NOSTRADAMUS · Position Analytics Engine

SIMULATOR Draw

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/hl-pred-draw-295 page.

▲ YES EDGE · +0.002 · f★ 0.3% · deploy 0.1% · net -0.50pp

§1 · Position economics

Payoff diagram · binary contract P/L vs resolution
YES · Expected P/L per share +0.0025@ model P(YES) = 0.074
-1.00-0.50+0.00+0.50+1.000.000.200.400.600.801.00price 0.071model 0.074YES resolution priceP/L per $1 contract
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
Kelly growth curve · g(f) with f★ and deployed f markers
f★ = 0.27% · g(f★) = 0.005%deploy 0.13% · g = 0.003%
-2.01%-1.51%-1.00%-0.50%0.01%0%8%16%24%32%40%f★ optimumdeployfraction of bankroll fexpected log-growth g(f)
g(f)f★ optimumdeployed fgrowth zone
Underbet leaves growth on the table; overbet destroys capital. The interior maximum is f★.

§2 · The trade ticket

Trade ticket · dollar outcomes at this stake
YES @ 0.071 · EV +$1stake $33 · 0.13% of bankroll
Deployed stakestake
$33
0.13% of bankroll
Sharesunits
467
each pays $1 if YES
Max payoutwin
$467
gross, if win
Max profitwin
+$434
net of cost
Max losslose
-$33
binary settles to $0
Payout multiple×
×14.05
$1 → $14.05
Risk:RewardR:R
13.05 : 1
win $13.05 per $1
Expected P/LE[P/L]
+$1
probability-weighted
OutcomeP(model)P/LContribution
Resolves YES (win)7.4%+$434+$32
Resolves against (lose)92.6%-$33-$31
Expected value100.0%+$1
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.

§3 · Break-even & cushion

Break-even & cushion · margin of safety
Cushion +0.2 pprelative edge +3.5%
Required win ratebreak-even
7.1%
price = implied probability
Model win rateP(win)
7.4%
what you forecast
Cushionedge
+0.2 pp
margin of safety
Fair pricemodel
0.074
where you think it should trade
-60-3003060020406080100you @ 7.1%market price (%)cushion (pp)
The market price equals the win rate you must beat to make money.

§4 · Odds conversion

Implied probability, decimal, American, fractional
Implied probabilityP
7.1%
= price
Decimal oddsEU
14.055
total return per $1
AmericanUS
+1305
$100 wins $1305
FractionalUK
13.05 / 1
profit per $1 risked
Profit per $100stake
+$1305.48
clean dollar framing
-1000-5000+500+1000020406080100you · 7.1%implied probability (%)American odds
underdog (+)favorite (-)your price
Five views of the same number.

§4b · Time & annualized return

Time & APR · capital lockup vs annualized return
APR 60% · APY 81%ROI 3.5% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+3.5%
APR (simple)scaled
+60%
ROI × 365/days
APY (compounded)if redeployed
+81%
(1+ROI)^(365/d) − 1
Daily expectedper day
+0.16%
geometric, per day held
Capital turns/yrvelocity
×17.4
how often this slot recycles
0%220%440%660%880%1100%121416180100120now 21ddays to resolutionannualized return (capped 1000%)
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

Cost waterfall · gross edge → net of friction
Net edge -0.50 pperosion 304% · break-even w/ fees 7.9%
-0.7pp-0.5pp-0.3pp-0.0pp0.2pp0.4pp+0.25Gross edge-0.75- ½ spread+0.00- entry fee+0.00- exit fee-0.50Net edgeEV / share (pp)
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.

§6 · Sizing menu

Sizing menu · disciplined deployment
Full Kellyf★
$66
0.27% · g = 0.005%
Half Kelly½ f★
$33
0.13% · g = 0.003%
Quarter Kelly¼ f★
$17
0.07% · g = 0.002%
Flat 1%1%
$250
1.00% · g = -0.028%
Flat 2%2%
$500
2.00% · g = -0.164%
Flat 5%5%
$1,250
5.00% · g = -1.053%
Recommended¼ f★
$17
survives model error
$0$369$738$1,106$1,475$66Full Kelly0.27%$33Half Kelly0.13%$17Quarter Kelly0.07%$250Flat 1%1.00%$500Flat 2%2.00%$1,250Flat 5%5.00%
Quarter-Kelly is the industry default — survives model error far better than full Kelly.

§7 · Information theory

Binary entropy · uncertainty in bits
Market entropyH(p)
0.370 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.379 bit
Δ +0.009 bit vs market
Surprise · YES−log₂ p
3.81 bit
self-information
Surprise · NO−log₂(1−p)
0.11 bit
self-information
0.000.260.530.791.050.00.20.40.60.81.0marketmodelprobabilityH (bits)
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
KL divergence · upper bound on exploitable edge
NOISE · D_KL(q ‖ p) = 0.0000 nat (0.0001 bit)belief ≈ market — stand down
-0.004-0.002-0.0000.0010.0030.0025YES branch-0.0025NO branchΣKL = 0.0000 natKL contribution (nat)
YES contributionNO contributionbelief ‖ marketnoise
Zero KL ⇒ you know nothing the crowd doesn't.

