KALSHI · CFTC-CLEARED BINARY CONTRACT · SCIENCE AND TECHNOLOGY

Best AI in Dec 2026?

YES · live

13.1¢

NO · live

86.9¢

▸ Advanced metrics · M2M bundle

kalshi · kxllm1-26dec31-goog · fresh · feed 1m old

24h sparkline · 60 pts▼ —

realized vol (ann.)

9.90%

max drawdown

1.50%

sharpe

—

ulcer index

0.68%

RMS drawdown

pain index

0.32%

mean drawdown

mod. VaR 95%

0.01%

Cornish-Fisher

martin ratio

—

ret / ulcer

CDaR 95%

1.50%

cond. drawdown

gain/pain

0.33

Σgain / Σ|loss|

sterling

—

ret / CDaR

omega (θ=0)

0.33

upside/downside

roll spread

1.0 bps

implied (price-only)

bars used

216

store

spread

76.0 bps

24h Δ

—

flow lean

—

carry

flat

signalNEUTRALconfidence 20%

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

LIVEPOLL0SRCWARMING1.1m⏱--:--:-- 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

13.1¢

NO · live

86.9¢

YES price · live 24h (Kalshi candlesticks)

no history

YES / NO split · live

Σ 99.95% · fair

Σ-sides total = 99.95% (tight rounding)

H(p) entropy = 0.560 / 1.00 bits (56%) · moderate uncertainty

YES

13.1%13.1¢7.63×▬ +0.00pp

86.9%86.9¢1.15×▬ +0.00pp

Σ 99.95% · arb gap 0.05pp

Live numerics · pulse on poll

LIVE NUMERICS9 metrics·POLL 0

⏱snapshot age

1.1m

·ticker

KXLLM1-26DEC31-GOOG

▲YES bid

13.10¢

▲YES ask

13.20¢

ΣΣ sides

99.95%

⚖arb gap

0.050pp

$24h vol $

$486.1

◐open interest $

$648.1k

◳history points

0 bars (live)

§1 · Quote

Ticker: KXLLM1-26DEC31-GOOG
Event ticker: KXLLM1-26DEC31
YES bid / ask: 13.10¢ / 13.20¢ (spread 0.10pp)
NO bid / ask: 86.80¢ / 86.90¢
Last YES: 13.10¢
Σ-sides: 99.95% (arb gap 0.05pp)

§2 · Activity

Volume 24h: $486.08
Volume total: $132.34k
Open interest: $648.11k
Liquidity: $0.00
Close time: 2026-12-31T15:00:00Z · 194.1d 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 (599 bars · effective 347249 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 194.1 d · σ/bar 0.491pp · expected |Δp| over horizon 33.53ppterminal variance p(1−p) = 0.1138 · n = 599✓ n = 599

μ per bar

-0.004pp

average Δp · drift

σ per bar

0.491pp

one-bar volatility · logit-free

Per-day movedaily

2.41pp

σ × √24

Per-horizon move194d

33.53pp

σ × √4658.202764722222

Terminal variancebinary

0.1138

p(1−p) at resolution

Current pricep

13.1¢

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 0.81pp · ES₉₅ 1.02pp · method parametric · drift-correcteddrift -0.004pp/bar · quantised: yes · median step 0.10pp · unique ratio 0.08✓ n = 599

VaR 95%

0.81pp

1.645·σ (parametric) of Δp

ES 95%

1.02pp

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

13.1%

= price

Decimal oddsEU

7.634

total return per $1

AmericanUS

+663

$100 wins $663

FractionalUK

6.63 / 1

profit per $1 risked

Profit per $100stake

+$663.36

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)

0.560 bit

max 1.0 at p = 0.5

Your entropyH(q)

0.560 bit

Δ +0.000 bit vs market

Surprise · YES−log₂ p

2.93 bit

self-information

Surprise · NO−log₂(1−p)

0.20 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 12:46:42 UTC
Snapshot age: 1.1m
SHA-256 attestation: 9eaaecbc141e29b04b8c48055e0e66714c3ff63e88e0f4133b1fddca246c9882 · 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 · 599 barsperiods/year ≈ 347.2K

Realized vol (annualised)

2043.03%

σ per bar = 0.034670

Mean return (annualised)

-9392.86%

μ per bar = -0.000270

Sharpe (rf=0)

-4.60

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