POLYMARKET · PREDICTION MARKET · TECH & BUSINESS

Will OpenAI have the best AI model at the end of June 2026?

YES · live
2.4¢
NO · live
97.7¢

▸ Advanced metrics · M2M bundle

polymarket · will-openai-have-the-best-ai-model-at-the-end-of-june-2026 · fresh · feed 1s old
24h sparkline · 60 pts▼ —
realized vol (ann.)
29.24%
max drawdown
28.79%
sharpe
—
ulcer index
16.41%
RMS drawdown
pain index
13.32%
mean drawdown
mod. VaR 95%
0.00%
Cornish-Fisher
martin ratio
—
ret / ulcer
CDaR 95%
28.01%
cond. drawdown
gain/pain
0.80
Σgain / Σ|loss|
sterling
—
ret / CDaR
omega (θ=0)
0.80
upside/downside
roll spread
1.4 bps
implied (price-only)
bars used
2000
store
spread
—
24h Δ
—
flow lean
—
carry
flat
signalNEUTRALconfidence 20%
Same bundle via M2M API: /api/m2m/pm-will-openai-have-the-best-ai-model-at-the-end-of-june-2026/bundle · venue execution: polymarket →
LIVEPOLL0SRCFRESH1.3s⏱--:--:-- UTC8NEXT8.0sUP0s--:--HIST0/30
▶ STREAMING·HYPERLIQUID·POLYMARKET·0 POLLS·SRC FRESH·UPTIME 0s·NEXT POLL 8.0s·CC0 OPEN DATA·HYPO.MARKETS·▶ STREAMING·HYPERLIQUID·POLYMARKET·0 POLLS·SRC FRESH·UPTIME 0s·NEXT POLL 8.0s·CC0 OPEN DATA·HYPO.MARKETS·
YES · live
2.4¢
NO · live
97.7¢
YES price · live 24h
n=25 · μ=0.0296 · σ=0.0040 · range [0.0235, 0.0365] · R²=0.607▼ FALLING -32.86%σ HIGH 13.61%LAST 0.02350.03650.03330.03000.02670.0235μ = 0.0296max 0.0365min 0.0235dataMA(5)OLS R²=0.61μ lineμ ± σ bandmaxminlive endpoint
25 ticks · last 2.35¢
YES / NO split · live
YES 2.4%NO 97.7%NO97.7%97.65¢ · odds 1/1.02
Σ 100.00% · fair
Σ-sides total = 100.00% (tight rounding)
H(p) entropy = 0.161 / 1.00 bits (16%) · informative — one side favoured
YES
2.4%2.4¢42.55×▬ +0.00pp
NO
97.7%97.7¢1.02×▬ +0.00pp
Σ 100.00% · arb gap 0.00pp
Per-tick activity · |Δp| in basis points · live
n=24 · Σ=465 · μ=19.4 · σ=19.8 · CV=1.02BURSTYcumulative energy ↗ · 50% by h=15017355270μ = 197050%h1h5h9h13h17h21#1 peak#2-3> μactivequietμ linecum energy
Σ 465bp moved · peak 70bp · n=24 ticks
Live numerics · pulse on poll
LIVE NUMERICS8 metrics·POLL 0
⏱snapshot age
1.3s
▲YES mid
2.35¢ (2.35%)
▼NO mid
97.65¢ (97.65%)
ΣΣ sides
100.00%
⚖arb gap
0.000pp
$24h vol $
$35.7k
≋liquidity $
$106.4k
◳history points
25 ticks (live)

§1 · 24h price history (YES + NO tokens)

YES price · CLOB mid
n=25 · μ=0.0296 · σ=0.0040 · range [0.0235, 0.0365] · R²=0.607▼ FALLING -32.86%σ HIGH 13.61%LAST 0.02350.03650.03330.03000.02670.0235μ = 0.0296max 0.0365min 0.0235dataMA(5)OLS R²=0.61μ lineμ ± σ bandmaxmin
25 YES observations from clob.polymarket.com · last 2.35¢
NO price · CLOB mid
n=25 · μ=0.9704 · σ=0.0040 · range [0.9635, 0.9765] · R²=0.607▲ RISING +1.19%σ LOW 0.41%LAST 0.97650.97650.97330.97000.96670.9635μ = 0.9704max 0.9765min 0.9635dataMA(5)OLS R²=0.61μ lineμ ± σ bandmaxmin
25 NO observations from clob.polymarket.com · last 97.65¢

