POLYMARKET · PREDICTION MARKET · WEATHER & CLIMATE

Will the highest temperature in Seoul be 23°C on June 20?

YES · live
0.1¢
NO · live
100.0¢

▸ Advanced metrics · M2M bundle

polymarket · highest-temperature-in-seoul-on-june-20-2026-23c · fresh · feed 5s old
24h sparkline · 60 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
552
store
spread
—
24h Δ
—
flow lean
—
carry
flat
signalNEUTRALconfidence 20%
Same bundle via M2M API: /api/m2m/pm-highest-temperature-in-seoul-on-june-20-2026-23c/bundle · venue execution: polymarket →
LIVEPOLL0SRCFRESH4.8s⏱--:--:-- 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
0.1¢
NO · live
100.0¢
YES price · live 24h
n=25 · μ=0.0309 · σ=0.0585 · range [0.0005, 0.1550] · R²=0.496▼ FALLING -99.68%σ EXTREME 189.34%LAST 0.00050.15500.11640.07770.03910.0005μ = 0.0309max 0.1550min 0.0005dataMA(5)OLS R²=0.50μ lineμ ± σ bandmaxminlive endpoint
25 ticks · last 0.05¢
YES / NO split · live
YES 0.1%NO 100.0%NO100.0%99.95¢ · odds 1/1.00
Σ 100.00% · fair
Σ-sides total = 100.00% (tight rounding)
H(p) entropy = 0.006 / 1.00 bits (1%) · informative — one side favoured
YES
0.1%0.1¢2000.00×▬ +0.00pp
NO
100.0%100.0¢1.00×▬ +0.00pp
Σ 100.00% · arb gap 0.00pp
Per-tick activity · |Δp| in basis points · live
n=24 · Σ=2,055 · μ=85.6 · σ=281.4 · CV=3.29BURSTY · concentratedcumulative energy ↗ · 50% by h=503466931,0391,385μ = 861,38550%h1h5h9h13h17h21#1 peak#2-3> μactivequietμ linecum energy
Σ 2055bp moved · peak 1385bp · n=24 ticks
Live numerics · pulse on poll
LIVE NUMERICS8 metrics·POLL 0
⏱snapshot age
4.8s
▲YES mid
0.05¢ (0.05%)
▼NO mid
99.95¢ (99.95%)
ΣΣ sides
100.00%
⚖arb gap
0.000pp
$24h vol $
$61.5k
≋liquidity $
$16.4k
◳history points
25 ticks (live)

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

YES price · CLOB mid
n=25 · μ=0.0309 · σ=0.0585 · range [0.0005, 0.1550] · R²=0.496▼ FALLING -99.68%σ EXTREME 189.34%LAST 0.00050.15500.11640.07770.03910.0005μ = 0.0309max 0.1550min 0.0005dataMA(5)OLS R²=0.50μ lineμ ± σ bandmaxmin
25 YES observations from clob.polymarket.com · last 0.05¢
NO price · CLOB mid
n=25 · μ=0.9691 · σ=0.0585 · range [0.8450, 0.9995] · R²=0.496▲ RISING +18.28%σ HIGH 6.03%LAST 0.99950.99950.96090.92230.88360.8450μ = 0.9691max 0.9995min 0.8450dataMA(5)OLS R²=0.50μ lineμ ± σ bandmaxmin
25 NO observations from clob.polymarket.com · last 99.95¢

