POLYMARKET · PREDICTION MARKET · WEATHER & CLIMATE

Will the highest temperature in Chengdu be 27°C on June 20?

YES · live
0.1¢
NO · live
100.0¢

▸ Advanced metrics · M2M bundle

polymarket · highest-temperature-in-chengdu-on-june-20-2026-27c · fresh · feed 7s old
24h sparkline · 60 pts▼ —
realized vol (ann.)
7.46%
max drawdown
66.67%
sharpe
—
ulcer index
63.21%
RMS drawdown
pain index
60.45%
mean drawdown
mod. VaR 95%
0.00%
Cornish-Fisher
martin ratio
—
ret / ulcer
CDaR 95%
66.67%
cond. drawdown
gain/pain
0.67
Σgain / Σ|loss|
sterling
—
ret / CDaR
omega (θ=0)
0.67
upside/downside
roll spread
32.6 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-chengdu-on-june-20-2026-27c/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
100.0¢
YES price · live 24h
n=25 · μ=0.0834 · σ=0.1348 · range [0.0005, 0.3450] · R²=0.576▼ FALLING -99.80%σ EXTREME 161.63%LAST 0.00050.34500.25890.17270.08660.0005μ = 0.0834max 0.3450min 0.0005dataMA(5)OLS R²=0.58μ 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=4,935 · μ=205.6 · σ=505.2 · CV=2.46BURSTY · concentratedcumulative energy ↗ · 50% by h=705611,1231,6842,245μ = 2062,24550%h1h5h9h13h17h21#1 peak#2-3> μactivequietμ linecum energy
Σ 4935bp moved · peak 2245bp · n=24 ticks
Live numerics · pulse on poll
LIVE NUMERICS8 metrics·POLL 0
⏱snapshot age
7.1s
▲YES mid
0.05¢ (0.05%)
▼NO mid
99.95¢ (99.95%)
ΣΣ sides
100.00%
⚖arb gap
0.000pp
$24h vol $
$60.8k
≋liquidity $
$6.7k
◳history points
25 ticks (live)