§2 · Distribution of Δp

Histogram of hourly increments
n=24 · 10 bins · μ=-0.0006 · σ=0.0026 · skew=0.24 (symmetric) · kurt=0.66 (mesokurtic)754201-0.63ppbin -0.63pp · n=1 · 14.3% peakbin -0.63pp · n=1 · 14.3% peak1-0.50ppbin -0.50pp · n=1 · 14.3% peakbin -0.50pp · n=1 · 14.3% peak1-0.37ppbin -0.37pp · n=1 · 14.3% peakbin -0.37pp · n=1 · 14.3% peak3-0.24ppbin -0.24pp · n=3 · 42.9% peakbin -0.24pp · n=3 · 42.9% peak7-0.11ppbin -0.11pp · n=7 · 100.0% peakbin -0.11pp · n=7 · 100.0% peak50.02ppbin 0.02pp · n=5 · 71.4% peakbin 0.02pp · n=5 · 71.4% peak40.15ppbin 0.15pp · n=4 · 57.1% peakbin 0.15pp · n=4 · 57.1% peak0.28pp0.41pp20.54ppbin 0.54pp · n=2 · 28.6% peakbin 0.54pp · n=2 · 28.6% peakμΔ < 0 · loss barsΔ ≈ 0 · flatΔ > 0 · gain barsN(μ,σ²) referenceμ line · ±σ band shaded
n=24
Q-Q plot · standardised Δp vs N(0,1)
n=24 · skew=0.24 · kurt=1.16 · near 17 / mid 7 / far 0 · OLS slope=0.99 intercept=-0.00APPROXIMATELY NORMALUPPER TAIL NORMALLOWER TAIL NORMAL-3σ-3σ-2σ-2σ-1σ-1σ+0σ+0σ+1σ+1σ+2σ+2σ+3σ+3σsample ↓marginal: sample bars + theoretical N(0,1) curve →theoretical Φ⁻¹(p) →↑ sample z-quantile|Δ| < 0.3σ · on the line|Δ| < 1σ · moderate|Δ| ≥ 1σ · outliery = x refOLS fit
reference line = identity (perfect normality). Heavy upper-right tail = fat positive tail.

§3 · Sample moments

Descriptive statistics · 5-number summary · shape diagnostics
SAMPLE MOMENTS · N=25PLATYKURTIC · THIN TAILS (G₂=-1.05)
μ MEAN2.96¢95% CI: [2.80¢, 3.11¢]
σ STD DEV0.40ppσ² = 0.162 · CV = 13.61%
med MEDIAN2.90¢Q₁ 2.75¢ · Q₃ 3.25¢
FIVE-NUMBER SUMMARY · BOX PLOTrange 1.30pp · IQR 0.50pp (1.349σ→0.54pp)
min 2.35¢Q₁ 2.75¢med 2.90¢Q₃ 3.25¢max 3.65¢μ
SKEWNESS · G₁0.257approximately symmetric
−3−10+1+3
EXCESS KURTOSIS · G₂-1.052platykurtic · thin tails
−30+2+4+6
μ ↔ medianμ > med · right-tailed|μ−med| / σ = 0.14
σ × 1.349 ↔ IQRconsistent with normalratio = 1.09
range ↔ σconcentrated (range < 4σ)range / σ = 3.23
μ = mean YES probability · σ = standard deviation · 95% CI = μ ± 1.96·SE. Skew/kurt diagnose departure from normality.

