POLYMARKET · PREDICTION MARKET · WEATHER & CLIMATE

Will the highest temperature in Shanghai be 30°C on June 20?

YES · live
0.1¢
NO · live
99.9¢

▸ Advanced metrics · M2M bundle

polymarket · highest-temperature-in-shanghai-on-june-20-2026-30c · fresh · feed 7s old
24h sparkline · 60 pts▼ —
realized vol (ann.)
11.97%
max drawdown
75.00%
sharpe
—
ulcer index
60.45%
RMS drawdown
pain index
57.22%
mean drawdown
mod. VaR 95%
0.00%
Cornish-Fisher
martin ratio
—
ret / ulcer
CDaR 95%
75.00%
cond. drawdown
gain/pain
0.80
Σgain / Σ|loss|
sterling
—
ret / CDaR
omega (θ=0)
0.80
upside/downside
roll spread
25.5 bps
implied (price-only)
bars used
918
store
spread
—
24h Δ
—
flow lean
—
carry
flat
signalNEUTRALconfidence 20%
Same bundle via M2M API: /api/m2m/pm-highest-temperature-in-shanghai-on-june-20-2026-30c/bundle · venue execution: polymarket →
LIVEPOLL0SRCFRESH7.1s⏱--:--:-- 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
99.9¢
YES price · live 24h
n=25 · μ=0.1948 · σ=0.1434 · range [0.0005, 0.3800] · R²=0.746▼ FALLING -99.64%σ EXTREME 73.62%LAST 0.00100.38000.28510.19030.09540.0005μ = 0.1948max 0.3800min 0.0005dataMA(5)OLS R²=0.75μ lineμ ± σ bandmaxminlive endpoint
25 ticks · last 0.10¢
YES / NO split · live
YES 0.1%NO 99.9%NO99.9%99.90¢ · odds 1/1.00
Σ 100.00% · fair
Σ-sides total = 100.00% (tight rounding)
H(p) entropy = 0.011 / 1.00 bits (1%) · informative — one side favoured
YES
0.1%0.1¢1000.00×▬ +0.00pp
NO
99.9%99.9¢1.00×▬ +0.00pp
Σ 100.00% · arb gap 0.00pp
Per-tick activity · |Δp| in basis points · live
n=24 · Σ=7,640 · μ=318.3 · σ=395.6 · CV=1.24BURSTYcumulative energy ↗ · 50% by h=1303136259381,250μ = 3181,25050%h1h5h9h13h17h21#1 peak#2-3> μactivequietμ linecum energy
Σ 7640bp moved · peak 1250bp · n=24 ticks
Live numerics · pulse on poll
LIVE NUMERICS8 metrics·POLL 0
⏱snapshot age
7.1s
▲YES mid
0.10¢ (0.10%)
▼NO mid
99.90¢ (99.90%)
ΣΣ sides
100.00%
⚖arb gap
0.000pp
$24h vol $
$18.7k
≋liquidity $
$3.5k
◳history points
25 ticks (live)

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

YES price · CLOB mid
n=25 · μ=0.1948 · σ=0.1434 · range [0.0005, 0.3800] · R²=0.746▼ FALLING -99.64%σ EXTREME 73.62%LAST 0.00100.38000.28510.19030.09540.0005μ = 0.1948max 0.3800min 0.0005dataMA(5)OLS R²=0.75μ lineμ ± σ bandmaxmin
25 YES observations from clob.polymarket.com · last 0.10¢
NO price · CLOB mid
n=25 · μ=0.8052 · σ=0.1434 · range [0.6200, 0.9995] · R²=0.746▲ RISING +37.79%σ EXTREME 17.81%LAST 0.99900.99950.90460.80970.71490.6200μ = 0.8052max 0.9995min 0.6200dataMA(5)OLS R²=0.75μ lineμ ± σ bandmaxmin
25 NO observations from clob.polymarket.com · last 99.90¢

