NOSTRADAMUS · Position Analytics Engine
SIMULATOR Will the Fed increase interest rates by 25 bps after the September 2026 meeting?
← 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-will-the-fed-increase-interest-rates-by-25-bps-after-the-september-2026-meeting-649 page.
▲ YES EDGE · +0.038 · f★ 6.3% · deploy 3.1% · net 3.06pp
§1 · Position economics
YES · Expected P/L per share +0.0381@ model P(YES) = 0.433
P/L per sharemarket pricemodel Pprofit zoneloss zone
Profit is linear in the eventual settlement price.
f★ = 6.29% · g(f★) = 0.300%deploy 3.14% · g = 0.226%
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 @ 0.395 · EV +$76stake $786 · 3.14% of bankroll
Deployed stakestake
$786
3.14% of bankroll
Sharesunits
1,990
each pays $1 if YES
Max payoutwin
$1,990
gross, if win
Max profitwin
+$1,204
net of cost
Max losslose
-$786
binary settles to $0
Payout multiple×
×2.53
$1 → $2.53
Risk:RewardR:R
1.53 : 1
win $1.53 per $1
Expected P/LE[P/L]
+$76
probability-weighted
| Outcome | P(model) | P/L | Contribution |
|---|---|---|---|
| Resolves YES (win) | 43.3% | +$1,204 | +$521 |
| Resolves against (lose) | 56.7% | -$786 | -$446 |
| Expected value | 100.0% | — | +$76 |
What you actually win and lose. The bottom table tabulates probability-weighted P/L by outcome.
§3 · Break-even & cushion
Cushion +3.8 pprelative edge +9.6%
Required win ratebreak-even
39.5%
price = implied probability
Model win rateP(win)
43.3%
what you forecast
Cushionedge
+3.8 pp
margin of safety
Fair pricemodel
0.433
where you think it should trade
The market price equals the win rate you must beat to make money.
§4 · Odds conversion
Implied probabilityP
39.5%
= price
Decimal oddsEU
2.532
total return per $1
AmericanUS
+153
$100 wins $153
FractionalUK
1.53 / 1
profit per $1 risked
Profit per $100stake
+$153.16
clean dollar framing
underdog (+)favorite (-)your price
Five views of the same number.
§4b · Time & annualized return
APR 167% · APY 395%ROI 9.6% over 21d · 17.4 turns/yr
Time to resolvehorizon
21.0 d
504h capital lockup
Raw ROIper resolve
+9.6%
APR (simple)scaled
+167%
ROI × 365/days
APY (compounded)if redeployed
+395%
(1+ROI)^(365/d) − 1
Daily expectedper day
+0.44%
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 +3.06 pperosion 20% · break-even w/ fees 40.3%
gross edgefrictionnet edgefee 0 bps · spread 1.50¢
The number that decides whether to trade.
§6 · Sizing menu
Full Kellyf★
$1,572
6.29% · g = 0.300%
Half Kelly½ f★
$786
3.14% · g = 0.226%
Quarter Kelly¼ f★
$393
1.57% · g = 0.132%
Flat 1%1%
$250
1.00% · g = 0.088%
Flat 2%2%
$500
2.00% · g = 0.161%
Flat 5%5%
$1,250
5.00% · g = 0.287%
Recommended¼ f★
$393
survives model error
Quarter-Kelly is the industry default — survives model error far better than full Kelly.
§7 · Information theory
Market entropyH(p)
0.968 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.987 bit
Δ +0.019 bit vs market
Surprise · YES−log₂ p
1.34 bit
self-information
Surprise · NO−log₂(1−p)
0.72 bit
self-information
H(p) peaks at p = 0.5 (one bit of irreducible doubt).
NOISE · D_KL(q ‖ p) = 0.0030 nat (0.0043 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 0.433 · CI [0.32, 0.55] · κ 67.2
Posterior meanE[θ]
0.433
Beta(29.1, 38.1)
95% credible intervalHDI
[0.32, 0.55]
price INSIDE → weak edge
Concentrationκ
67.2
pseudo-obs behind belief
Disagreementvs crowd
+3.8 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] +5.7% · P(YES) 41.8% · VaR₉₅ 100.0%400 paths · 504 bars to resolution
Expected P/Lper $1
+5.70%
P(YES) empiricalq
41.8%
Best pathmax
+153.2%
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 0.23% · ruin rate 3.8%400 paths × 120 bets · f deploy 3.14%
Sharpe / betμ/σ
0.074
μ 0.29% · σ 3.9%
Sortino / betμ/σ↓
0.092
downside-only denominator
VaR 95%5%
-3.1%
per-bet worst-case
CVaR 95%ES
-3.1%
mean tail loss
Max drawdownMDD
-7.8%
Calmar 0.03
Ruin rate≤50%
3.8%
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 -15.5pp · crowd gap -19.3pp
Anchor gapmodel − base
-15.5 pp
Crowd gapprice − base
-19.3 pp
Verdictdiscipline
ANCHORED
Reference-class anchoring prevents narrative-driven blowups.
§11 · Forecast quality (synthetic ledger)
SKILL POSITIVE · in-sample BSS 19.3% · AUC 0.762out-of-sample BSS (5-fold) 19.5% ± 2.9% · Brier 0.2017 · log-loss 0.5982 · n 1600✓ n = 1600
BrierBS
0.2017
lower = better · ō 0.49
BSSvs base
19.3%
improvement over base rate
ReliabilityREL
0.0045
miscalibration · want ↓
ResolutionRES
0.0526
decisiveness · want ↑
Log lossLL
0.5982
cross-entropy
AUCROC
0.762
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 1.16 · expectancy +0.072R180 trades · win 55.0% · Sharpe 0.067
Total P/Lnet
+$3,250
on $45,000 cycled
Win ratehit %
55.0%
99 W / 81 L
Profit factorPF
1.16
$ won / $ lost
Expectancyper trade
+$18.06
avg $ per position
R-expectancyper risk
+0.072R
in units of risk taken
Avg win / losspayoff
$237.37 / -$250.00
ratio 0.95 : 1
Sharpe / traderisk-adj
0.067
μR / σR
Closing line valueCLV
+3.75 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.