§5 · Time-series structure

Regime & autocorrelation diagnostics
TIME-SERIES STRUCTUREREGIME: MEAN-REVERTING · ρ(1) -0.26 + ADF rejected
ρ(1) AUTOCORR-0.263within white-noise band
ρ(2) AUTOCORR-0.302lag-2 not significant
H · HURST EXPONENT1.021strongly persistent
OLS TREND · t-STAT-5.966significant @ α=0.05
HURST EXPONENT [0, 1]strongly persistent · H = 1.021
H = 1.021STRONGLY PERSISTENT
0
anti-persistent0.45
mean-reverting0.5
random walk0.55
persistent1
strongly trending
AUTOCORRELATION FUNCTION · ρ(k) for k=1..5WHITE NOISE · no significant lags
k=1-0.263k=2-0.302k=3+0.256k=4+0.013k=5-0.1010+1−1+0.41−0.41+ momentum (ρ > +0.41)− reversal (ρ < −0.41)noise (within band)±2/√n threshold
OLS TREND · t-STAT · [-5, +5]SIGNIFICANT @ 1% (|t|=5.97)
−5 reject−1.960 retain H₀+1.96+5 reject
REGIME CLASSIFICATIONMEAN-REVERTING · ρ(1) -0.26 + ADF rejectedfrom Hurst + ρ(1) joint diagnosis
PREDICTABILITY · score 1.00very high · strong structure|ρ(1)| + 2·|H − 0.5| heuristic
TREND SIGNIFICANCESIGNIFICANT @ 1% (|t|=5.97)α=0.05 critical |t|=1.96 · α=0.01 |t|=2.58
ρ(k) = lag-k sample autocorrelation · H = R/S Hurst exponent · t = OLS-trend t-statistic. Significance bands at ±2/√n approximate the 95% white-noise envelope. α=0.05 critical |t|=1.96; α=0.01 |t|=2.58.

§6 · Microstructure

Market quality · two-sided pricing · activity
MICROSTRUCTURE · MARKET QUALITYPERFECT · ARB-FREE Σ=100.00%
MARKET ID631141
SLUGwill-openai-have…of-june-2026
CATEGORYTech & Business
TWO-SIDED PRICINGFAVOURS NO (98¢)
PRIMARY · YES2.35¢implied prob 2.35% · decimal odds 42.55×
COUNTER · NO97.65¢implied prob 97.65% · decimal odds 1.02×
2.35¢
97.65¢
Σ-SIDES ARBITRAGE TESTPERFECT · ARB-FREE Σ=100.00%
0%50%100% · target110%
Σ = 100.00% · |1 − Σ| = 0.000pp
24H ACTIVITY · LIQUIDITYACTIVE
24H VOLUME35.69k USD 24h
LIQUIDITY106.43k USD
MARKET QUALITYPERFECT · ARB-FREE Σ=100.00%|1−Σ| ≤ 0.5pp ⇒ fair · > 2pp ⇒ inefficient
PRICING SKEWFAVOURS NO (98¢)|primary − counter| = 0.953 · entropy 0.161 bits
LIQUIDITY DEPTHACTIVE100k+ deep · 10k+ active · 1k+ modest · 100+ thin
Σ-sides = YES + NO implied probabilities. Perfect arb-free Σ = 100%. |1−Σ| > 2pp suggests synthetic outright arbitrage.

§7 · Position sizing & edge analysis

Probability split · YES vs NO · Kelly · entropy · arbitrage
FAIR MARKET · no edge
YES 2.4%NO 97.7%YES p̂2.4%H = 0.161 / 1.00 bits
Probability scale (YES)
0%25%50%
fair75%100%
Implied decimal odds
YES42.55×(2¢)NO1.02×(98¢)
Kelly bet-size (% of bankroll) K* = 0.00%
K* full
0.00%
½K half
0.00%
¼K quarter
0.00%
Entropy H(p̂) = 0.161 bits (16% of max) · informative — one side strongly favoured
0 (certain)0.250.50.751.00 (max)
Σ-sides = 100.00% · |1 − Σ| = 0.00pp · tight cross-venue rounding
K* full = (b·p − q)/b · ½K and ¼K are conservative fractions of the full-Kelly bet. Entropy in bits — log₂(2)=1 is maximum uncertainty for a binary market.

