POLYMARKET · PREDICTION MARKET · TECH & BUSINESS

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

YES · live
2.5¢
NO · live
97.5¢

▸ Advanced metrics · M2M bundle

polymarket · will-openai-have-the-best-ai-model-at-the-end-of-june-2026 · fresh · feed 0s old
24h sparkline · 60 pts▼ -12.07%
realized vol (ann.)
21.19%
max drawdown
30.30%
sharpe
—
ulcer index
20.39%
RMS drawdown
pain index
18.68%
mean drawdown
mod. VaR 95%
0.00%
Cornish-Fisher
martin ratio
—
ret / ulcer
CDaR 95%
29.06%
cond. drawdown
gain/pain
0.62
Σgain / Σ|loss|
sterling
—
ret / CDaR
omega (θ=0)
0.62
upside/downside
roll spread
2.4 bps
implied (price-only)
bars used
2000
store
spread
—
24h Δ
-12.07%
flow lean
—
carry
flat
signalNEUTRALconfidence 25%
  • 24h change -12.07%
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 →
LIVEPOLL0SRCFRESH3ms⏱--:--:-- 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
2.5¢
NO · live
97.5¢
YES price · live 24h
n=25 · μ=0.0281 · σ=0.0031 · range [0.0235, 0.0365] · R²=0.403▼ FALLING -30.14%σ HIGH 11.18%LAST 0.02550.03650.03330.03000.02670.0235μ = 0.0281max 0.0365min 0.0235dataMA(5)OLS R²=0.40μ lineμ ± σ bandmaxminlive endpoint
25 ticks · last 2.55¢
YES / NO split · live
YES 2.5%NO 97.5%NO97.5%97.45¢ · odds 1/1.03
Σ 100.00% · fair
Σ-sides total = 100.00% (tight rounding)
H(p) entropy = 0.171 / 1.00 bits (17%) · informative — one side favoured
YES
2.5%2.5¢39.22×▬ +0.00pp
NO
97.5%97.5¢1.03×▬ +0.00pp
Σ 100.00% · arb gap 0.00pp
Per-tick activity · |Δp| in basis points · live
n=24 · Σ=460 · μ=19.2 · σ=20.6 · CV=1.08BURSTYcumulative energy ↗ · 50% by h=12017355270μ = 197050%h1h5h9h13h17h21#1 peak#2-3> μactivequietμ linecum energy
Σ 460bp moved · peak 70bp · n=24 ticks
Live numerics · pulse on poll
LIVE NUMERICS8 metrics·POLL 0
⏱snapshot age
3ms
▲YES mid
2.55¢ (2.55%)
▼NO mid
97.45¢ (97.45%)
ΣΣ sides
100.00%
⚖arb gap
0.000pp
$24h vol $
$36.9k
≋liquidity $
$103.9k
◳history points
25 ticks (live)

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

YES price · CLOB mid
n=25 · μ=0.0281 · σ=0.0031 · range [0.0235, 0.0365] · R²=0.403▼ FALLING -30.14%σ HIGH 11.18%LAST 0.02550.03650.03330.03000.02670.0235μ = 0.0281max 0.0365min 0.0235dataMA(5)OLS R²=0.40μ lineμ ± σ bandmaxmin
25 YES observations from clob.polymarket.com · last 2.55¢
NO price · CLOB mid
n=25 · μ=0.9719 · σ=0.0031 · range [0.9635, 0.9765] · R²=0.403▲ RISING +1.14%σ LOW 0.32%LAST 0.97450.97650.97330.97000.96670.9635μ = 0.9719max 0.9765min 0.9635dataMA(5)OLS R²=0.40μ lineμ ± σ bandmaxmin
25 NO observations from clob.polymarket.com · last 97.45¢