§2 · Distribution of Δp

Histogram of hourly increments
n=24 · 10 bins · μ=-0.0049 · σ=0.0271 · skew=-4.21 (left-skewed) · kurt=16.60 (leptokurtic (fat tails))211611501-13.11ppbin -13.11pp · n=1 · 4.8% peakbin -13.11pp · n=1 · 4.8% peak-11.62pp-10.14pp-8.65pp-7.17pp-5.68pp-4.20pp1-2.71ppbin -2.71pp · n=1 · 4.8% peakbin -2.71pp · n=1 · 4.8% peak1-1.23ppbin -1.23pp · n=1 · 4.8% peakbin -1.23pp · n=1 · 4.8% peak210.26ppbin 0.26pp · n=21 · 100.0% peakbin 0.26pp · n=21 · 100.0% 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=-4.29 · kurt=17.29 · near 6 / mid 12 / far 6 · OLS slope=0.59 intercept=-0.00LEPTOKURTIC — FAT TAILSTHIN UPPER TAILLOWER TAIL NORMAL-3σ-3σ-2σ-2σ-1σ-1σ+0σ+0σ+1σ+1σ+2σ+2σ+3σ+3σΔ=-2.66σsample ↓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=25STRONGLY RIGHT-SKEWED (G₁=1.42)
μ MEAN3.09¢95% CI: [0.80¢, 5.38¢]
σ STD DEV5.85ppσ² = 34.185 · CV = 189.34%
med MEDIAN0.15¢Q₁ 0.05¢ · Q₃ 0.45¢
FIVE-NUMBER SUMMARY · BOX PLOTrange 15.45pp · IQR 0.40pp (1.349σ→7.89pp)
min 0.05¢Q₁ 0.05¢med 0.15¢Q₃ 0.45¢max 15.50¢μ
SKEWNESS · G₁1.418right-skewed
−3−10+1+3
EXCESS KURTOSIS · G₂0.058mesokurtic · normal-like
−30+2+4+6
μ ↔ medianμ > med · right-tailed|μ−med| / σ = 0.50
σ × 1.349 ↔ IQRdiverges from normalratio = 19.72
range ↔ σconcentrated (range < 4σ)range / σ = 2.64
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: INDETERMINATE · weak signal at n=24
ρ(1) AUTOCORR-0.022within white-noise band
ρ(2) AUTOCORR-0.115lag-2 not significant
H · HURST EXPONENT0.990strongly persistent
OLS TREND · t-STAT-4.758significant @ α=0.05
HURST EXPONENT [0, 1]strongly persistent · H = 0.990
H = 0.990STRONGLY 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=1-0.022k=2-0.115k=3-0.074k=4+0.083k=5-0.0030+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|=4.76)
−5 reject−1.960 retain H₀+1.96+5 reject
REGIME CLASSIFICATIONINDETERMINATE · weak signal at n=24from Hurst + ρ(1) joint diagnosis
PREDICTABILITY · score 1.00very high · strong structure|ρ(1)| + 2·|H − 0.5| heuristic
TREND SIGNIFICANCESIGNIFICANT @ 1% (|t|=4.76)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 ID2591987
SLUGhighest-temperature-in-seoul-on-june-20-2026-23c
CATEGORYWeather & Climate
TWO-SIDED PRICINGFAVOURS NO (100¢)
PRIMARY · YES0.05¢implied prob 0.05% · decimal odds 2000.00×
COUNTER · NO99.95¢implied prob 99.95% · decimal odds 1.00×
0.05¢
99.95¢
Σ-SIDES ARBITRAGE TESTPERFECT · ARB-FREE Σ=100.00%