§8 · Time decay & θ projection

Time decay & theta projection
⏱ URGENCY · DISTANTresolves 2026-06-30 00:00 UTC
15days
12hrs
50min
15.54 days·θ = 1.971 pp/day
YES →$1.00(P = 2.4%)
NO →$0.00(P = 97.7%)
current: $0.0235 · expected return per side: $0.98 on YES hit · $0.02 on NO hit
0%25%50%75%100%YES $1NO $0NOW+7.8dRESOLVESP projection · σ=0.40% · path funnel to settle at YES=1 or NO=0
Theta progression · θ ∝ σ / √t_remainingθ_now = 1.971 pp/day
now15.54d left
1.971 pp/day×1.00
−25%11.65d left
2.276 pp/day×1.15
−50%7.77d left
2.788 pp/day×1.41
−75%3.88d left
3.943 pp/day×2.00
−90%1.55d left
6.234 pp/day×3.16
θ approximation: σ/√T (expected daily move magnitude). The cone shows ±√(p̂(1−p̂)) widening as time decays, funneling to {0, 1} at resolution. Theta accelerates as √(t_left)→0.

§9 · Hourly return heatmap

24-hour signed Δp grid · green = up · red = down
HOURLY RETURN HEATMAP · n=24 bars · best 0.60% · worst -0.70% · typical |Δ| 0.19%BEARISH SESSION -1.15%BEST+0.60%17hWORST-0.70%5hTYPICAL |Δ|0.19%mean absoluteCUMULATIVE-1.15%Σ signed ΔSTREAK▬ 0flat-runASIA · 00-08 UTCμ -0.09% · Σ -0.65%EUROPE · 08-16 UTCμ +0.03% · Σ +0.25%US · 16-24 UTCμ -0.09% · Σ -0.75%CUMULATIVE Δ PATH · final -1.15%+0.15%-1.15%0.15% · 1h0.15% · 1h0.15%1h-0.20% · 2h-0.20% · 2h-0.20%2h0.15% · 3h0.15% · 3h0.15%3h0.05% · 4h0.05% · 4h0.05%4h-0.70% · 5h-0.70% · 5h-0.70%5h▼ WORST0.05% · 6h0.05% · 6h0.05%6h-0.15% · 7h-0.15% · 7h-0.15%7h-0.05% · 8h-0.05% · 8h-0.05%8h0.10% · 9h0.10% · 9h0.10%9h0.00% · 10h0.00% · 10h·10h-0.05% · 11h-0.05% · 11h-0.05%11h-0.10% · 12h-0.10% · 12h-0.10%12h0.00% · 13h0.00% · 13h·13h0.55% · 14h0.55% · 14h0.55%14h-0.20% · 15h-0.20% · 15h-0.20%15h-0.45% · 16h-0.45% · 16h-0.45%16h0.60% · 17h0.60% · 17h0.60%17h★ BEST-0.15% · 18h-0.15% · 18h-0.15%18h-0.30% · 19h-0.30% · 19h-0.30%19h-0.35% · 20h-0.35% · 20h-0.35%20h0.10% · 21h0.10% · 21h0.10%21h-0.15% · 22h-0.15% · 22h-0.15%22h-0.05% · 23h-0.05% · 23h-0.05%23h0.00% · 24h0.00% · 24h·24hTIME PATTERNEurope-led (+0.25%)RUNSup max 2 · down max 3BREADTH33% up · 54% down · 13% flat
8 up bars · 13 down · best 0.60% · worst -0.70% · typical |Δ| 0.194%

§10 · Equity curve & underwater drawdown

Cumulative compounded return + running peak-to-trough
EQUITY & DRAWDOWN ANALYSIS · n=25 barsLOSS · SHALLOW DD (-1.15%)FINAL-1.15%MAX DD-1.30%RECOVERYONGOING · 23 barsMAX RUN-UP+0.15%UNDERWATER23/25 (92%)STREAK▬ 0EQUITY CURVE · end 0.9885 · peak 1.0015 · range [0.9885, 1.0015]1.00150.9885break-even = 1★ PEAK 1.0015UNDERWATER DRAWDOWN · max -1.30% · moderate0%-1.30%▼ TROUGH -1.30%TOP DRAWDOWN PERIODS · 1 total#1 -1.30%bar 3-25 · 23 bars · ONGOINGDD SEVERITYmoderate (max -1.30%)RECOVERYongoing · 23 barsTIME UNDER WATER92% of session · 23/25 bars
final equity 0.9885 (-1.15%) · max DD -1.30% · time-under-water 23/25 bars

§11 · Rolling-window statistics (w = 6 bars)

