KALSHI · CFTC-CLEARED BINARY CONTRACT · SCIENCE AND TECHNOLOGY

Best AI in Dec 2026?

YES · live

13.3¢

NO · live

86.8¢

▸ Advanced metrics · M2M bundle

kalshi · kxllm1-26dec31-goog · fresh · feed 43s old

24h sparkline · 38 pts▼ —

realized vol (ann.)

0.00%

max drawdown

0.00%

sharpe

—

ulcer index

0.00%

RMS drawdown

pain index

0.00%

mean drawdown

mod. VaR 95%

0.00%

Cornish-Fisher

martin ratio

—

ret / ulcer

CDaR 95%

0.00%

cond. drawdown

gain/pain

—

Σgain / Σ|loss|

sterling

—

ret / CDaR

omega (θ=0)

1.00

upside/downside

roll spread

0.0 bps

implied (price-only)

bars used

store

spread

151.5 bps

24h Δ

—

flow lean

—

carry

flat

signalNEUTRALconfidence 20%

Same bundle via M2M API: /api/m2m/kalshi-kxllm1-26dec31-goog/bundle · venue execution: kalshi →

LIVEPOLL0SRCWARMING43.4s⏱--:--:-- UTCNEXT8.0sUP0s--:--HIST0/30

▶ STREAMING·HYPERLIQUID·POLYMARKET·0 POLLS·SRC WARMING·UPTIME 0s·NEXT POLL 8.0s·CC0 OPEN DATA·HYPO.MARKETS·▶ STREAMING·HYPERLIQUID·POLYMARKET·0 POLLS·SRC WARMING·UPTIME 0s·NEXT POLL 8.0s·CC0 OPEN DATA·HYPO.MARKETS·

YES · live

13.3¢

NO · live

86.8¢

YES price · live 24h (Kalshi candlesticks)

no history

YES / NO split · live

Σ 100.10% · fair

Σ-sides total = 100.10% (tight rounding)

H(p) entropy = 0.565 / 1.00 bits (57%) · moderate uncertainty

YES

13.3%13.3¢7.52×▬ +0.00pp

86.7%86.8¢1.15×▬ +0.00pp

Σ 100.10% · arb gap 0.10pp

Live numerics · pulse on poll

LIVE NUMERICS9 metrics·POLL 0

⏱snapshot age

43.4s

·ticker

KXLLM1-26DEC31-GOOG

▲YES bid

13.10¢

▲YES ask

13.30¢

ΣΣ sides

100.10%

⚖arb gap

0.100pp

$24h vol $

$492.5

◐open interest $

$647.6k

◳history points

0 bars (live)

§1 · Quote

Ticker: KXLLM1-26DEC31-GOOG
Event ticker: KXLLM1-26DEC31
YES bid / ask: 13.10¢ / 13.30¢ (spread 0.20pp)
NO bid / ask: 86.70¢ / 86.90¢
Last YES: 13.30¢
Σ-sides: 100.10% (arb gap 0.10pp)

§2 · Activity

Volume 24h: $492.52
Volume total: $134.29k
Open interest: $647.59k
Liquidity: $0.00
Close time: 2026-12-31T15:00:00Z · 194.3d from now
Status: active

§3 · Resolution rules

If Google has the top-ranked LLM on Dec 31, 2026, then the market resolves to Yes.

▸ Depth section using sovereign-store price series (421 bars · effective 344091 bars/year) — annualisation reflects native polling cadence, not upstream timeframes.