§2 · Distribution of Δp

Histogram of hourly increments
n=24 · 10 bins · μ=-0.0004 · σ=0.0027 · skew=0.29 (symmetric) · kurt=0.51 (mesokurtic)864201-0.63ppbin -0.63pp · n=1 · 12.5% peakbin -0.63pp · n=1 · 12.5% peak1-0.50ppbin -0.50pp · n=1 · 12.5% peakbin -0.50pp · n=1 · 12.5% peak1-0.37ppbin -0.37pp · n=1 · 12.5% peakbin -0.37pp · n=1 · 12.5% peak2-0.24ppbin -0.24pp · n=2 · 25.0% peakbin -0.24pp · n=2 · 25.0% peak8-0.11ppbin -0.11pp · n=8 · 100.0% peakbin -0.11pp · n=8 · 100.0% peak60.02ppbin 0.02pp · n=6 · 75.0% peakbin 0.02pp · n=6 · 75.0% peak20.15ppbin 0.15pp · n=2 · 25.0% peakbin 0.15pp · n=2 · 25.0% peak0.28pp10.41ppbin 0.41pp · n=1 · 12.5% peakbin 0.41pp · n=1 · 12.5% peak20.54ppbin 0.54pp · n=2 · 25.0% peakbin 0.54pp · n=2 · 25.0% 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=0.31 · kurt=1.02 · near 14 / mid 10 / far 0 · OLS slope=0.98 intercept=-0.00APPROXIMATELY NORMALMILDLY HEAVY UPPERLOWER 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=25RIGHT-SKEWED (G₁=0.65)
μ MEAN2.81¢95% CI: [2.68¢, 2.93¢]
σ STD DEV0.31ppσ² = 0.098 · CV = 11.18%
med MEDIAN2.80¢Q₁ 2.55¢ · Q₃ 2.95¢
FIVE-NUMBER SUMMARY · BOX PLOTrange 1.30pp · IQR 0.40pp (1.349σ→0.42pp)
min 2.35¢Q₁ 2.55¢med 2.80¢Q₃ 2.95¢max 3.65¢μ
SKEWNESS · G₁0.647right-skewed
−3−10+1+3
EXCESS KURTOSIS · G₂0.144mesokurtic · normal-like
−30+2+4+6
μ ↔ median≈ equal · symmetric|μ−med| / σ = 0.03
σ × 1.349 ↔ IQRconsistent with normalratio = 1.06
range ↔ σwide tails (range > 4σ)range / σ = 4.14
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 · ADF rejects unit root
ρ(1) AUTOCORR-0.181within white-noise band
ρ(2) AUTOCORR-0.260lag-2 not significant
H · HURST EXPONENT0.617persistent
OLS TREND · t-STAT-3.943significant @ α=0.05
HURST EXPONENT [0, 1]persistent · H = 0.617
H = 0.617PERSISTENT
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=1-0.181k=2-0.260k=3+0.161k=4+0.135k=5-0.1810+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|=3.94)
−5 reject−1.960 retain H₀+1.96+5 reject
REGIME CLASSIFICATIONMEAN-REVERTING · ADF rejects unit rootfrom Hurst + ρ(1) joint diagnosis
PREDICTABILITY · score 0.41high · clear structure|ρ(1)| + 2·|H − 0.5| heuristic
TREND SIGNIFICANCESIGNIFICANT @ 1% (|t|=3.94)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 (97¢)
PRIMARY · YES2.55¢implied prob 2.55% · decimal odds 39.22×
COUNTER · NO97.45¢implied prob 97.45% · decimal odds 1.03×
2.55¢