Rolling annualised Sharpe ratio · green positive · red negative
n=19 · +5 / −14 (26% positive) · μ=-21.98 · σ=29.10UNPROFITABLE STRATEGYLAST -66.72 (-1.54σ vs μ)85.4442.720.00-42.72-85.44μ = -21.98-23.77-23.77-40.56-40.56-33.00-33.00-36.47-36.47-39.72-39.72-17.82-17.82-45.28-45.28-22.83-22.8332.7632.7611.8211.82-11.79-11.7914.8014.8012.8212.821.731.73-35.01-35.01-22.05-22.05-11.10-11.10-85.44-85.44-66.72-66.72v > 0 · positivev < 0 · negativeμ mean lineμ ± σ bandlatest bar (outlined)
latest -66.717 · range [-85.44, 32.76] · μ -21.980 · positive Sharpe = excess-return-per-risk earned by buying-and-holding through this window
Rolling annualised volatility (%)
n=19 · μ=26.4483 · σ=11.0292 · range [6.3937, 42.2129] · R²=0.029▼ FALLING -46.56%σ EXTREME 41.70%LAST 16.412542.212933.258124.303315.34856.3937μ = 26.4483max 42.2129min 6.3937dataMA(3)OLS R²=0.03μ lineμ ± σ bandmaxmin
latest 16.41% · range [6.39%, 42.21%] · μ 26.45% · σ̂ scaled to annualised (×√8760)
Rolling lag-1 autocorrelation ρ(1)
n=19 · +2 / −17 (11% positive) · μ=-0.209 · σ=0.176MEAN-REVERSIONLAST -0.061 (+0.84σ vs μ)0.4550.2270.000-0.227-0.455μ = -0.209-0.349-0.349-0.376-0.376-0.329-0.329-0.419-0.419-0.143-0.143-0.181-0.1810.1550.155-0.048-0.0480.0370.037-0.343-0.343-0.012-0.012-0.324-0.324-0.455-0.455-0.328-0.328-0.255-0.255-0.359-0.359-0.034-0.034-0.148-0.148-0.061-0.061v > 0 · positivev < 0 · negativeμ mean lineμ ± σ bandlatest bar (outlined)
latest -0.061 · |ρ| > 0.3 ⇒ regime with persistence (ρ > 0) or reversal (ρ < 0) · |ρ| ≤ 0.1 = consistent with random walk

§12 · Hypothesis tests (α = 0.05)

Formal inference at 5% significance
1 of 6 REJECT · mixed evidence1 reject·5 pass·α = 0.05
𝒩

Jarque-Bera

FAIL TO REJECTns

H₀: Δp ~ Normal(μ, σ²)

STATISTIC
3.2918
p-VALUE (log scale)
0.1928
α
10⁻⁴10⁻³10⁻²10⁻¹1
p ≥ α · null retainednormality not rejected
ρ

Ljung-Box(h=5)

FAIL TO REJECTns

H₀: No serial autocorrelation up to lag 5

STATISTIC
6.7514
p-VALUE (log scale)
0.2388
α
10⁻⁴10⁻³10⁻²10⁻¹1
p ≥ α · null retainedconsistent with white noise
Ψ

Dickey-Fuller (τ_μ)

FAIL TO REJECTns

H₀: p has a unit root (non-stationary)

STATISTIC
-1.6849
p-VALUE (log scale)
0.4453
α
10⁻⁴10⁻³10⁻²10⁻¹1
p ≥ α · null retainedrandom-walk behaviour (crit ≈ -2.86)
±

Wald-Wolfowitz runs

FAIL TO REJECTns

H₀: Sign sequence of Δ is random

STATISTIC
1.4739
p-VALUE (log scale)
0.1405
α
10⁻⁴10⁻³10⁻²10⁻¹1
p ≥ α · null retainedsigns appear random (14 runs)
χ

KPSS (μ stationarity)

REJECT H₀*

H₀: p IS level-stationary

STATISTIC
0.6562
p-VALUE (log scale)
0.0175
α
10⁻⁴10⁻³10⁻²10⁻¹1
p < α · rejection zonenon-stationary (crit 0.463)
χ

Variance ratio q=3

FAIL TO REJECTns

H₀: Δp is a random walk · VR = 1

STATISTIC
-1.7084
p-VALUE (log scale)
0.0876
α
10⁻⁴10⁻³10⁻²10⁻¹1
p ≥ α · null retainedVR 0.480 ≈ 1 (RW behaviour)
Each row states an explicit null H₀, the test statistic, an approximated p-value, and the decision. REJECT means evidence against H₀. KPSS complements ADF (rejecting both ⇒ ambiguous; rejecting one ⇒ clean verdict).