§4 · Honest position analytics

A binary-market analytics module framed in horizon time (days to resolution, not annualised). Estimators that need a model probability q as a first-class input (Kelly, KL divergence, Bayesian posterior, Mark-to-Market MC) only render when q is provided externally. Sweep an exploratory q at the interactive simulator →

§5 · Horizon returns

Returns · per bar / per day / per horizon

Horizon 194.3 d · σ/bar 0.586pp · expected |Δp| over horizon 40.04ppterminal variance p(1−p) = 0.1153 · n = 421✓ n = 421

μ per bar

-0.005pp

average Δp · drift

σ per bar

0.586pp

one-bar volatility · logit-free

Per-day movedaily

2.87pp

σ × √24

Per-horizon move194d

40.04pp

σ × √4663.124658611111

Terminal variancebinary

0.1153

p(1−p) at resolution

Current pricep

13.3¢

latest snapshot

Note: annualised Sharpe/Sortino are omitted — they are not meaningful for a bounded fixed-horizon binary contract that snaps to {0, 1} at resolution.

Annualised metrics are intentionally omitted — they don't apply to bounded probability series that resolve at a fixed date.

§6 · Tail risk

VaR · ES · max drawdown

VaR₉₅ 0.97pp · ES₉₅ 1.21pp · method parametric · drift-correcteddrift -0.005pp/bar · quantised: yes · median step 0.10pp · unique ratio 0.11✓ n = 421

VaR 95%

0.97pp

1.645·σ (parametric) of Δp

ES 95%

1.21pp

mean of the tail

Max drawdown

35.6pp

peak 17.4¢ → trough 11.2¢

Median step

0.10pp

price bucket granularity

Price series is bucketed (cent grid). Empirical quantiles collapse to grid points — parametric N(0, σ²) used instead.

Empirical quantiles unless the price series is bucketed (PM cent grid), in which case parametric N(0, σ²) is used to avoid grid collapse.

§7 · Odds conversion

Odds conversion · every dialect a bettor thinks in

Implied probabilityP

13.3%

= price

Decimal oddsEU

7.519

total return per $1

AmericanUS

+652

$100 wins $652

FractionalUK

6.52 / 1

profit per $1 risked

Profit per $100stake

+$651.88

clean dollar framing

underdog (+)favorite (-)your price

Price → implied probability → decimal odds → American moneyline → fractional. Five views of the same number, plus the moneyline curve.

§8 · Binary entropy

Binary entropy · uncertainty as bits of information

Market entropyH(p)

0.566 bit

max 1.0 at p = 0.5

Your entropyH(q)

0.566 bit

Δ +0.000 bit vs market

Surprise · YES−log₂ p

2.91 bit

self-information

Surprise · NO−log₂(1−p)

0.21 bit

self-information

Market entropy only — model entropy requires an external q.

§9 · Model-dependent surfaces

§ Edge / Kelly / KL · no model probability provided

External model required

The position-economics, Kelly, KL-divergence, Bayesian and Monte-Carlo surfaces require a model probability q as input — a number independent of the market price p.

The previous build defaulted q to a tape-momentum heuristic derived from p; that produces apparent edge that is structurally guaranteed to be small and is not a useful skill signal. The auto-derived path has been removed.

To explore these surfaces with a hypothetical q, open the interactive simulator and drag the MODEL P(YES) slider. To wire a real model, POST to the NOSTRADAMUS hook (TBD) or pass ?q=… on the simulator URL.

§∞ · Provenance & attestation

Upstream: api.elections.kalshi.com
Snapshot fetched: 2026-06-20 07:51:47 UTC
Snapshot age: 43.4s
SHA-256 attestation: 664834cd6821c73f66104edae7e6e40add63ab0b82af474f153f52c24483c697 · deterministic hash of the source snapshot — proves this page was rendered from this exact data
Open data licence: CC0 / public domain · free to mirror, syndicate, analyse

Risk metrics

▸ sovereign store · 421 barsperiods/year ≈ 344.1K

Realized vol (annualised)

2426.97%

σ per bar = 0.041374

Mean return (annualised)

-12010.69%

μ per bar = -0.000349

Sharpe (rf=0)

-4.95

annualised; risk-free assumed zero

Max drawdown

35.63%

peak 0.17 → trough 0.11 over 30 bars

/api/asset/kalshi-kxllm1-26dec31-goog/risk · same metrics, JSON