§8 · Bayesian inference

Bayesian posterior · prior + evidence → belief with 95% CI
MARKET PRICE INSIDE 95% CIposterior μ 0.074 · CI [0.00, 0.23] · κ 17.9
Posterior meanE[θ]
0.074
Beta(1.3, 16.6)
95% credible intervalHDI
[0.00, 0.23]
price INSIDE → weak edge
Concentrationκ
17.9
pseudo-obs behind belief
Disagreementvs crowd
+0.2 pp
posterior − price
0.000.200.400.600.801.00marketposterior μprobability θposterior density
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)

Mark-to-market MC · single position held to resolution
E[P/L] +5.4% · P(YES) 7.5% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+5.41%
P(YES) empiricalq
7.5%
Best pathmax
+1305.5%
Worst pathmin
-100.0%
VaR 95%5%
100.0%
CVaR 95%ES
100.0%
25¢50¢75¢100¢084168252336420504entry 7.1¢model q 7.4¢bars until resolutionprice path
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)

Monte-Carlo equity fan · this profile, repeated 400× independently
Median CAGR/bet 0.01% · ruin rate 0.0%400 paths × 120 bets · f deploy 0.50%
Sharpe / betμ/σ
0.032
μ 0.06% · σ 1.9%
Sortino / betμ/σ↓
0.120
downside-only denominator
VaR 95%5%
-0.5%
per-bet worst-case
CVaR 95%ES
-0.5%
mean tail loss
Max drawdownMDD
-6.8%
Calmar 0.00
Ruin rate≤50%
0.0%
P(equity ever ≤ 50%)
0.73×0.90×1.08×1.26×1.43×1.61×020406080100120startruin 50%bet #bankroll multiple
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

Probability stack · base rate vs crowd vs model
ANCHORED · supported by convictionanchor gap -42.7pp · crowd gap -43.0pp
0%20%40%60%80%100%Reference base rate50.1%Market price7.1%Model P(YES)7.4%
Anchor gapmodel − base
-42.7 pp
Crowd gapprice − base
-43.0 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.

§11 · Forecast quality (synthetic ledger)

Brier · Murphy decomposition · reliability · ROC
SKILL POSITIVE · in-sample BSS 21.9% · AUC 0.777out-of-sample BSS (5-fold) 21.9% ± 2.1% · Brier 0.1950 · log-loss 0.5859 · n 1600n = 1600
BrierBS
0.1950
lower = better · ō 0.52
BSSvs base
21.9%
improvement over base rate
ReliabilityREL
0.0048
miscalibration · want ↓
ResolutionRES
0.0590
decisiveness · want ↑
Log lossLL
0.5859
cross-entropy
AUCROC
0.777
0.5 coin · 1.0 oracle
0.00.20.40.60.81.00.00.20.40.60.81.0stated probability fobserved frequency ō0.00.20.40.60.81.00.00.20.40.60.81.0AUC = 0.777false positive ratetrue positive rate0.0000.0750.1500.2250.2990.250UNC0.059RES0.005REL0.195BRIERcontribution
calibration curveROCUNC (irreducible)RES (skill, ↑)REL (miscalib, ↓)
Computed on a seeded synthetic forecast ledger. Reseed (⟳) to redraw.

§12 · Journal vitals (synthetic ledger)

Track record · win rate · PF · expectancy · CLV · equity curve
PROFITABLE · PF 1.03 · expectancy +0.015R180 trades · win 53.9% · Sharpe 0.014
Total P/Lnet
+$658
on $45,000 cycled
Win ratehit %
53.9%
97 W / 83 L
Profit factorPF
1.03
$ won / $ lost
Expectancyper trade
+$3.66
avg $ per position
R-expectancyper risk
+0.015R
in units of risk taken
Avg win / losspayoff
$220.70 / -$250.00
ratio 0.88 : 1
Sharpe / traderisk-adj
0.014
μR / σR
Closing line valueCLV
+3.17 pp
avg edge vs close
-$1,659-$426$807$2,040$3,27303672108144180trade #cumulative P/L (USD)
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.

▸ Advanced metrics · M2M bundle

hyperliquid · pred-draw-295 · fresh · feed 3s old
24h sparkline · 60 pts
realized vol (ann.)
238.71%
max drawdown
28.07%
sharpe
ulcer index
1.95%
RMS drawdown
pain index
0.49%
mean drawdown
mod. VaR 95%
0.00%
Cornish-Fisher
martin ratio
ret / ulcer
CDaR 95%
4.82%
cond. drawdown
gain/pain
1.04
Σgain / Σ|loss|
sterling
ret / CDaR
omega (θ=0)
1.04
upside/downside
roll spread
209.3 bps
implied (price-only)
bars used
2000
store
spread
24h Δ
flow lean
carry
flat
signalNEUTRALconfidence 20%
Same bundle via M2M API: /api/m2m/hl-pred-draw-295/bundle · venue execution: hyperliquid