POLYMARKET · PREDICTION MARKET · WEATHER & CLIMATE

Will the highest temperature in Seoul be 32°C or higher on June 15?

YES · live
0.1¢
NO · live
100.0¢

▸ Advanced metrics · M2M bundle

polymarket · highest-temperature-in-seoul-on-june-15-2026-32corhigher · fresh · feed 0s old
24h sparkline · 60 pts▼ —
realized vol (ann.)
29.58%
max drawdown
94.44%
sharpe
—
ulcer index
79.90%
RMS drawdown
pain index
77.61%
mean drawdown
mod. VaR 95%
0.00%
Cornish-Fisher
martin ratio
—
ret / ulcer
CDaR 95%
94.44%
cond. drawdown
gain/pain
0.11
Σgain / Σ|loss|
sterling
—
ret / CDaR
omega (θ=0)
0.11
upside/downside
roll spread
155.5 bps
implied (price-only)
bars used
545
store
spread
—
24h Δ
—
flow lean
—
carry
flat
signalNEUTRALconfidence 20%
Same bundle via M2M API: /api/m2m/pm-highest-temperature-in-seoul-on-june-15-2026-32corhigher/bundle · venue execution: polymarket →
LIVEPOLL0SRCFRESH20ms⏱--:--:-- 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=0.0073 · σ=0.0033 · range [0.0005, 0.0135] · R²=0.351▼ FALLING -95.24%σ EXTREME 45.22%LAST 0.00050.01350.01030.00700.00370.0005μ = 0.0073max 0.0135min 0.0005dataMA(5)OLS R²=0.35μ 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=630 · μ=26.3 · σ=20.6 · CV=0.78RISING +57% h/hcumulative energy ↗ · 50% by h=15019385675μ = 267550%h1h5h9h13h17h21#1 peak#2-3> μactivequietμ linecum energy
Σ 630bp moved · peak 75bp · n=24 ticks
Live numerics · pulse on poll
LIVE NUMERICS8 metrics·POLL 0
⏱snapshot age
20ms
▲YES mid
0.05¢ (0.05%)
▼NO mid
99.95¢ (99.95%)
ΣΣ sides
100.00%
⚖arb gap
0.000pp
$24h vol $
$27.4k
≋liquidity $
$18.8k
◳history points
25 ticks (live)

