NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will Crude Oil (CL) hit (HIGH) $150 by end of June?
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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-crude-oil-cl-hit-high-150-by-end-of-june-788-691 page.
▲ YES EDGE · +0.026 · f★ 2.7% · deploy 1.3% · net 1.90pp
§1 · Position economics
YES · Expected P/L per share +0.0265@ model P(YES) = 0.037
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 2.67% · g(f★) = 1.979%deploy 1.34% · g = 1.661%
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 @ 0.011 · EV +$804stake $334 · 1.34% of bankroll
Deployed stakestake
$334
1.34% of bankroll
Sharesunits
30,395
each pays $1 if YES
Max payoutwin
$30,395
gross, if win
Max profitwin
+$30,061
net of cost
Max losslose
-$334
binary settles to $0
Payout multiple×
×90.91
$1 → $90.91
Risk:RewardR:R
89.91 : 1
win $89.91 per $1
Expected P/LE[P/L]
+$804
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 3.7% | +$30,061 | +$1,126 |
| Resolves against (lose) | 96.3% | -$334 | -$322 |
| Expected value | 100.0% | — | +$804 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +2.6 pprelative edge +240.5%
Required win ratebreak-even
1.1%
price = implied probability
Model win rateP(win)
3.7%
what you forecast
Cushionedge
+2.6 pp
margin of safety
Fair pricemodel
0.037
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
1.1%
= price
Decimal oddsEU
90.909
total return per $1
AmericanUS
+8991
$100 wins $8991
FractionalUK
89.91 / 1
profit per $1 risked
Profit per $100stake
+$8990.91
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 4180% · APY 177159092294%ROI 240.5% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+240.5%
APR (simple)scaled
+4180%
ROI × 365/days
APY (compounded)if redeployed
+177159092294%
(1+ROI)^(365/d) − 1
Daily expectedper day
+6.01%
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 +1.90 pperosion 28% · break-even w/ fees 1.8%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$669
2.67% · g = 1.979%
Half Kelly½ f★
$334
1.34% · g = 1.661%
Quarter Kelly¼ f★
$167
0.67% · g = 1.117%
Flat 1%1%
$250
1.00% · g = 1.435%
Flat 2%2%
$500
2.00% · g = 1.909%
Flat 5%5%
$1,250
5.00% · g = 1.445%
Recommended¼ f★
$167
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.087 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.230 bit
Δ +0.143 bit vs market
Surprise · YES−log₂ p
6.51 bit
self-information
Surprise · NO−log₂(1−p)
0.02 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0198 nat (0.0286 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 0.037 · CI [0.00, 0.22] · κ 9.0
Posterior meanE[θ]
0.037
Beta(0.3, 8.7)
95% credible intervalHDI
[0.00, 0.22]
price INSIDE → weak edge
Concentrationκ
9.0
pseudo-obs behind belief
Disagreementvs crowd
+1.7 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] +309.1% · P(YES) 4.5% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+309.09%
P(YES) empiricalq
4.5%
Best pathmax
+8990.9%
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 2.02% · ruin rate 7.0%400 paths × 120 bets · f deploy 1.34%
Sharpe / betμ/σ
0.176
μ 4.63% · σ 26.3%
Sortino / betμ/σ↓
3.464
downside-only denominator
VaR 95%5%
-1.3%
per-bet worst-case
CVaR 95%ES
-1.3%
mean tail loss
Max drawdownMDD
-28.6%
Calmar 0.07
Ruin rate≤50%
7.0%
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 -36.8pp · crowd gap -39.4pp
Anchor gapmodel − base
-36.8 pp
Crowd gapprice − base
-39.4 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 16.3% · AUC 0.748out-of-sample BSS (5-fold) 16.3% ± 1.4% · Brier 0.2093 · log-loss 0.6274 · n 1600✓ n = 1600
BrierBS
0.2093
lower = better · ō 0.49
BSSvs base
16.3%
improvement over base rate
ReliabilityREL
0.0066
miscalibration · want ↓
ResolutionRES
0.0475
decisiveness · want ↑
Log lossLL
0.6274
cross-entropy
AUCROC
0.748
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 53.9% · Sharpe 0.056
Total P/Lnet
+$2,785
on $45,000 cycled
Win ratehit %
53.9%
97 W / 83 L
Profit factorPF
1.13
$ won / $ lost
Expectancyper trade
+$15.47
avg $ per position
R-expectancyper risk
+0.062R
in units of risk taken
Avg win / losspayoff
$242.63 / -$250.00
ratio 0.97 : 1
Sharpe / traderisk-adj
0.056
μR / σR
Closing line valueCLV
+3.11 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.