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

YES price · CLOB mid
n=25 · μ=0.0834 · σ=0.1348 · range [0.0005, 0.3450] · R²=0.576▼ FALLING -99.80%σ EXTREME 161.63%LAST 0.00050.34500.25890.17270.08660.0005μ = 0.0834max 0.3450min 0.0005dataMA(5)OLS R²=0.58μ lineμ ± σ bandmaxmin
25 YES observations from clob.polymarket.com · last 0.05¢
NO price · CLOB mid
n=25 · μ=0.9166 · σ=0.1348 · range [0.6550, 0.9995] · R²=0.576▲ RISING +32.38%σ HIGH 14.71%LAST 0.99950.99950.91340.82730.74110.6550μ = 0.9166max 0.9995min 0.6550dataMA(5)OLS R²=0.58μ 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=-0.0107 · σ=0.0512 · skew=-2.99 (left-skewed) · kurt=8.20 (leptokurtic (fat tails))17139401-21.13ppbin -21.13pp · n=1 · 5.9% peakbin -21.13pp · n=1 · 5.9% peak-18.48pp-15.84pp1-13.19ppbin -13.19pp · n=1 · 5.9% peakbin -13.19pp · n=1 · 5.9% peak-10.55pp-7.90pp-5.26pp1-2.61ppbin -2.61pp · n=1 · 5.9% peakbin -2.61pp · n=1 · 5.9% peak170.03ppbin 0.03pp · n=17 · 100.0% peakbin 0.03pp · n=17 · 100.0% peak42.68ppbin 2.68pp · n=4 · 23.5% peakbin 2.68pp · n=4 · 23.5% 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=-3.12 · kurt=9.36 · near 6 / mid 13 / far 5 · OLS slope=0.72 intercept=-0.00LEPTOKURTIC — FAT TAILSTHIN UPPER TAILLOWER TAIL NORMAL-3σ-3σ-2σ-2σ-1σ-1σ+0σ+0σ+1σ+1σ+2σ+2σ+3σ+3σΔ=-2.04σsample ↓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=1.02)
μ MEAN8.34¢95% CI: [3.06¢, 13.63¢]
σ STD DEV13.48ppσ² = 181.791 · CV = 161.63%
med MEDIAN0.15¢Q₁ 0.05¢ · Q₃ 22.50¢
FIVE-NUMBER SUMMARY · BOX PLOTrange 34.45pp · IQR 22.45pp (1.349σ→18.19pp)
min 0.05¢Q₁ 0.05¢med 0.15¢Q₃ 22.50¢max 34.50¢μ
SKEWNESS · G₁1.024right-skewed
−3−10+1+3
EXCESS KURTOSIS · G₂-0.845mesokurtic · normal-like
−30+2+4+6
μ ↔ medianμ > med · right-tailed|μ−med| / σ = 0.61
σ × 1.349 ↔ IQRconsistent with normalratio = 0.81
range ↔ σconcentrated (range < 4σ)range / σ = 2.56
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: TRENDING · variance ratio > 1
ρ(1) AUTOCORR+0.394within white-noise band
ρ(2) AUTOCORR-0.060lag-2 not significant
H · HURST EXPONENT0.609persistent
OLS TREND · t-STAT-5.591significant @ α=0.05
HURST EXPONENT [0, 1]persistent · H = 0.609
H = 0.609PERSISTENT
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+0.394k=2-0.060k=3-0.168k=4-0.254k=5-0.2210+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|=5.59)
−5 reject−1.960 retain H₀+1.96+5 reject
REGIME CLASSIFICATIONTRENDING · variance ratio > 1from Hurst + ρ(1) joint diagnosis
PREDICTABILITY · score 0.61very high · strong structure|ρ(1)| + 2·|H − 0.5| heuristic
TREND SIGNIFICANCESIGNIFICANT @ 1% (|t|=5.59)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 ID2592164
SLUGhighest-temperature-in-chengdu-on-june-20-2026-27c
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 VOLUME60.81k USD 24h
LIQUIDITY6.70k 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 = 66.053 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=13.48% · path funnel to settle at YES=1 or NO=0
Theta progression · θ ∝ σ / √t_remainingθ_now = 66.053 pp/day
now2.33h left
66.053 pp/day×1.00
−25%1.74h left
76.271 pp/day×1.15
−50%1.16h left
93.413 pp/day×1.41
−75%0.58h left
132.106 pp/day×2.00
−90%0.23h left
208.877 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 4.00% · worst -22.45% · typical |Δ| 2.06%BEARISH SESSION -24.45%BEST+4.00%2hWORST-22.45%7hTYPICAL |Δ|2.06%mean absoluteCUMULATIVE-24.45%Σ signed ΔSTREAK↘ 1down-runASIA · 00-08 UTCμ -3.49% · Σ -24.45%EUROPE · 08-16 UTCμ +0.03% · Σ +0.25%US · 16-24 UTCμ -0.03% · Σ -0.20%CUMULATIVE Δ PATH · final -24.45%+10.00%-24.45%1.00% · 1h1.00% · 1h1.00%1h4.00% · 2h4.00% · 2h4.00%2h★ BEST3.50% · 3h3.50% · 3h3.50%3h1.50% · 4h1.50% · 4h1.50%4h0.00% · 5h0.00% · 5h·5h-12.00% · 6h-12.00% · 6h-12.00%6h-22.45% · 7h-22.45% · 7h-22.45%7h▼ WORST0.00% · 8h0.00% · 8h·8h0.00% · 9h0.00% · 9h·9h0.00% · 10h0.00% · 10h·10h0.10% · 11h0.10% · 11h0.10%11h0.15% · 12h0.15% · 12h0.15%12h0.00% · 13h0.00% · 13h·13h2.10% · 14h2.10% · 14h2.10%14h-2.10% · 15h-2.10% · 15h-2.10%15h0.00% · 16h0.00% · 16h·16h-0.20% · 17h-0.20% · 17h-0.20%17h-0.05% · 18h-0.05% · 18h-0.05%18h0.00% · 19h0.00% · 19h·19h0.05% · 20h0.05% · 20h0.05%20h0.00% · 21h0.00% · 21h·21h-0.05% · 22h-0.05% · 22h-0.05%22h0.05% · 23h0.05% · 23h0.05%23h-0.05% · 24h-0.05% · 24h-0.05%24hTIME PATTERNEurope-led (+0.25%)RUNSup max 4 · down max 2BREADTH38% up · 29% down · 33% flat
9 up bars · 7 down · best 4.00% · worst -22.45% · typical |Δ| 2.056%