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

YES price · CLOB mid
n=25 · μ=0.0073 · σ=0.0033 · range [0.0005, 0.0135] · R²=0.351▼ FALLING -95.24%σ EXTREME 45.22%LAST 0.00050.01350.01030.00700.00370.0005μ = 0.0073max 0.0135min 0.0005dataMA(5)OLS R²=0.35μ lineμ ± σ bandmaxmin
25 YES observations from clob.polymarket.com · last 0.05¢
NO price · CLOB mid
n=25 · μ=0.9927 · σ=0.0033 · range [0.9870, 0.9995] · R²=0.358▲ RISING +1.01%σ LOW 0.33%LAST 0.99950.99950.99640.99320.99010.9870μ = 0.9927max 0.9995min 0.9870dataMA(5)OLS R²=0.36μ 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=-0.0004 · σ=0.0032 · skew=0.71 (right-skewed) · kurt=-0.04 (mesokurtic)543102-0.48ppbin -0.48pp · n=2 · 40.0% peakbin -0.48pp · n=2 · 40.0% peak4-0.36ppbin -0.36pp · n=4 · 80.0% peakbin -0.36pp · n=4 · 80.0% peak5-0.23ppbin -0.23pp · n=5 · 100.0% peakbin -0.23pp · n=5 · 100.0% peak1-0.10ppbin -0.10pp · n=1 · 20.0% peakbin -0.10pp · n=1 · 20.0% peak50.04ppbin 0.04pp · n=5 · 100.0% peakbin 0.04pp · n=5 · 100.0% peak30.17ppbin 0.17pp · n=3 · 60.0% peakbin 0.17pp · n=3 · 60.0% peak20.30ppbin 0.30pp · n=2 · 40.0% peakbin 0.30pp · n=2 · 40.0% peak0.43pp0.56pp20.69ppbin 0.69pp · n=2 · 40.0% peakbin 0.69pp · n=2 · 40.0% 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=0.75 · kurt=0.18 · near 20 / mid 4 / far 0 · OLS slope=1.00 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=25APPROXIMATELY NORMAL · WELL-BEHAVED
μ MEAN0.73¢95% CI: [0.60¢, 0.86¢]
σ STD DEV0.33ppσ² = 0.110 · CV = 45.22%
med MEDIAN0.75¢Q₁ 0.65¢ · Q₃ 1.00¢
FIVE-NUMBER SUMMARY · BOX PLOTrange 1.30pp · IQR 0.35pp (1.349σ→0.45pp)
min 0.05¢Q₁ 0.65¢med 0.75¢Q₃ 1.00¢max 1.35¢μ
SKEWNESS · G₁-0.476approximately symmetric
−3−10+1+3
EXCESS KURTOSIS · G₂-0.463mesokurtic · normal-like
−30+2+4+6
μ ↔ median≈ equal · symmetric|μ−med| / σ = 0.05
σ × 1.349 ↔ IQRdiverges from normalratio = 1.28
range ↔ σconcentrated (range < 4σ)range / σ = 3.92
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) -0.52 + ADF rejected
ρ(1) AUTOCORR-0.520negative · reversal
ρ(2) AUTOCORR+0.270lag-2 not significant
H · HURST EXPONENT0.784strongly persistent
OLS TREND · t-STAT-3.530significant @ α=0.05
HURST EXPONENT [0, 1]strongly persistent · H = 0.784
H = 0.784STRONGLY PERSISTENT
0
anti-persistent0.45
mean-reverting0.5
random walk0.55
persistent1
strongly trending
AUTOCORRELATION FUNCTION · ρ(k) for k=1..51 SIGNIFICANT LAG · k=1
k=1 ★-0.520k=2+0.270k=3-0.374k=4+0.165k=5-0.1090+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|=3.53)
−5 reject−1.960 retain H₀+1.96+5 reject
REGIME CLASSIFICATIONMEAN-REVERTING · ρ(1) -0.52 + 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|=3.53)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 ID2528148
SLUGhighest-temperature-in-seoul-on-june-15-2026-32corhigher
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 VOLUME27.38k USD 24h
LIQUIDITY18.80k 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 2026-06-15 12:00 UTC
0days
03hrs
55min
3.9 hours·θ = 1.626 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+2.0hRESOLVESP projection · σ=0.33% · path funnel to settle at YES=1 or NO=0
Theta progression · θ ∝ σ / √t_remainingθ_now = 1.626 pp/day
now3.93h left
1.626 pp/day×1.00
−25%2.95h left
1.877 pp/day×1.15
−50%1.97h left
2.299 pp/day×1.41
−75%0.98h left
3.252 pp/day×2.00
−90%0.39h left
5.142 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 0.75% · worst -0.55% · typical |Δ| 0.26%BEARISH SESSION -1.00%BEST+0.75%16hWORST-0.55%19hTYPICAL |Δ|0.26%mean absoluteCUMULATIVE-1.00%Σ signed ΔSTREAK▬ 0flat-runASIA · 00-08 UTCμ -0.05% · Σ -0.35%EUROPE · 08-16 UTCμ -0.04% · Σ -0.30%US · 16-24 UTCμ -0.04% · Σ -0.35%CUMULATIVE Δ PATH · final -1.00%+0.30%-1.00%-0.20% · 1h-0.20% · 1h-0.20%1h0.05% · 2h0.05% · 2h0.05%2h-0.25% · 3h-0.25% · 3h-0.25%3h0.35% · 4h0.35% · 4h0.35%4h0.00% · 5h0.00% · 5h·5h-0.10% · 6h-0.10% · 6h-0.10%6h-0.20% · 7h-0.20% · 7h-0.20%7h0.15% · 8h0.15% · 8h0.15%8h-0.20% · 9h-0.20% · 9h-0.20%9h0.00% · 10h0.00% · 10h·10h0.70% · 11h0.70% · 11h0.70%11h-0.25% · 12h-0.25% · 12h-0.25%12h-0.40% · 13h-0.40% · 13h-0.40%13h0.05% · 14h0.05% · 14h0.05%14h-0.35% · 15h-0.35% · 15h-0.35%15h0.75% · 16h0.75% · 16h0.75%16h★ BEST-0.30% · 17h-0.30% · 17h-0.30%17h0.15% · 18h0.15% · 18h0.15%18h-0.55% · 19h-0.55% · 19h-0.55%19h▼ WORST0.25% · 20h0.25% · 20h0.25%20h-0.50% · 21h-0.50% · 21h-0.50%21h0.20% · 22h0.20% · 22h0.20%22h-0.35% · 23h-0.35% · 23h-0.35%23h0.00% · 24h0.00% · 24h·24hTIME PATTERNuniform across sessionsRUNSup max 1 · down max 2BREADTH38% up · 50% down · 13% flat
9 up bars · 12 down · best 0.75% · worst -0.55% · typical |Δ| 0.263%

