.023%
Flat 1%1%
$250
1.00% · g = 0.005%
Flat 2%2%
$500
2.00% · g = 0.010%
Flat 5%5%
$1,250
5.00% · g = 0.023%
Recommended¼ f★
$1,250
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.169 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.141 bit
Δ -0.027 bit vs market
Surprise · YES−log₂ p
0.04 bit
self-information
Surprise · NO−log₂(1−p)
5.32 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0005 nat (0.0008 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 0.980 · CI [0.70, 1.00] · κ 4.4
Posterior meanE[θ]
0.980
Beta(4.4, 0.1)
95% credible intervalHDI
[0.70, 1.00]
price INSIDE → weak edge
Concentrationκ
4.4
pseudo-obs behind belief
Disagreementvs crowd
+0.5 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] +1.0% · P(YES) 98.5% · VaR₉₅ -2.6%400 paths · 504 bars to resolution
Expected P/Lper $1
+1.03%
P(YES) empiricalq
98.5%
Best pathmax
+2.6%
Worst pathmin
-100.0%
VaR 95%5%
-2.6%
CVaR 95%ES
26.7%
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 -0.19% · ruin rate 2.8%400 paths × 120 bets · f deploy 10.00%
Sharpe / betμ/σ
-0.072
μ -0.14% · σ 2.0%
Sortino / betμ/σ↓
-0.014
downside-only denominator
VaR 95%5%
0.3%
per-bet worst-case
CVaR 95%ES
-0.1%
mean tail loss
Max drawdownMDD
-24.3%
Calmar -0.01
Ruin rate≤50%
2.8%
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 +40.3pp · crowd gap +39.8pp
Anchor gapmodel − base
+40.3 pp
Crowd gapprice − base
+39.8 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 19.4% · AUC 0.763out-of-sample BSS (5-fold) 19.6% ± 3.6% · Brier 0.2014 · log-loss 0.5972 · n 1600✓ n = 1600
BrierBS
0.2014
lower = better · ō 0.51
BSSvs base
19.4%
improvement over base rate
ReliabilityREL
0.0054
miscalibration · want ↓
ResolutionRES
0.0540
decisiveness · want ↑
Log lossLL
0.5972
cross-entropy
AUCROC
0.763
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 0.86 · expectancy -0.069R180 trades · win 48.9% · Sharpe -0.067
Total P/Lnet
-$3,116
on $45,000 cycled
Win ratehit %
48.9%
88 W / 92 L
Profit factorPF
0.86
$ won / $ lost
Expectancyper trade
-$17.31
avg $ per position
R-expectancyper risk
-0.069R
in units of risk taken
Avg win / losspayoff
$225.96 / -$250.00
ratio 0.90 : 1
Sharpe / traderisk-adj
-0.067
μR / σR
Closing line valueCLV
+2.21 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.