0%50%100% · target110%
Σ = 100.00% · |1 − Σ| = 0.000pp
24H ACTIVITY · LIQUIDITYACTIVE
24H VOLUME61.48k USD 24h
LIQUIDITY16.45k USD
MARKET QUALITYPERFECT · ARB-FREE Σ=100.00%|1−Σ| ≤ 0.5pp ⇒ fair · > 2pp ⇒ inefficient
PRICING SKEWFAVOURS NO (100¢)|primary − counter| = 0.999 · entropy 0.006 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 0.1%NO 100.0%YES p̂0.1%H = 0.006 / 1.00 bits
Probability scale (YES)
0%25%50%
fair75%100%
Implied decimal odds
YES2000.00×(0¢)NO1.00×(100¢)
Kelly bet-size (% of bankroll) K* = 0.00%
K* full
0.00%
½K half
0.00%
¼K quarter
0.00%
Entropy H(p̂) = 0.006 bits (1% 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 · VERY HIGHresolves 2026-06-20 12:00 UTC
0days
02hrs
19min
2.3 hours·θ = 28.643 pp/day
YES →$1.00(P = 0.1%)
NO →$0.00(P = 100.0%)
current: $0.0005 · expected return per side: $1.00 on YES hit · $0.00 on NO hit
0%25%50%75%100%YES $1NO $0NOW+1.2hRESOLVESP projection · σ=5.85% · path funnel to settle at YES=1 or NO=0
Theta progression · θ ∝ σ / √t_remainingθ_now = 28.643 pp/day
now2.33h left
28.643 pp/day×1.00
−25%1.74h left
33.074 pp/day×1.15
−50%1.16h left
40.508 pp/day×1.41
−75%0.58h left
57.286 pp/day×2.00
−90%0.23h left
90.578 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 1.00% · worst -13.85% · typical |Δ| 0.86%BEARISH SESSION -15.45%BEST+1.00%4hWORST-13.85%5hTYPICAL |Δ|0.86%mean absoluteCUMULATIVE-15.45%Σ signed ΔSTREAK▬ 0flat-runASIA · 00-08 UTCμ -2.21% · Σ -15.45%EUROPE · 08-16 UTCμ +0.04% · Σ +0.35%US · 16-24 UTCμ -0.04% · Σ -0.35%CUMULATIVE Δ PATH · final -15.45%+0.00%-15.45%-2.00% · 1h-2.00% · 1h-2.00%1h0.00% · 2h0.00% · 2h·2h1.00% · 3h1.00% · 3h1.00%3h1.00% · 4h1.00% · 4h1.00%4h★ BEST-13.85% · 5h-13.85% · 5h-13.85%5h▼ WORST-1.25% · 6h-1.25% · 6h-1.25%6h-0.35% · 7h-0.35% · 7h-0.35%7h0.00% · 8h0.00% · 8h·8h0.00% · 9h0.00% · 9h·9h0.00% · 10h0.00% · 10h·10h0.05% · 11h0.05% · 11h0.05%11h0.00% · 12h0.00% · 12h·12h0.05% · 13h0.05% · 13h0.05%13h0.00% · 14h0.00% · 14h·14h0.25% · 15h0.25% · 15h0.25%15h-0.10% · 16h-0.10% · 16h-0.10%16h-0.05% · 17h-0.05% · 17h-0.05%17h0.20% · 18h0.20% · 18h0.20%18h-0.15% · 19h-0.15% · 19h-0.15%19h-0.25% · 20h-0.25% · 20h-0.25%20h0.00% · 21h0.00% · 21h·21h0.00% · 22h0.00% · 22h·22h0.00% · 23h0.00% · 23h·23h0.00% · 24h0.00% · 24h·24hTIME PATTERNEurope-led (+0.35%)RUNSup max 2 · down max 3BREADTH25% up · 33% down · 42% flat
6 up bars · 8 down · best 1.00% · worst -13.85% · typical |Δ| 0.856%