§10 · Equity curve & underwater drawdown

Cumulative compounded return + running peak-to-trough
EQUITY & DRAWDOWN ANALYSIS · n=25 barsLOSS · SHALLOW DD (-1.01%)FINAL-1.01%MAX DD-1.30%RECOVERYONGOING · 13 barsMAX RUN-UP+0.30%UNDERWATER23/25 (92%)STREAK▬ 0EQUITY CURVE · end 0.9899 · peak 1.0030 · range [0.9899, 1.0030]1.00300.9899break-even = 1★ PEAK 1.0030UNDERWATER DRAWDOWN · max -1.30% · moderate0%-1.30%▼ TROUGH -1.30%TOP DRAWDOWN PERIODS · 2 total#1 -1.30%bar 13-25 · 13 bars · ONGOING#2 -0.40%bar 2-11 · 10 bars · recoveredDD SEVERITYmoderate (max -1.30%)RECOVERYongoing · 13 barsTIME UNDER WATER92% of session · 23/25 bars
final equity 0.9899 (-1.01%) · 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 · +3 / −14 (16% positive) · μ=-9.69 · σ=16.79UNPROFITABLE STRATEGYLAST -41.85 (-1.92σ vs μ)41.8520.920.00-20.92-41.85μ = -9.69-10.82-10.82-10.82-10.82-3.44-3.440.000.00-40.23-40.2316.0016.008.668.660.000.00-4.02-4.02-9.59-9.5914.9614.96-17.82-17.82-3.56-3.56-8.34-8.34-1.62-1.62-6.16-6.16-31.87-31.87-33.51-33.51-41.85-41.85v > 0 · positivev < 0 · negativeμ mean lineμ ± σ bandlatest bar (outlined)
latest -41.845 · range [-41.85, 16.00] · μ -9.685 · positive Sharpe = excess-return-per-risk earned by buying-and-holding through this window
Rolling annualised volatility (%)
n=19 · μ=33.7338 · σ=10.3624 · range [12.7016, 48.7832] · R²=0.497▲ RISING +63.79%σ EXTREME 30.72%LAST 33.145948.783239.762830.742421.722012.7016μ = 33.7338max 48.7832min 12.7016dataMA(3)OLS R²=0.50μ lineμ ± σ bandmaxmin
latest 33.15% · range [12.70%, 48.78%] · μ 33.73% · σ̂ scaled to annualised (×√8760)
Rolling lag-1 autocorrelation ρ(1)
n=19 · +0 / −19 (0% positive) · μ=-0.444 · σ=0.264MEAN-REVERSIONLAST -0.831 (-1.46σ vs μ)0.8840.4420.000-0.442-0.884μ = -0.444-0.457-0.457-0.345-0.345-0.378-0.378-0.170-0.170-0.693-0.693-0.050-0.050-0.398-0.398-0.135-0.135-0.125-0.125-0.133-0.133-0.223-0.223-0.446-0.446-0.592-0.592-0.571-0.571-0.647-0.647-0.492-0.492-0.871-0.871-0.884-0.884-0.831-0.831v > 0 · positivev < 0 · negativeμ mean lineμ ± σ bandlatest bar (outlined)
latest -0.831 · |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
2.8551
p-VALUE (log scale)
0.2399
α
10⁻⁴10⁻³10⁻²10⁻¹1
p ≥ α · null retainednormality not rejected
ρ

Ljung-Box(h=5)

REJECT H₀*

H₀: No serial autocorrelation up to lag 5

STATISTIC
14.7968
p-VALUE (log scale)
0.0114
α
10⁻⁴10⁻³10⁻²10⁻¹1
p < α · rejection zoneserial dependence detected
Ψ

Dickey-Fuller (τ_μ)

FAIL TO REJECTns

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

STATISTIC
-2.4750
p-VALUE (log scale)
0.1280
α
10⁻⁴10⁻³10⁻²10⁻¹1
p ≥ α · null retainedrandom-walk behaviour (crit ≈ -2.86)
±

Wald-Wolfowitz runs

REJECT H₀***

H₀: Sign sequence of Δ is random

STATISTIC
3.5301
p-VALUE (log scale)
0.0004
α
10⁻⁴10⁻³10⁻²10⁻¹1
p < α · rejection zonenon-random sign pattern (19 runs)
χ

KPSS (μ stationarity)