97.45¢
Σ-SIDES ARBITRAGE TESTPERFECT · ARB-FREE Σ=100.00%
0%50%100% · target110%
Σ = 100.00% · |1 − Σ| = 0.000pp
24H ACTIVITY · LIQUIDITYACTIVE
24H VOLUME36.87k USD 24h
LIQUIDITY103.87k USD
MARKET QUALITYPERFECT · ARB-FREE Σ=100.00%|1−Σ| ≤ 0.5pp ⇒ fair · > 2pp ⇒ inefficient
PRICING SKEWFAVOURS NO (97¢)|primary − counter| = 0.949 · entropy 0.171 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 2.5%NO 97.5%YES p̂2.5%H = 0.171 / 1.00 bits
Probability scale (YES)
0%25%50%
fair75%100%
Implied decimal odds
YES39.22×(3¢)NO1.03×(97¢)
Kelly bet-size (% of bankroll) K* = 0.00%
K* full
0.00%
½K half
0.00%
¼K quarter
0.00%
Entropy H(p̂) = 0.171 bits (17% 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
08hrs
51min
15.37 days·θ = 1.537 pp/day
YES →$1.00(P = 2.5%)
NO →$0.00(P = 97.5%)
current: $0.0255 · expected return per side: $0.97 on YES hit · $0.03 on NO hit
0%25%50%75%100%YES $1NO $0NOW+7.7dRESOLVESP projection · σ=0.31% · path funnel to settle at YES=1 or NO=0
Theta progression · θ ∝ σ / √t_remainingθ_now = 1.537 pp/day
now15.37d left
1.537 pp/day×1.00
−25%11.53d left
1.775 pp/day×1.15
−50%7.68d left
2.174 pp/day×1.41
−75%3.84d left
3.075 pp/day×2.00
−90%1.54d left
4.861 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 -1.10%BEST+0.60%13hWORST-0.70%1hTYPICAL |Δ|0.19%mean absoluteCUMULATIVE-1.10%Σ signed ΔSTREAK▬ 0flat-runASIA · 00-08 UTCμ -0.11% · Σ -0.80%EUROPE · 08-16 UTCμ -0.01% · Σ -0.05%US · 16-24 UTCμ -0.03% · Σ -0.25%CUMULATIVE Δ PATH · final -1.10%+0.00%-1.30%-0.70% · 1h-0.70% · 1h-0.70%1h▼ WORST0.05% · 2h0.05% · 2h0.05%2h-0.15% · 3h-0.15% · 3h-0.15%3h-0.05% · 4h-0.05% · 4h-0.05%4h0.10% · 5h0.10% · 5h0.10%5h0.00% · 6h0.00% · 6h·6h-0.05% · 7h-0.05% · 7h-0.05%7h-0.10% · 8h-0.10% · 8h-0.10%8h0.00% · 9h0.00% · 9h·9h0.55% · 10h0.55% · 10h0.55%10h-0.20% · 11h-0.20% · 11h-0.20%11h-0.45% · 12h-0.45% · 12h-0.45%12h0.60% · 13h0.60% · 13h0.60%13h★ BEST-0.15% · 14h-0.15% · 14h-0.15%14h-0.30% · 15h-0.30% · 15h-0.30%15h-0.35% · 16h-0.35% · 16h-0.35%16h0.10% · 17h0.10% · 17h0.10%17h-0.15% · 18h-0.15% · 18h-0.15%18h-0.05% · 19h-0.05% · 19h-0.05%19h0.00% · 20h0.00% · 20h·20h0.35% · 21h0.35% · 21h0.35%21h0.00% · 22h0.00% · 22h·22h-0.15% · 23h-0.15% · 23h-0.15%23h0.00% · 24h0.00% · 24h·24hTIME PATTERNEurope-led (+-0.05%)RUNSup max 1 · down max 3BREADTH25% up · 54% down · 21% flat
6 up bars · 13 down · best 0.60% · worst -0.70% · typical |Δ| 0.192%