§10 · Equity curve & underwater drawdown

Cumulative compounded return + running peak-to-trough
EQUITY & DRAWDOWN ANALYSIS · n=25 barsSEVERE DRAWDOWN -24.73%FINAL-24.73%MAX DD-31.79%RECOVERYONGOING · 19 barsMAX RUN-UP+10.35%UNDERWATER19/25 (76%)STREAK↘ 1EQUITY CURVE · end 0.7527 · peak 1.1035 · range [0.7527, 1.1035]1.10350.7527break-even = 1★ PEAK 1.1035UNDERWATER DRAWDOWN · max -31.79% · severe0%-31.79%▼ TROUGH -31.79%TOP DRAWDOWN PERIODS · 1 total#1 -31.79%bar 7-25 · 19 bars · ONGOINGDD SEVERITYsevere (max -31.79%)RECOVERYongoing · 19 barsTIME UNDER WATER76% of session · 19/25 bars
final equity 0.7527 (-24.73%) · max DD -31.79% · time-under-water 19/25 bars

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

Rolling annualised Sharpe ratio · green positive · red negative
n=19 · +4 / −13 (21% positive) · μ=-16.47 · σ=32.85UNPROFITABLE STRATEGYLAST 0.00 (+0.50σ vs μ)58.6829.340.00-29.34-58.68μ = -16.47-5.28-5.28-37.16-37.16-45.14-45.14-53.05-53.05-56.63-56.63-56.40-56.40-37.70-37.7058.6858.6843.6843.682.932.932.932.93-0.59-0.59-2.93-2.93-2.93-2.93-42.44-42.44-35.63-35.63-45.28-45.280.000.000.000.00v > 0 · positivev < 0 · negativeμ mean lineμ ± σ bandlatest bar (outlined)
latest 0.000 · range [-56.63, 58.68] · μ -16.470 · positive Sharpe = excess-return-per-risk earned by buying-and-holding through this window
Rolling annualised volatility (%)
n=19 · μ=361.1056 · σ=405.9919 · range [4.1857, 999.8036] · R²=0.681▼ FALLING -99.24%σ EXTREME 112.43%LAST 4.1857999.8036750.8991501.9946253.09024.1857μ = 361.1056max 999.8036min 4.1857dataMA(3)OLS R²=0.68μ lineμ ± σ bandmaxmin
latest 4.19% · range [4.19%, 999.80%] · μ 361.11% · σ̂ scaled to annualised (×√8760)
Rolling lag-1 autocorrelation ρ(1)
n=19 · +9 / −10 (47% positive) · μ=-0.097 · σ=0.314CLOSE TO MARTINGALELAST -0.500 (-1.28σ vs μ)0.5080.2540.000-0.254-0.508μ = -0.0970.1500.1500.4220.4220.1710.1710.1070.1070.0860.0860.2390.239-0.032-0.0320.1290.129-0.067-0.067-0.508-0.508-0.498-0.498-0.497-0.497-0.498-0.498-0.508-0.508-0.065-0.0650.0580.0580.2230.223-0.250-0.250-0.500-0.500v > 0 · positivev < 0 · negativeμ mean lineμ ± σ bandlatest bar (outlined)
latest -0.500 · |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
187.1135
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
8.7621
p-VALUE (log scale)
0.1178
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
-1.2420
p-VALUE (log scale)
0.6537
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
-0.4606
p-VALUE (log scale)
0.6451
α
10⁻⁴10⁻³10⁻²10⁻¹1
p ≥ α · null retainedsigns appear random (8 runs)
χ

KPSS (μ stationarity)