§2 · Distribution of Δp

Histogram of hourly increments
n=24 · 10 bins · μ=-0.0139 · σ=0.0469 · skew=-0.68 (left-skewed) · kurt=0.54 (mesokurtic)653203-11.45ppbin -11.45pp · n=3 · 50.0% peakbin -11.45pp · n=3 · 50.0% peak-9.35pp-7.25pp-5.15pp6-3.05ppbin -3.05pp · n=6 · 100.0% peakbin -3.05pp · n=6 · 100.0% peak6-0.95ppbin -0.95pp · n=6 · 100.0% peakbin -0.95pp · n=6 · 100.0% peak61.15ppbin 1.15pp · n=6 · 100.0% peakbin 1.15pp · n=6 · 100.0% peak3.25pp25.35ppbin 5.35pp · n=2 · 33.3% peakbin 5.35pp · n=2 · 33.3% peak17.45ppbin 7.45pp · n=1 · 16.7% peakbin 7.45pp · n=1 · 16.7% 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=-0.92 · kurt=1.00 · near 14 / mid 10 / far 0 · OLS slope=0.95 intercept=-0.00APPROXIMATELY NORMALUPPER TAIL NORMALMILDLY HEAVY LOWER-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=-1.62)
μ MEAN19.48¢95% CI: [13.86¢, 25.10¢]
σ STD DEV14.34ppσ² = 205.589 · CV = 73.62%
med MEDIAN27.00¢Q₁ 0.75¢ · Q₃ 30.50¢
FIVE-NUMBER SUMMARY · BOX PLOTrange 37.95pp · IQR 29.75pp (1.349σ→19.34pp)
min 0.05¢Q₁ 0.75¢med 27.00¢Q₃ 30.50¢max 38.00¢μ
SKEWNESS · G₁-0.422approximately symmetric
−3−10+1+3
EXCESS KURTOSIS · G₂-1.624platykurtic · thin tails
−30+2+4+6
μ ↔ medianμ < med · left-tailed|μ−med| / σ = 0.52
σ × 1.349 ↔ IQRdiverges from normalratio = 0.65
range ↔ σconcentrated (range < 4σ)range / σ = 2.65
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-0.040within white-noise band
ρ(2) AUTOCORR-0.026lag-2 not significant
H · HURST EXPONENT0.778strongly persistent
OLS TREND · t-STAT-8.215significant @ α=0.05
HURST EXPONENT [0, 1]strongly persistent · H = 0.778
H = 0.778STRONGLY 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=1-0.040k=2-0.026k=3+0.029k=4+0.045k=5-0.1990+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|=8.22)
−5 reject−1.960 retain H₀+1.96+5 reject
REGIME CLASSIFICATIONINDETERMINATE · weak signal at n=24from Hurst + ρ(1) joint diagnosis
PREDICTABILITY · score 0.60high · clear structure|ρ(1)| + 2·|H − 0.5| heuristic
TREND SIGNIFICANCESIGNIFICANT @ 1% (|t|=8.22)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 ID2592067
SLUGhighest-temperature-in-shanghai-on-june-20-2026-30c
CATEGORYWeather & Climate
TWO-SIDED PRICINGFAVOURS NO (100¢)
PRIMARY · YES0.10¢implied prob 0.10% · decimal odds 1000.00×
COUNTER · NO99.90¢implied prob 99.90% · decimal odds 1.00×
0.10¢
99.90¢
Σ-SIDES ARBITRAGE TESTPERFECT · ARB-FREE Σ=100.00%
0%50%100% · target110%
Σ = 100.00% · |1 − Σ| = 0.000pp
24H ACTIVITY · LIQUIDITYACTIVE
24H VOLUME18.66k USD 24h
LIQUIDITY3.51k USD
MARKET QUALITYPERFECT · ARB-FREE Σ=100.00%|1−Σ| ≤ 0.5pp ⇒ fair · > 2pp ⇒ inefficient
PRICING SKEWFAVOURS NO (100¢)|primary − counter| = 0.998 · entropy 0.011 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 99.9%YES p̂0.1%H = 0.011 / 1.00 bits
Probability scale (YES)
0%25%50%
fair75%100%
Implied decimal odds
YES1000.00×(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) = 0.011 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.

§9 · Hourly return heatmap

24-hour signed Δp grid · green = up · red = down
HOURLY RETURN HEATMAP · n=24 bars · best 8.50% · worst -12.50% · typical |Δ| 3.18%MILD BEARISH -27.40%BEST+8.50%14hWORST-12.50%16hTYPICAL |Δ|3.18%mean absoluteCUMULATIVE-27.40%Σ signed ΔSTREAK▬ 0flat-runASIA · 00-08 UTCμ +1.21% · Σ +8.50%EUROPE · 08-16 UTCμ -1.37% · Σ -11.00%US · 16-24 UTCμ -3.11% · Σ -24.90%CUMULATIVE Δ PATH · final -27.40%+10.50%-27.45%0.00% · 1h0.00% · 1h·1h1.00% · 2h1.00% · 2h1.00%2h2.00% · 3h2.00% · 3h2.00%3h2.00% · 4h2.00% · 4h2.00%4h1.00% · 5h1.00% · 5h1.00%5h4.50% · 6h4.50% · 6h4.50%6h-2.00% · 7h-2.00% · 7h-2.00%7h-2.50% · 8h-2.50% · 8h-2.50%8h-3.00% · 9h-3.00% · 9h-3.00%9h-3.00% · 10h-3.00% · 10h-3.00%10h-2.00% · 11h-2.00% · 11h-2.00%11h5.00% · 12h5.00% · 12h5.00%12h-12.00% · 13h-12.00% · 13h-12.00%13h8.50% · 14h8.50% · 14h8.50%14h★ BEST-2.00% · 15h-2.00% · 15h-2.00%15h-12.50% · 16h-12.50% · 16h-12.50%16h▼ WORST-11.75% · 17h-11.75% · 17h-11.75%17h0.30% · 18h0.30% · 18h0.30%18h-1.00% · 19h-1.00% · 19h-1.00%19h0.15% · 20h0.15% · 20h0.15%20h-0.15% · 21h-0.15% · 21h-0.15%21h0.05% · 22h0.05% · 22h0.05%22h0.00% · 23h0.00% · 23h·23h0.00% · 24h0.00% · 24h·24hTIME PATTERNAsia-led (+8.50%)RUNSup max 5 · down max 5BREADTH42% up · 46% down · 13% flat
10 up bars · 11 down · best 8.50% · worst -12.50% · typical |Δ| 3.183%