§10 · Equity curve & underwater drawdown

Cumulative compounded return + running peak-to-trough
EQUITY & DRAWDOWN ANALYSIS · n=25 barsLOSS · SHALLOW DD (-1.10%)FINAL-1.10%MAX DD-1.30%RECOVERYONGOING · 24 barsMAX RUN-UP+0.00%UNDERWATER24/25 (96%)STREAK▬ 0EQUITY CURVE · end 0.9890 · peak 1.0000 · range [0.9870, 1.0000]1.00000.9870break-even = 1★ PEAK 1.0000UNDERWATER DRAWDOWN · max -1.30% · moderate0%-1.30%▼ TROUGH -1.30%TOP DRAWDOWN PERIODS · 1 total#1 -1.30%bar 2-25 · 24 bars · ONGOINGDD SEVERITYmoderate (max -1.30%)RECOVERYongoing · 24 barsTIME UNDER WATER96% of session · 24/25 bars
final equity 0.9890 (-1.10%) · max DD -1.30% · time-under-water 24/25 bars

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

Rolling annualised Sharpe ratio · green positive · red negative
n=19 · +7 / −11 (37% positive) · μ=-13.36 · σ=30.87MIXED EDGELAST 13.80 (+0.88σ vs μ)85.4442.720.00-42.72-85.44μ = -13.36-39.72-39.72-17.82-17.82-45.28-45.28-22.83-22.8332.7632.7611.8211.82-11.79-11.7914.8014.8012.8212.821.731.73-35.01-35.01-22.05-22.05-11.10-11.10-85.44-85.44-66.72-66.72-6.61-6.6122.7422.740.000.0013.8013.80v > 0 · positivev < 0 · negativeμ mean lineμ ± σ bandlatest bar (outlined)
latest 13.800 · range [-85.44, 32.76] · μ -13.363 · positive Sharpe = excess-return-per-risk earned by buying-and-holding through this window
Rolling annualised volatility (%)
n=19 · μ=24.0783 · σ=11.4863 · range [6.3937, 42.2129] · R²=0.002▼ FALLING -42.43%σ EXTREME 47.70%LAST 15.869842.212933.258124.303315.34856.3937μ = 24.0783max 42.2129min 6.3937dataMA(3)OLS R²=0.00μ lineμ ± σ bandmaxmin
latest 15.87% · range [6.39%, 42.21%] · μ 24.08% · σ̂ scaled to annualised (×√8760)
Rolling lag-1 autocorrelation ρ(1)
n=19 · +3 / −16 (16% positive) · μ=-0.145 · σ=0.163MEAN-REVERSIONLAST -0.039 (+0.65σ vs μ)0.4550.2270.000-0.227-0.455μ = -0.145-0.143-0.143-0.181-0.1810.1550.155-0.048-0.0480.0370.037-0.343-0.343-0.012-0.012-0.324-0.324-0.455-0.455-0.328-0.328-0.255-0.255-0.359-0.359-0.034-0.034-0.148-0.148-0.061-0.061-0.160-0.160-0.105-0.1050.0440.044-0.039-0.039v > 0 · positivev < 0 · negativeμ mean lineμ ± σ bandlatest bar (outlined)
latest -0.039 · |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
3 of 6 REJECT · mixed evidence3 reject·3 pass·α = 0.05
𝒩

Jarque-Bera

FAIL TO REJECTns

H₀: Δp ~ Normal(μ, σ²)

STATISTIC
2.9031
p-VALUE (log scale)
0.2342
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
5.2260
p-VALUE (log scale)
0.3893
α
10⁻⁴10⁻³10⁻²10⁻¹1
p ≥ α · null retainedconsistent with white noise
Ψ

Dickey-Fuller (τ_μ)

REJECT H₀**

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

STATISTIC
-3.5947
p-VALUE (log scale)
0.0061
α
10⁻⁴10⁻³10⁻²10⁻¹1
p < α · rejection zonestationary · mean-reverting (crit ≈ -2.86)
±

Wald-Wolfowitz runs

REJECT H₀*

H₀: Sign sequence of Δ is random

STATISTIC
2.0895
p-VALUE (log scale)
0.0367
α
10⁻⁴10⁻³10⁻²10⁻¹1
p < α · rejection zonenon-random sign pattern (13 runs)
χ

KPSS (μ stationarity)

REJECT H₀*

H₀: p IS level-stationary

STATISTIC
0.5926
p-VALUE (log scale)
0.0233
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
-1.7198
p-VALUE (log scale)
0.0855
α
10⁻⁴10⁻³10⁻²10⁻¹1
p ≥ α · null retainedVR 0.477 ≈ 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=7.55e-6 · top T=3.43h (22.8%) · top-3 cover 59.2%2 SIGNIFICANT CYCLEScumulative energy ↗ (2 bins above 2× noise)2.1e-51.5e-51.0e-55.2e-60.0e+0μ noise floor2× noise (significance)period 24.0 · power 1.25e-6 · 1.4% energyperiod 24.0 · power 1.25e-6 · 1.4% energyperiod 12.0 · power 7.95e-6 · 8.8% energyperiod 12.0 · power 7.95e-6 · 8.8% energyperiod 8.0 · power 6.90e-6 · 7.6% energyperiod 8.0 · power 6.90e-6 · 7.6% energyperiod 6.0 · power 2.26e-6 · 2.5% energyperiod 6.0 · power 2.26e-6 · 2.5% energyperiod 4.8 · power 3.06e-6 · 3.4% energyperiod 4.8 · power 3.06e-6 · 3.4% energyperiod 4.0 · power 1.41e-5 · 15.6% energyperiod 4.0 · power 1.41e-5 · 15.6% energyperiod 3.4 · power 2.06e-5 · 22.8% energyperiod 3.4 · power 2.06e-5 · 22.8% energyperiod 3.0 · power 1.32e-6 · 1.5% energyperiod 3.0 · power 1.32e-6 · 1.5% energyperiod 2.7 · power 1.89e-5 · 20.9% energyperiod 2.7 · power 1.89e-5 · 20.9% energyperiod 2.4 · power 2.14e-6 · 2.4% energyperiod 2.4 · power 2.14e-6 · 2.4% energyperiod 2.2 · power 1.19e-5 · 13.1% energyperiod 2.2 · power 1.19e-5 · 13.1% energyperiod 2.0 · power 1.67e-7 · 0.2% energyperiod 2.0 · power 1.67e-7 · 0.2% energy50% by T=3.4h#1 dominantT=3.43h#2T=2.67h#3T=4.00hT=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 22.8% of total energy · Σ|X̂|²/n = 9.056e-5