REJECT H₀*

H₀: p IS level-stationary

STATISTIC
0.6141
p-VALUE (log scale)
0.0214
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
1.9411
p-VALUE (log scale)
0.0522
α
10⁻⁴10⁻³10⁻²10⁻¹1
p ≥ α · null retainedVR 1.591 ≈ 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=2.81e-3 · top T=8.00h (20.1%) · top-3 cover 52.2%2 SIGNIFICANT CYCLEScumulative energy ↗ (2 bins above 2× noise)6.8e-35.1e-33.4e-31.7e-30.0e+0μ noise floor2× noise (significance)period 24.0 · power 3.73e-3 · 11.1% energyperiod 24.0 · power 3.73e-3 · 11.1% energyperiod 12.0 · power 6.70e-3 · 19.9% energyperiod 12.0 · power 6.70e-3 · 19.9% energyperiod 8.0 · power 6.76e-3 · 20.1% energyperiod 8.0 · power 6.76e-3 · 20.1% energyperiod 6.0 · power 4.11e-3 · 12.2% energyperiod 6.0 · power 4.11e-3 · 12.2% energyperiod 4.8 · power 3.05e-3 · 9.1% energyperiod 4.8 · power 3.05e-3 · 9.1% energyperiod 4.0 · power 2.21e-3 · 6.5% energyperiod 4.0 · power 2.21e-3 · 6.5% energyperiod 3.4 · power 1.59e-3 · 4.7% energyperiod 3.4 · power 1.59e-3 · 4.7% energyperiod 3.0 · power 2.18e-3 · 6.5% energyperiod 3.0 · power 2.18e-3 · 6.5% energyperiod 2.7 · power 1.46e-3 · 4.3% energyperiod 2.7 · power 1.46e-3 · 4.3% energyperiod 2.4 · power 3.30e-4 · 1.0% energyperiod 2.4 · power 3.30e-4 · 1.0% energyperiod 2.2 · power 5.42e-4 · 1.6% energyperiod 2.2 · power 5.42e-4 · 1.6% energyperiod 2.0 · power 1.03e-3 · 3.1% energyperiod 2.0 · power 1.03e-3 · 3.1% energy50% by T=8.0h#1 dominantT=8.00h#2T=12.00h#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 ≈ 8.00h (freq 0.125) · concentrates 20.1% of total energy · Σ|X̂|²/n = 3.369e-2

▸ 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 0.006pp · expected |Δp| over horizon 0.01ppterminal variance p(1−p) = 0.0005 · n = 552✓ n = 552
μ per bar
-0.000pp
average Δp · drift
σ per bar
0.006pp
one-bar volatility · logit-free
Per-day movedaily
0.03pp
σ × √24
Per-horizon move0d
0.01pp
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 0.01pp · ES₉₅ 0.01pp · method parametric · drift-correcteddrift -0.000pp/bar · quantised: yes · median step 0.05pp · unique ratio 0.01✓ n = 552
VaR 95%
0.01pp
1.645·σ (parametric) of Δp
ES 95%
0.01pp
mean of the tail
Max drawdown
66.7pp
peak 0.1¢ → 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
94902710527910875646824188808687324619426292443502463262061946860352105150958
NO token ID
44677270317284316617373003431565855324808371952473738389615205819932559321147
Snapshot fetched
2026-06-20 09:40:20 UTC
Snapshot age
7.1s
History points
25 CLOB mids
Page rendered
2026-06-20 09:40:27 UTC
Storage policy
no persistence — fetched on every request
SHA-256 attestation
e9b37e5d224b7c15c80fa76b63f0869ed86d23aef97cfa7261534b8d4f647370 · 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$70.71HL PERPETH-USD perpetual$1,727.6

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-chengdu-on-june-20-2026-27c/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)
8619.00%
σ per bar = 0.065107
Mean return (annualised)
-220463.38%
μ per bar = -0.001258
Sharpe (rf=0)
-25.58
annualised; risk-free assumed zero
Max drawdown
66.67%
peak 0.00 → trough 0.00 over 5 bars

/api/asset/pm-highest-temperature-in-chengdu-on-june-20-2026-27c/risk · same metrics, JSON