§10 · Equity curve & underwater drawdown

Cumulative compounded return + running peak-to-trough
EQUITY & DRAWDOWN ANALYSIS · n=25 barsSEVERE DRAWDOWN -26.35%FINAL-26.35%MAX DD-33.63%RECOVERYONGOING · 18 barsMAX RUN-UP+10.91%UNDERWATER18/25 (72%)STREAK▬ 0EQUITY CURVE · end 0.7365 · peak 1.1091 · range [0.7361, 1.1091]1.10910.7361break-even = 1★ PEAK 1.1091UNDERWATER DRAWDOWN · max -33.63% · severe0%-33.63%▼ TROUGH -33.63%TOP DRAWDOWN PERIODS · 1 total#1 -33.63%bar 8-25 · 18 bars · ONGOINGDD SEVERITYsevere (max -33.63%)RECOVERYongoing · 18 barsTIME UNDER WATER72% of session · 18/25 bars
final equity 0.7365 (-26.35%) · max DD -33.63% · time-under-water 18/25 bars

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

Rolling annualised Sharpe ratio · green positive · red negative
n=19 · +3 / −15 (16% positive) · μ=-19.65 · σ=43.73UNPROFITABLE STRATEGYLAST -34.99 (-0.35σ vs μ)106.2853.140.00-53.14-106.28μ = -19.65106.28106.2862.9162.9129.3429.340.000.00-25.90-25.90-43.14-43.14-37.81-37.81-50.48-50.48-14.16-14.16-12.06-12.06-27.27-27.27-41.28-41.28-53.40-53.40-36.26-36.26-69.73-69.73-62.86-62.86-40.59-40.59-21.95-21.95-34.99-34.99v > 0 · positivev < 0 · negativeμ mean lineμ ± σ bandlatest bar (outlined)
latest -34.986 · range [-69.73, 106.28] · μ -19.649 · positive Sharpe = excess-return-per-risk earned by buying-and-holding through this window
Rolling annualised volatility (%)
n=19 · μ=444.7318 · σ=267.8483 · range [39.6445, 875.4686] · R²=0.061▼ FALLING -72.51%σ EXTREME 60.23%LAST 39.6445875.4686666.5126457.5566248.600639.6445μ = 444.7318max 875.4686min 39.6445dataMA(3)OLS R²=0.06μ lineμ ± σ bandmaxmin
latest 39.64% · range [39.64%, 875.47%] · μ 444.73% · σ̂ scaled to annualised (×√8760)
Rolling lag-1 autocorrelation ρ(1)
n=19 · +8 / −11 (42% positive) · μ=-0.143 · σ=0.344CLOSE TO MARTINGALELAST -0.220 (-0.22σ vs μ)0.7280.3640.000-0.364-0.728μ = -0.143-0.089-0.089-0.539-0.5390.0350.0350.2250.2250.3050.3050.0650.0650.0590.059-0.443-0.443-0.668-0.668-0.728-0.728-0.466-0.466-0.225-0.225-0.167-0.1670.1960.1960.2030.2030.3880.388-0.086-0.086-0.557-0.557-0.220-0.220v > 0 · positivev < 0 · negativeμ mean lineμ ± σ bandlatest bar (outlined)
latest -0.220 · |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
6.2180
p-VALUE (log scale)
0.0446
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
1.4568
p-VALUE (log scale)
0.9174
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
-0.3618
p-VALUE (log scale)
0.9106
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
-0.2137
p-VALUE (log scale)
0.8308
α
10⁻⁴10⁻³10⁻²10⁻¹1
p ≥ α · null retainedsigns appear random (11 runs)
χ