§10 · Equity curve & underwater drawdown

Cumulative compounded return + running peak-to-trough
EQUITY & DRAWDOWN ANALYSIS · n=25 barsSEVERE DRAWDOWN -15.25%FINAL-15.25%MAX DD-15.25%RECOVERYONGOING · 24 barsMAX RUN-UP+0.00%UNDERWATER24/25 (96%)STREAK▬ 0EQUITY CURVE · end 0.8475 · peak 1.0000 · range [0.8475, 1.0000]1.00000.8475break-even = 1★ PEAK 1.0000UNDERWATER DRAWDOWN · max -15.25% · severe0%-15.25%▼ TROUGH -15.25%TOP DRAWDOWN PERIODS · 1 total#1 -15.25%bar 2-25 · 24 bars · ONGOINGDD SEVERITYsevere (max -15.25%)RECOVERYongoing · 24 barsTIME UNDER WATER96% of session · 24/25 bars
final equity 0.8475 (-15.25%) · max DD -15.25% · time-under-water 24/25 bars

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

Rolling annualised Sharpe ratio · green positive · red negative
n=19 · +7 / −12 (37% positive) · μ=-7.40 · σ=40.50MIXED EDGELAST -57.77 (-1.24σ vs μ)60.4230.210.00-30.21-60.42μ = -7.40-41.46-41.46-36.48-36.48-36.48-36.48-39.88-39.88-43.47-43.47-47.66-47.66-31.55-31.5560.4260.4260.4260.4256.2656.2633.6733.6719.2719.2739.1839.1814.3114.31-7.83-7.83-35.68-35.68-25.48-25.48-20.28-20.28-57.77-57.77v > 0 · positivev < 0 · negativeμ mean lineμ ± σ bandlatest bar (outlined)
latest -57.768 · range [-57.77, 60.42] · μ -7.395 · positive Sharpe = excess-return-per-risk earned by buying-and-holding through this window
Rolling annualised volatility (%)
n=19 · μ=150.1995 · σ=234.1543 · range [2.4166, 538.2431] · R²=0.592▼ FALLING -98.10%σ EXTREME 155.90%LAST 10.1094538.2431404.2865270.3298136.37322.4166μ = 150.1995max 538.2431min 2.4166dataMA(3)OLS R²=0.59μ lineμ ± σ bandmaxmin
latest 10.11% · range [2.42%, 538.24%] · μ 150.20% · σ̂ scaled to annualised (×√8760)
Rolling lag-1 autocorrelation ρ(1)
n=19 · +3 / −16 (16% positive) · μ=-0.192 · σ=0.238MEAN-REVERSIONLAST 0.281 (+1.99σ vs μ)0.5850.2920.000-0.292-0.585μ = -0.192-0.196-0.196-0.178-0.178-0.197-0.197-0.245-0.2450.0460.0460.2180.218-0.000-0.000-0.333-0.333-0.583-0.583-0.196-0.196-0.585-0.585-0.347-0.347-0.404-0.404-0.509-0.509-0.123-0.123-0.132-0.132-0.107-0.107-0.059-0.0590.2810.281v > 0 · positivev < 0 · negativeμ mean lineμ ± σ bandlatest bar (outlined)
latest 0.281 · |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
2 of 6 REJECT · mixed evidence2 reject·4 pass·α = 0.05
𝒩

Jarque-Bera

REJECT H₀***

H₀: Δp ~ Normal(μ, σ²)

STATISTIC
559.9564
p-VALUE (log scale)
< 0.0001
α
10⁻⁴10⁻³10⁻²10⁻¹1
p < α · rejection zonenon-normal · fat tails or skew present
ρ

Ljung-Box(h=5)

FAIL TO REJECTns

H₀: No serial autocorrelation up to lag 5

STATISTIC
0.7655
p-VALUE (log scale)
0.9770
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
-2.2608
p-VALUE (log scale)
0.1910
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
-0.4877
p-VALUE (log scale)
0.6258
α
10⁻⁴10⁻³10⁻²10⁻¹1
p ≥ α · null retainedsigns appear random (7 runs)
χ

KPSS (μ stationarity)

REJECT H₀*

H₀: p IS level-stationary

STATISTIC
0.5663
p-VALUE (log scale)
0.0267
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
-0.0967
p-VALUE (log scale)
0.9230
α
10⁻⁴10⁻³10⁻²10⁻¹1
p ≥ α · null retainedVR 0.971 ≈ 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=8.28e-4 · top T=4.00h (11.7%) · top-3 cover 32.4%WHITE NOISE · no dominant cyclecumulative energy ↗ (0 bins above 2× noise)1.2e-38.8e-45.8e-42.9e-40.0e+0μ noise floorperiod 24.0 · power 8.80e-4 · 8.9% energyperiod 24.0 · power 8.80e-4 · 8.9% energyperiod 12.0 · power 6.80e-4 · 6.8% energyperiod 12.0 · power 6.80e-4 · 6.8% energyperiod 8.0 · power 6.46e-4 · 6.5% energyperiod 8.0 · power 6.46e-4 · 6.5% energyperiod 6.0 · power 8.12e-4 · 8.2% energyperiod 6.0 · power 8.12e-4 · 8.2% energyperiod 4.8 · power 1.11e-3 · 11.1% energyperiod 4.8 · power 1.11e-3 · 11.1% energyperiod 4.0 · power 1.17e-3 · 11.7% energyperiod 4.0 · power 1.17e-3 · 11.7% energyperiod 3.4 · power 9.43e-4 · 9.5% energyperiod 3.4 · power 9.43e-4 · 9.5% energyperiod 3.0 · power 7.61e-4 · 7.7% energyperiod 3.0 · power 7.61e-4 · 7.7% energyperiod 2.7 · power 5.36e-4 · 5.4% energyperiod 2.7 · power 5.36e-4 · 5.4% energyperiod 2.4 · power 6.56e-4 · 6.6% energyperiod 2.4 · power 6.56e-4 · 6.6% energyperiod 2.2 · power 8.53e-4 · 8.6% energyperiod 2.2 · power 8.53e-4 · 8.6% energyperiod 2.0 · power 8.94e-4 · 9.0% energyperiod 2.0 · power 8.94e-4 · 9.0% energy50% by T=4.0h#1 dominantT=4.00h#2T=4.80h#3T=3.43hT=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 ≈ 4.00h (freq 0.250) · concentrates 11.7% of total energy · Σ|X̂|²/n = 9.935e-3

