NOSTRADAMUS · Position Analytics Engine
SIMULATOR Austria
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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-austria-175 page.
▲ YES EDGE · +0.033 · f★ 3.3% · deploy 1.7% · net 2.57pp
§1 · Position economics
YES · Expected P/L per share +0.0332@ model P(YES) = 0.036
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 3.33% · g(f★) = 5.539%deploy 1.66% · g = 4.970%
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 @ 0.003 · EV +$4,243stake $416 · 1.66% of bankroll
Deployed stakestake
$416
1.66% of bankroll
Sharesunits
127,853
each pays $1 if YES
Max payoutwin
$127,853
gross, if win
Max profitwin
+$127,437
net of cost
Max losslose
-$416
binary settles to $0
Payout multiple×
×307.22
$1 → $307.22
Risk:RewardR:R
306.22 : 1
win $306.22 per $1
Expected P/LE[P/L]
+$4,243
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 3.6% | +$127,437 | +$4,644 |
| Resolves against (lose) | 96.4% | -$416 | -$401 |
| Expected value | 100.0% | — | +$4,243 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +3.3 pprelative edge +1019.5%
Required win ratebreak-even
0.3%
price = implied probability
Model win rateP(win)
3.6%
what you forecast
Cushionedge
+3.3 pp
margin of safety
Fair pricemodel
0.036
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
0.3%
= price
Decimal oddsEU
307.220
total return per $1
AmericanUS
+30622
$100 wins $30622
FractionalUK
306.22 / 1
profit per $1 risked
Profit per $100stake
+$30621.97
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 17720% · APY 170995857126981074944%ROI 1019.5% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+1019.5%
APR (simple)scaled
+17720%
ROI × 365/days
APY (compounded)if redeployed
+170995857126981074944%
(1+ROI)^(365/d) − 1
Daily expectedper day
+12.19%
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 +2.57 pperosion 23% · break-even w/ fees 1.1%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$832
3.33% · g = 5.539%
Half Kelly½ f★
$416
1.66% · g = 4.970%
Quarter Kelly¼ f★
$208
0.83% · g = 3.810%
Flat 1%1%
$250
1.00% · g = 4.139%
Flat 2%2%
$500
2.00% · g = 5.208%
Flat 5%5%
$1,250
5.00% · g = 5.231%
Recommended¼ f★
$208
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.032 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.226 bit
Δ +0.194 bit vs market
Surprise · YES−log₂ p
8.26 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) = 0.0554 nat (0.0799 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 0.036 · CI [0.00, 0.23] · κ 8.8
Posterior meanE[θ]
0.036
Beta(0.3, 8.4)
95% credible intervalHDI
[0.00, 0.23]
price INSIDE → weak edge
Concentrationκ
8.8
pseudo-obs behind belief
Disagreementvs crowd
+1.6 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] +1128.9% · P(YES) 4.0% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+1128.88%
P(YES) empiricalq
4.0%
Best pathmax
+30622.0%
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 7.73% · ruin rate 9.0%400 paths × 120 bets · f deploy 1.66%
Sharpe / betμ/σ
0.216
μ 24.24% · σ 112.1%
Sortino / betμ/σ↓
14.559
downside-only denominator
VaR 95%5%
-1.7%
per-bet worst-case
CVaR 95%ES
-1.7%
mean tail loss
Max drawdownMDD
-28.5%
Calmar 0.27
Ruin rate≤50%
9.0%
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 -54.7pp · crowd gap -58.0pp
Anchor gapmodel − base
-54.7 pp
Crowd gapprice − base
-58.0 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 20.9% · AUC 0.772out-of-sample BSS (5-fold) 21.0% ± 1.9% · Brier 0.1977 · log-loss 0.5899 · n 1600✓ n = 1600
BrierBS
0.1977
lower = better · ō 0.49
BSSvs base
20.9%
improvement over base rate
ReliabilityREL
0.0041
miscalibration · want ↓
ResolutionRES
0.0559
decisiveness · want ↑
Log lossLL
0.5899
cross-entropy
AUCROC
0.772
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 0.92 · expectancy -0.041R180 trades · win 48.3% · Sharpe -0.037
Total P/Lnet
-$1,843
on $45,000 cycled
Win ratehit %
48.3%
87 W / 93 L
Profit factorPF
0.92
$ won / $ lost
Expectancyper trade
-$10.24
avg $ per position
R-expectancyper risk
-0.041R
in units of risk taken
Avg win / losspayoff
$246.06 / -$250.00
ratio 0.98 : 1
Sharpe / traderisk-adj
-0.037
μR / σR
Closing line valueCLV
+1.86 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.