KPSS (μ stationarity)

REJECT H₀**

H₀: p IS level-stationary

STATISTIC
0.7701
p-VALUE (log scale)
0.0084
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
0.0153
p-VALUE (log scale)
0.9878
α
10⁻⁴10⁻³10⁻²10⁻¹1
p ≥ α · null retainedVR 1.005 ≈ 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=2.59e-3 · top T=2.00h (15.9%) · top-3 cover 42.6%WHITE NOISE · no dominant cyclecumulative energy ↗ (0 bins above 2× noise)4.9e-33.7e-32.5e-31.2e-30.0e+0μ noise floorperiod 24.0 · power 4.34e-3 · 14.0% energyperiod 24.0 · power 4.34e-3 · 14.0% energyperiod 12.0 · power 4.07e-4 · 1.3% energyperiod 12.0 · power 4.07e-4 · 1.3% energyperiod 8.0 · power 3.96e-3 · 12.7% energyperiod 8.0 · power 3.96e-3 · 12.7% energyperiod 6.0 · power 1.07e-3 · 3.5% energyperiod 6.0 · power 1.07e-3 · 3.5% energyperiod 4.8 · power 1.58e-3 · 5.1% energyperiod 4.8 · power 1.58e-3 · 5.1% energyperiod 4.0 · power 3.36e-3 · 10.8% energyperiod 4.0 · power 3.36e-3 · 10.8% energyperiod 3.4 · power 2.34e-3 · 7.5% energyperiod 3.4 · power 2.34e-3 · 7.5% energyperiod 3.0 · power 3.97e-3 · 12.8% energyperiod 3.0 · power 3.97e-3 · 12.8% energyperiod 2.7 · power 2.13e-3 · 6.9% energyperiod 2.7 · power 2.13e-3 · 6.9% energyperiod 2.4 · power 7.98e-4 · 2.6% energyperiod 2.4 · power 7.98e-4 · 2.6% energyperiod 2.2 · power 2.18e-3 · 7.0% energyperiod 2.2 · power 2.18e-3 · 7.0% energyperiod 2.0 · power 4.93e-3 · 15.9% energyperiod 2.0 · power 4.93e-3 · 15.9% energy50% by T=3.4h#1 dominantT=2.00h#2T=24.00h#3T=3.00hT=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 15.9% of total energy · Σ|X̂|²/n = 3.106e-2

▸ Depth section using sovereign-store price series (918 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 0.3 d · σ/bar 0.009pp · expected |Δp| over horizon 0.02ppterminal variance p(1−p) = 0.0010 · n = 918✓ n = 918
μ per bar
-0.000pp
average Δp · drift
σ per bar
0.009pp
one-bar volatility · logit-free
Per-day movedaily
0.04pp
σ × √24
Per-horizon move0d
0.02pp
σ × √6
Terminal variancebinary
0.0010
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 0.01pp · ES₉₅ 0.02pp · method parametric · drift-correcteddrift -0.000pp/bar · quantised: yes · median step 0.05pp · unique ratio 0.00✓ n = 918
VaR 95%
0.01pp
1.645·σ (parametric) of Δp
ES 95%
0.02pp
mean of the tail
Max drawdown
75.0pp
peak 0.2¢ → 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
1000.000
total return per $1
AmericanUS
+99900
$100 wins $99900
FractionalUK
999.00 / 1
profit per $1 risked
Profit per $100stake
+$99900.00
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)
0.011 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.011 bit
Δ +0.000 bit vs market
Surprise · YES−log₂ p
9.97 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
57264051022917498162806354182646332350429118484852248311073778994097008886460
NO token ID
97667712712275806753562426844033111101402156731080675904455995335217267631582
Snapshot fetched
2026-06-20 12:08:50 UTC
Snapshot age
7.1s
History points
25 CLOB mids
Page rendered
2026-06-20 12:08:57 UTC
Storage policy
no persistence — fetched on every request
SHA-256 attestation
e430f22f631427ae19cc3e465c93b8af216dde88093340ba9689cc6b1ad4dcbe · deterministic hash of source snapshot
Open data licence
CC0 / public domain

§∞-2 · Related markets · explore more

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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-shanghai-on-june-20-2026-30c/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 · 918 barsperiods/year ≈ 1.75M
Realized vol (annualised)
12943.22%
σ per bar = 0.097763
Mean return (annualised)
-132492.44%
μ per bar = -0.000756
Sharpe (rf=0)
-10.24
annualised; risk-free assumed zero
Max drawdown
75.00%
peak 0.00 → trough 0.00 over 83 bars

/api/asset/pm-highest-temperature-in-shanghai-on-june-20-2026-30c/risk · same metrics, JSON