§13 · Spectral analysis (DFT periodogram)

Power spectrum of Δp · ‖X̂(k)‖²/n
n=12 bins · noise floor μ=7.32e-6 · top T=3.43h (32.5%) · top-3 cover 66.7%2 SIGNIFICANT CYCLEScumulative energy ↗ (2 bins above 2× noise)2.9e-52.1e-51.4e-57.1e-60.0e+0μ noise floor2× noise (significance)period 24.0 · power 1.54e-6 · 1.8% energyperiod 24.0 · power 1.54e-6 · 1.8% energyperiod 12.0 · power 5.30e-6 · 6.0% energyperiod 12.0 · power 5.30e-6 · 6.0% energyperiod 8.0 · power 3.12e-6 · 3.6% energyperiod 8.0 · power 3.12e-6 · 3.6% energyperiod 6.0 · power 8.75e-7 · 1.0% energyperiod 6.0 · power 8.75e-7 · 1.0% energyperiod 4.8 · power 7.58e-6 · 8.6% energyperiod 4.8 · power 7.58e-6 · 8.6% energyperiod 4.0 · power 7.18e-6 · 8.2% energyperiod 4.0 · power 7.18e-6 · 8.2% energyperiod 3.4 · power 2.86e-5 · 32.5% energyperiod 3.4 · power 2.86e-5 · 32.5% energyperiod 3.0 · power 2.17e-6 · 2.5% energyperiod 3.0 · power 2.17e-6 · 2.5% energyperiod 2.7 · power 2.02e-5 · 23.0% energyperiod 2.7 · power 2.02e-5 · 23.0% energyperiod 2.4 · power 6.13e-7 · 0.7% energyperiod 2.4 · power 6.13e-7 · 0.7% energyperiod 2.2 · power 9.85e-6 · 11.2% energyperiod 2.2 · power 9.85e-6 · 11.2% energyperiod 2.0 · power 8.44e-7 · 1.0% energyperiod 2.0 · power 8.44e-7 · 1.0% energy50% by T=3.4h#1 dominantT=3.43h#2T=2.67h#3T=2.18hT=2hT=3hT=4hT=6hT=8hT=12hT=16hT=24h← shorter cycle (high freq · Nyquist=½) · period T (bars per cycle) · longer cycle (low freq · 1/n) →#1 dominant#2 peak#3 peak> 2× noisenoiseμ floor2μ sig.cum energy
dominant period ≈ 3.43h (freq 0.292) · concentrates 32.5% of total energy · Σ|X̂|²/n = 8.779e-5

▸ Depth section using sovereign-store price series (2810 bars · effective 1752810 bars/year) — annualisation reflects native polling cadence, not upstream timeframes.

§14 · 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 →

§15 · Horizon returns

Returns · per bar / per day / per horizon
Horizon 15.5 d · σ/bar 0.019pp · expected |Δp| over horizon 0.36ppterminal variance p(1−p) = 0.0229 · n = 2810✓ n = 2810
μ per bar
-0.000pp
average Δp · drift
σ per bar
0.019pp
one-bar volatility · logit-free
Per-day movedaily
0.09pp
σ × √24
Per-horizon move16d
0.36pp
σ × √372.8472977777778
Terminal variancebinary
0.0229
p(1−p) at resolution
Current pricep
2.4¢
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.

§16 · Tail risk

VaR · ES · max drawdown
VaR₉₅ 0.03pp · ES₉₅ 0.04pp · method parametric · drift-correcteddrift -0.000pp/bar · quantised: yes · median step 0.05pp · unique ratio 0.01✓ n = 2810
VaR 95%
0.03pp
1.645·σ (parametric) of Δp
ES 95%
0.04pp
mean of the tail
Max drawdown
28.8pp
peak 3.3¢ → trough 2.4¢
Median step
0.05pp
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.