REJECT H₀*

H₀: p IS level-stationary

STATISTIC
0.5322
p-VALUE (log scale)
0.0344
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
-1.5854
p-VALUE (log scale)
0.1129
α
10⁻⁴10⁻³10⁻²10⁻¹1
p ≥ α · null retainedVR 0.518 ≈ 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=1.38e-5 · top T=2.00h (44.2%) · top-3 cover 68.0%STRONG CYCLE @ T≈2.0cumulative energy ↗ (1 bin above 2× noise)7.3e-55.5e-53.7e-51.8e-50.0e+0μ noise floor2× noise (significance)period 24.0 · power 2.90e-6 · 1.7% energyperiod 24.0 · power 2.90e-6 · 1.7% energyperiod 12.0 · power 7.48e-7 · 0.5% energyperiod 12.0 · power 7.48e-7 · 0.5% energyperiod 8.0 · power 2.45e-6 · 1.5% energyperiod 8.0 · power 2.45e-6 · 1.5% energyperiod 6.0 · power 1.60e-5 · 9.6% energyperiod 6.0 · power 1.60e-5 · 9.6% energyperiod 4.8 · power 5.93e-6 · 3.6% energyperiod 4.8 · power 5.93e-6 · 3.6% energyperiod 4.0 · power 4.88e-6 · 2.9% energyperiod 4.0 · power 4.88e-6 · 2.9% energyperiod 3.4 · power 4.26e-6 · 2.6% energyperiod 3.4 · power 4.26e-6 · 2.6% energyperiod 3.0 · power 1.39e-5 · 8.4% energyperiod 3.0 · power 1.39e-5 · 8.4% energyperiod 2.7 · power 5.75e-6 · 3.5% energyperiod 2.7 · power 5.75e-6 · 3.5% energyperiod 2.4 · power 1.24e-5 · 7.5% energyperiod 2.4 · power 1.24e-5 · 7.5% energyperiod 2.2 · power 2.35e-5 · 14.1% energyperiod 2.2 · power 2.35e-5 · 14.1% energyperiod 2.0 · power 7.35e-5 · 44.2% energyperiod 2.0 · power 7.35e-5 · 44.2% energy50% by T=2.2h#1 dominantT=2.00h#2T=2.18h#3T=6.00hT=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 ≈ 2.00h (freq 0.500) · concentrates 44.2% of total energy · Σ|X̂|²/n = 1.662e-4

▸ Depth section using sovereign-store price series (545 bars · effective 1753200 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 0.022pp · expected |Δp| over horizon 0.05ppterminal variance p(1−p) = 0.0005 · n = 545✓ n = 545
μ per bar
-0.002pp
average Δp · drift
σ per bar
0.022pp
one-bar volatility · logit-free
Per-day movedaily
0.11pp
σ × √24
Per-horizon move0d
0.05pp
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 0.04pp · ES₉₅ 0.05pp · method parametric · drift-correcteddrift -0.002pp/bar · quantised: yes · median step 0.05pp · unique ratio 0.01✓ n = 545
VaR 95%
0.04pp
1.645·σ (parametric) of Δp
ES 95%
0.05pp
mean of the tail
Max drawdown
94.4pp
peak 0.9¢ → trough 0.1¢
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
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
61291155725275639315023176925063418356396053733072260063213997474214598011599
NO token ID
58030565595336059399937606961046045048096108455904393487292527294959932924545
Snapshot fetched
2026-06-15 08:04:05 UTC
Snapshot age
20ms
History points
25 CLOB mids
Page rendered
2026-06-15 08:04:05 UTC
Storage policy
no persistence — fetched on every request
SHA-256 attestation
d0a6b9da0b3f46a2da8e765761c453883c298ee8f93298a1cc02b0f5090f082a · deterministic hash of source snapshot
Open data licence
CC0 / public domain

§∞-2 · Related markets · explore more

HL PREDSpain92.0¢HL PREDBrazil88.0¢HL PREDNorway78.9¢POLYMARKETUS x Iran permanent peace deal by June 15, 2026?87¢POLYMARKETUS x Iran permanent peace deal by June 30, 2026?94¢POLYMARKETWill Germany win the 2026 FIFA World Cup?6¢HL PERPBTC-USD perpetual$65,734HL PERPETH-USD perpetual$1,719.4HL PERPHYPE-USD perpetual$65.47

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-15-2026-32corhigher/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 · 545 barsperiods/year ≈ 1.75M
Realized vol (annualised)
9213.55%
σ per bar = 0.069584
Mean return (annualised)
-931507.31%
μ per bar = -0.005313
Sharpe (rf=0)
-101.10
annualised; risk-free assumed zero
Max drawdown
94.44%
peak 0.01 → trough 0.00 over 419 bars

/api/asset/pm-highest-temperature-in-seoul-on-june-15-2026-32corhigher/risk · same metrics, JSON