▸ Depth section using sovereign-store price series (3594 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 15.4 d · σ/bar 0.019pp · expected |Δp| over horizon 0.37ppterminal variance p(1−p) = 0.0248 · n = 3594✓ n = 3594
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 move15d
0.37pp
σ × √368.86071
Terminal variancebinary
0.0248
p(1−p) at resolution
Current pricep
2.5¢
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 0.00✓ n = 3594
VaR 95%
0.03pp
1.645·σ (parametric) of Δp
ES 95%
0.04pp
mean of the tail
Max drawdown
30.3pp
peak 3.3¢ → trough 2.3¢
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
2.5%
= price
Decimal oddsEU
39.216
total return per $1
AmericanUS
+3822
$100 wins $3822
FractionalUK
38.22 / 1
profit per $1 risked
Profit per $100stake
+$3821.57
clean dollar framing
-1000-5000+500+1000020406080100you · 2.5%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)
0.171 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.171 bit
Δ +0.000 bit vs market
Surprise · YES−log₂ p
5.29 bit
self-information
Surprise · NO−log₂(1−p)
0.04 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 15:08:21 UTC
Snapshot age
3ms
History points
25 CLOB mids
Page rendered
2026-06-14 15:08:21 UTC
Storage policy
no persistence — fetched on every request
SHA-256 attestation
2f507519766a24f079eb1741faaaa95cdf458396e141f16791ec6fbde66ab92e · deterministic hash of source snapshot
Open data licence
CC0 / public domain

§∞-2 · Related markets · explore more

HL PREDGermany94.6¢HL PREDSpain90.0¢HL PREDUruguay66.7¢POLYMARKETWill Australia win the 2026 FIFA World Cup?0¢POLYMARKETWill Scotland win the 2026 FIFA World Cup?0¢POLYMARKETWill Turkiye win the 2026 FIFA World Cup?1¢HL PERPBTC-USD perpetual$64,084HL PERPETH-USD perpetual$1,662.7HL PERPHYPE-USD perpetual$60.38

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
0.025500
(best bid + best ask) / 2
Spread
1176.5bp
(bestAsk − bestBid) / mid
Imbalance (whole book)
-0.889
ask-heavy
Imbalance (top-5)
+0.754
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$1.00K0.05437011321.72bp0.06900027FILLED
BUY$10.00K0.12331238357.62bp0.28000075FILLED
BUY$100.00K0.546008204120.63bp0.998000121FILLED
SELL$1.00K0.0066997373.14bp0.00200021FILLED
SELL$10.00K0.0022959099.99bp0.00100022PARTIAL
SELL$100.00K0.0022959099.99bp0.00100022PARTIAL

Risk metrics

▸ sovereign store · 3,594 barsperiods/year ≈ 1.75M
Realized vol (annualised)
898.68%
σ per bar = 0.006788
Mean return (annualised)
-6274.48%
μ per bar = -0.000036
Sharpe (rf=0)
-6.98
annualised; risk-free assumed zero
Max drawdown
30.30%
peak 0.03 → trough 0.02 over 1992 bars

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