§17 · Odds conversion

Odds conversion · every dialect a bettor thinks in
Implied probabilityP
2.4%
= price
Decimal oddsEU
42.553
total return per $1
AmericanUS
+4155
$100 wins $4155
FractionalUK
41.55 / 1
profit per $1 risked
Profit per $100stake
+$4155.32
clean dollar framing
-1000-5000+500+1000020406080100you · 2.4%implied probability (%)American odds
underdog (+)favorite (-)your price
Price → implied probability → decimal odds → American moneyline → fractional. Five views of the same number, plus the moneyline curve.

§18 · Binary entropy

Binary entropy · uncertainty as bits of information
Market entropyH(p)
0.161 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.161 bit
Δ +0.000 bit vs market
Surprise · YES−log₂ p
5.41 bit
self-information
Surprise · NO−log₂(1−p)
0.03 bit
self-information
0.000.260.530.791.050.00.20.40.60.81.0marketmodelprobabilityH (bits)
Market entropy only — model entropy requires an external q.

§19 · 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 (snapshot)
gamma-api.polymarket.com
Upstream (history)
clob.polymarket.com
YES token ID
80866595097163743756836544235158704187050842622501590485463390368127663845144
NO token ID
59148378005891809491211416100126897026310179790411869168117833625964267167611
Snapshot fetched
2026-06-14 11:09:08 UTC
Snapshot age
1.3s
History points
25 CLOB mids
Page rendered
2026-06-14 11:09:09 UTC
Storage policy
no persistence — fetched on every request
SHA-256 attestation
e95b970f4364f88486b00906ad9ae9a0c674d77b64f5994db6aad7a8dcd35150 · deterministic hash of source snapshot
Open data licence
CC0 / public domain

§∞-2 · Related markets · explore more

HL PREDGermany94.4¢HL PREDSpain90.4¢HL PREDUruguay66.6¢POLYMARKETWill Australia win the 2026 FIFA World Cup?0¢POLYMARKETWill Scotland win the 2026 FIFA World Cup?0¢POLYMARKETUS x Iran permanent peace deal by June 15, 2026?23¢HL PERPBTC-USD perpetual$64,485HL PERPETH-USD perpetual$1,672.9HL PERPHYPE-USD perpetual$60.75

Also see: /arb opportunities · RSS feed · more in Tech & Business

Market depth

▸ live order book · Polymarket YES
Depth within 1bp
$0
bid $0 · ask $0
Depth within 5bp
$0
bid $0 · ask $0
Depth within 10bp
$0
bid $0 · ask $0
Depth within 50bp
$0
bid $0 · ask $0
Mid price
0.023500
(best bid + best ask) / 2
Spread
1276.6bp
(bestAsk − bestBid) / mid
Imbalance (whole book)
-0.889
ask-heavy
Imbalance (top-5)
+0.888
bid-heavy top-of-book

Slippage scenarios

▸ live book walk · Polymarket YES

Simulating a market order at three notionals against the live book. Slippage = avg execution price vs. mid, in basis points. Worst fill = price of the deepest level touched. Live JSON: /api/asset/pm-will-openai-have-the-best-ai-model-at-the-end-of-june-2026/slippage?size=10000&side=buy

SideNotionalAvg fillSlippageWorst fillLevelsStatus
BUY$1.00K0.05599813828.88bp0.08900037FILLED
BUY$10.00K0.12517443265.72bp0.28000074FILLED
BUY$100.00K0.542740220953.00bp0.990000118FILLED
SELL$1.00K0.0066827156.69bp0.00200020FILLED
SELL$10.00K0.0022949023.88bp0.00100021PARTIAL
SELL$100.00K0.0022949023.88bp0.00100021PARTIAL

Risk metrics

▸ sovereign store · 2,810 barsperiods/year ≈ 1.75M
Realized vol (annualised)
848.26%
σ per bar = 0.006407
Mean return (annualised)
-13122.39%
μ per bar = -0.000075
Sharpe (rf=0)
-15.47
annualised; risk-free assumed zero
Max drawdown
28.79%
peak 0.03 → trough 0.02 over 1661 bars

/api/asset/pm-will-openai-have-the-best-ai-model-at-the-end-of-june-2026/risk · same metrics, JSON