NOSTRADAMUS · Position Analytics Engine
SIMULATOR China x Taiwan military clash before 2027?
← Back to live dashboardEmbed cardOG previewTop moversArb
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-china-x-taiwan-military-clash-before-2027 page.
▲ YES EDGE · +0.009 · f★ 0.9% · deploy 0.5% · net 0.11pp
§1 · Position economics
YES · Expected P/L per share +0.0086@ model P(YES) = 0.099
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 0.94% · g(f★) = 0.044%deploy 0.47% · g = 0.033%
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 @ 0.090 · EV +$11stake $118 · 0.47% of bankroll
Deployed stakestake
$118
0.47% of bankroll
Sharesunits
1,310
each pays $1 if YES
Max payoutwin
$1,310
gross, if win
Max profitwin
+$1,192
net of cost
Max losslose
-$118
binary settles to $0
Payout multiple×
×11.11
$1 → $11.11
Risk:RewardR:R
10.11 : 1
win $10.11 per $1
Expected P/LE[P/L]
+$11
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 9.9% | +$1,192 | +$117 |
| Resolves against (lose) | 90.1% | -$118 | -$106 |
| Expected value | 100.0% | — | +$11 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +0.9 pprelative edge +9.5%
Required win ratebreak-even
9.0%
price = implied probability
Model win rateP(win)
9.9%
what you forecast
Cushionedge
+0.9 pp
margin of safety
Fair pricemodel
0.099
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
9.0%
= price
Decimal oddsEU
11.111
total return per $1
AmericanUS
+1011
$100 wins $1011
FractionalUK
10.11 / 1
profit per $1 risked
Profit per $100stake
+$1011.11
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 166% · APY 387%ROI 9.5% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+9.5%
APR (simple)scaled
+166%
ROI × 365/days
APY (compounded)if redeployed
+387%
(1+ROI)^(365/d) − 1
Daily expectedper day
+0.43%
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 +0.11 pperosion 87% · break-even w/ fees 9.8%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$236
0.94% · g = 0.044%
Half Kelly½ f★
$118
0.47% · g = 0.033%
Quarter Kelly¼ f★
$59
0.24% · g = 0.019%
Flat 1%1%
$250
1.00% · g = 0.044%
Flat 2%2%
$500
2.00% · g = -0.006%
Flat 5%5%
$1,250
5.00% · g = -0.590%
Recommended¼ f★
$59
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.436 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.464 bit
Δ +0.028 bit vs market
Surprise · YES−log₂ p
3.47 bit
self-information
Surprise · NO−log₂(1−p)
0.14 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0004 nat (0.0006 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 0.099 · CI [0.02, 0.24] · κ 23.7
Posterior meanE[θ]
0.099
Beta(2.3, 21.3)
95% credible intervalHDI
[0.02, 0.24]
price INSIDE → weak edge
Concentrationκ
23.7
pseudo-obs behind belief
Disagreementvs crowd
+0.9 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] -8.3% · P(YES) 8.3% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
-8.33%
P(YES) empiricalq
8.3%
Best pathmax
+1011.1%
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 0.04% · ruin rate 0.0%400 paths × 120 bets · f deploy 0.50%
Sharpe / betμ/σ
0.030
μ 0.05% · σ 1.7%
Sortino / betμ/σ↓
0.101
downside-only denominator
VaR 95%5%
-0.5%
per-bet worst-case
CVaR 95%ES
-0.5%
mean tail loss
Max drawdownMDD
-5.4%
Calmar 0.01
Ruin rate≤50%
0.0%
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 -46.4pp · crowd gap -47.3pp
Anchor gapmodel − base
-46.4 pp
Crowd gapprice − base
-47.3 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) 16.9% ± 2.4% · Brier 0.2078 · log-loss 0.6147 · n 1600✓ n = 1600
BrierBS
0.2078
lower = better · ō 0.51
BSSvs base
16.8%
improvement over base rate
ReliabilityREL
0.0062
miscalibration · want ↓
ResolutionRES
0.0474
decisiveness · want ↑
Log lossLL
0.6147
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 1.02 · expectancy +0.009R180 trades · win 53.3% · Sharpe 0.009
Total P/Lnet
+$408
on $45,000 cycled
Win ratehit %
53.3%
96 W / 84 L
Profit factorPF
1.02
$ won / $ lost
Expectancyper trade
+$2.26
avg $ per position
R-expectancyper risk
+0.009R
in units of risk taken
Avg win / losspayoff
$223.00 / -$250.00
ratio 0.89 : 1
Sharpe / traderisk-adj
0.009
μR / σR
Closing line valueCLV
+2.35 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.