NOSTRADAMUS · Position Analytics Engine
SIMULATOR Australia
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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/hl-pred-australia-174 page.
▲ YES EDGE · +0.018 · f★ 1.8% · deploy 0.9% · net 1.00pp
§1 · Position economics
YES · Expected P/L per share +0.0175@ model P(YES) = 0.020
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 1.76% · g(f★) = 2.460%deploy 0.88% · g = 2.178%
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 @ 0.002 · EV +$1,575stake $220 · 0.88% of bankroll
Deployed stakestake
$220
0.88% of bankroll
Sharesunits
89,761
each pays $1 if YES
Max payoutwin
$89,761
gross, if win
Max profitwin
+$89,541
net of cost
Max losslose
-$220
binary settles to $0
Payout multiple×
×408.16
$1 → $408.16
Risk:RewardR:R
407.16 : 1
win $407.16 per $1
Expected P/LE[P/L]
+$1,575
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 2.0% | +$89,541 | +$1,791 |
| Resolves against (lose) | 98.0% | -$220 | -$216 |
| Expected value | 100.0% | — | +$1,575 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +1.8 pprelative edge +716.3%
Required win ratebreak-even
0.2%
price = implied probability
Model win rateP(win)
2.0%
what you forecast
Cushionedge
+1.8 pp
margin of safety
Fair pricemodel
0.020
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
0.2%
= price
Decimal oddsEU
408.163
total return per $1
AmericanUS
+40716
$100 wins $40716
FractionalUK
407.16 / 1
profit per $1 risked
Profit per $100stake
+$40716.33
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 12450% · APY 706420380323365760%ROI 716.3% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+716.3%
APR (simple)scaled
+12450%
ROI × 365/days
APY (compounded)if redeployed
+706420380323365760%
(1+ROI)^(365/d) − 1
Daily expectedper day
+10.52%
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 +1.00 pperosion 43% · break-even w/ fees 1.0%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$440
1.76% · g = 2.460%
Half Kelly½ f★
$220
0.88% · g = 2.178%
Quarter Kelly¼ f★
$110
0.44% · g = 1.621%
Flat 1%1%
$250
1.00% · g = 2.262%
Flat 2%2%
$500
2.00% · g = 2.446%
Flat 5%5%
$1,250
5.00% · g = 1.096%
Recommended¼ f★
$110
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.025 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.141 bit
Δ +0.117 bit vs market
Surprise · YES−log₂ p
8.67 bit
self-information
Surprise · NO−log₂(1−p)
0.00 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
SIGNAL · D_KL(q ‖ p) = 0.0246 nat (0.0355 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 0.020 · CI [0.00, 0.30] · κ 4.4
Posterior meanE[θ]
0.020
Beta(0.1, 4.4)
95% credible intervalHDI
[0.00, 0.30]
price INSIDE → weak edge
Concentrationκ
4.4
pseudo-obs behind belief
Disagreementvs crowd
+0.0 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] +614.3% · P(YES) 1.8% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+614.29%
P(YES) empiricalq
1.8%
Best pathmax
+40716.3%
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 5.65% · ruin rate 8.5%400 paths × 120 bets · f deploy 0.88%
Sharpe / betμ/σ
0.190
μ 13.28% · σ 69.9%
Sortino / betμ/σ↓
15.097
downside-only denominator
VaR 95%5%
-0.9%
per-bet worst-case
CVaR 95%ES
-0.9%
mean tail loss
Max drawdownMDD
-22.6%
Calmar 0.25
Ruin rate≤50%
8.5%
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 -38.1pp · crowd gap -39.9pp
Anchor gapmodel − base
-38.1 pp
Crowd gapprice − base
-39.9 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 16.7% · AUC 0.749out-of-sample BSS (5-fold) 16.9% ± 0.7% · Brier 0.2084 · log-loss 0.6229 · n 1600✓ n = 1600
BrierBS
0.2084
lower = better · ō 0.50
BSSvs base
16.7%
improvement over base rate
ReliabilityREL
0.0061
miscalibration · want ↓
ResolutionRES
0.0475
decisiveness · want ↑
Log lossLL
0.6229
cross-entropy
AUCROC
0.749
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 1.08 · expectancy +0.042R180 trades · win 49.4% · Sharpe 0.029
Total P/Lnet
+$1,905
on $45,000 cycled
Win ratehit %
49.4%
89 W / 91 L
Profit factorPF
1.08
$ won / $ lost
Expectancyper trade
+$10.58
avg $ per position
R-expectancyper risk
+0.042R
in units of risk taken
Avg win / losspayoff
$277.02 / -$250.00
ratio 1.11 : 1
Sharpe / traderisk-adj
0.029
μR / σR
Closing line valueCLV
+2.43 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.