▸ Depth section using sovereign-store price series (552 bars · effective 1752518 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 0.3 d · σ/bar 0.000pp · expected |Δp| over horizon 0.00ppterminal variance p(1−p) = 0.0005 · n = 552✓ n = 552
μ per bar
+0.000pp
average Δp · drift
σ per bar
0.000pp
one-bar volatility · logit-free
Per-day movedaily
0.00pp
σ × √24
Per-horizon move0d
0.00pp
σ × √6
Terminal variancebinary
0.0005
p(1−p) at resolution
Current pricep
0.1¢
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.

§16 · Tail risk

VaR · ES · max drawdown
VaR₉₅ 0.00pp · ES₉₅ 0.00pp · method parametric · drift-correcteddrift +0.000pp/bar · quantised: yes · median step 0.00pp · unique ratio 0.00✓ n = 552
VaR 95%
0.00pp
1.645·σ (parametric) of Δp
ES 95%
0.00pp
mean of the tail
Max drawdown
0.0pp
peak 0.1¢ → trough 0.1¢
Median step
0.00pp
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
0.1%
= price
Decimal oddsEU
2000.000
total return per $1
AmericanUS
+199900
$100 wins $199900
FractionalUK
1999.00 / 1
profit per $1 risked
Profit per $100stake
+$199900.00
clean dollar framing
-1000-5000+500+1000020406080100you · 0.1%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)
0.006 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.006 bit
Δ +0.000 bit vs market
Surprise · YES−log₂ p
10.97 bit
self-information
Surprise · NO−log₂(1−p)
0.00 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
78218666625089929781343457710368715483349384865384041282723401540049814141070
NO token ID
51550841152041418418959431713128892650220997097233356661059879912760579471077
Snapshot fetched
2026-06-20 09:40:20 UTC
Snapshot age
4.8s
History points
25 CLOB mids
Page rendered
2026-06-20 09:40:25 UTC
Storage policy
no persistence — fetched on every request
SHA-256 attestation
dbd747707a392270ae048492f69eac22112a00bd5b2081c91bb0f8e2f250bb84 · deterministic hash of source snapshot
Open data licence
CC0 / public domain

§∞-2 · Related markets · explore more

HL PREDSpain88.4¢HL PREDEcuador86.3¢HL PREDBelgium67.7¢POLYMARKETWill USA win the 2026 FIFA World Cup?3¢POLYMARKET Iran agrees to end enrichment of uranium by June 30?6¢POLYMARKETWill Egypt win the 2026 FIFA World Cup?0¢HL PERPBTC-USD perpetual$63,616HL PERPHYPE-USD perpetual$70.72HL PERPETH-USD perpetual$1,727.7

Also see: /arb opportunities · RSS feed · more in Weather & Climate

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
—
(best bid + best ask) / 2
Spread
—
(bestAsk − bestBid) / mid
Imbalance (whole book)
-1.000
ask-heavy
Imbalance (top-5)
-1.000
ask-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-highest-temperature-in-seoul-on-june-20-2026-23c/slippage?size=10000&side=buy

SideNotionalAvg fillSlippageWorst fillLevelsStatus
BUY$1.00K————ERR
BUY$10.00K————ERR
BUY$100.00K————ERR
SELL$1.00K————ERR
SELL$10.00K————ERR
SELL$100.00K————ERR

Risk metrics

▸ sovereign store · 552 barsperiods/year ≈ 1.75M
Realized vol (annualised)
0.00%
σ per bar = 0.000000
Mean return (annualised)
0.00%
μ per bar = 0.000000
Sharpe (rf=0)
0.00
annualised; risk-free assumed zero
Max drawdown
0.00%
peak 0.00 → trough 0.00 over 0 bars

/api/asset/pm-highest-temperature-in-seoul-on-june-20-2026-23c/risk · same metrics, JSON