NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Ethereum reach $1,750 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-ethereum-reach-1750-on-june-14 page.
▲ YES EDGE · +0.060 · f★ 6.3% · deploy 3.1% · net 5.25pp
§1 · Position economics
YES · Expected P/L per share +0.0600@ model P(YES) = 0.103
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 6.27% · g(f★) = 3.163%deploy 3.14% · g = 2.571%
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 @ 0.043 · EV +$1,081stake $784 · 3.14% of bankroll
Deployed stakestake
$784
3.14% of bankroll
Sharesunits
18,024
each pays $1 if YES
Max payoutwin
$18,024
gross, if win
Max profitwin
+$17,239
net of cost
Max losslose
-$784
binary settles to $0
Payout multiple×
×22.99
$1 → $22.99
Risk:RewardR:R
21.99 : 1
win $21.99 per $1
Expected P/LE[P/L]
+$1,081
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 10.3% | +$17,239 | +$1,784 |
| Resolves against (lose) | 89.7% | -$784 | -$703 |
| Expected value | 100.0% | — | +$1,081 |
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 +137.9%
Required win ratebreak-even
4.3%
price = implied probability
Model win rateP(win)
10.3%
what you forecast
Cushionedge
+6.0 pp
margin of safety
Fair pricemodel
0.103
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
4.3%
= price
Decimal oddsEU
22.989
total return per $1
AmericanUS
+2199
$100 wins $2199
FractionalUK
21.99 / 1
profit per $1 risked
Profit per $100stake
+$2198.85
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 2397% · APY 348817912%ROI 137.9% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+137.9%
APR (simple)scaled
+2397%
ROI × 365/days
APY (compounded)if redeployed
+348817912%
(1+ROI)^(365/d) − 1
Daily expectedper day
+4.21%
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 +5.25 pperosion 13% · break-even w/ fees 5.1%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$1,568
6.27% · g = 3.163%
Half Kelly½ f★
$784
3.14% · g = 2.571%
Quarter Kelly¼ f★
$392
1.57% · g = 1.649%
Flat 1%1%
$250
1.00% · g = 1.156%
Flat 2%2%
$500
2.00% · g = 1.961%
Flat 5%5%
$1,250
5.00% · g = 3.077%
Recommended¼ f★
$392
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.258 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.480 bit
Δ +0.222 bit vs market
Surprise · YES−log₂ p
4.52 bit
self-information
Surprise · NO−log₂(1−p)
0.06 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
SIGNAL · D_KL(q ‖ p) = 0.0316 nat (0.0456 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 0.103 · CI [0.02, 0.25] · κ 24.8
Posterior meanE[θ]
0.103
Beta(2.6, 22.2)
95% credible intervalHDI
[0.02, 0.25]
price INSIDE → weak edge
Concentrationκ
24.8
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] +101.1% · P(YES) 8.8% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+101.15%
P(YES) empiricalq
8.8%
Best pathmax
+2198.9%
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 2.68% · ruin rate 13.8%400 paths × 120 bets · f deploy 3.14%
Sharpe / betμ/σ
0.200
μ 4.41% · σ 22.1%
Sortino / betμ/σ↓
1.407
downside-only denominator
VaR 95%5%
-3.1%
per-bet worst-case
CVaR 95%ES
-3.1%
mean tail loss
Max drawdownMDD
-29.6%
Calmar 0.09
Ruin rate≤50%
13.8%
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 -41.6pp · crowd gap -47.6pp
Anchor gapmodel − base
-41.6 pp
Crowd gapprice − base
-47.6 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 16.8% · AUC 0.750out-of-sample BSS (5-fold) 16.8% ± 3.2% · Brier 0.2080 · log-loss 0.6164 · n 1600✓ n = 1600
BrierBS
0.2080
lower = better · ō 0.51
BSSvs base
16.8%
improvement over base rate
ReliabilityREL
0.0062
miscalibration · want ↓
ResolutionRES
0.0481
decisiveness · want ↑
Log lossLL
0.6164
cross-entropy
AUCROC
0.750
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 1.13 · expectancy +0.062R180 trades · win 52.8% · Sharpe 0.055
Total P/Lnet
+$2,781
on $45,000 cycled
Win ratehit %
52.8%
95 W / 85 L
Profit factorPF
1.13
$ won / $ lost
Expectancyper trade
+$15.45
avg $ per position
R-expectancyper risk
+0.062R
in units of risk taken
Avg win / losspayoff
$252.96 / -$250.00
ratio 1.01 : 1
Sharpe / traderisk-adj
0.055
μR / σR
Closing line valueCLV
+3.26 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.