POLYMARKET · PREDICTION MARKET · WEATHER & CLIMATE

Will the highest temperature in Hong Kong be 31°C on June 15?

YES · live
0.1¢
NO · live
99.9¢

▸ Advanced metrics · M2M bundle

polymarket · highest-temperature-in-hong-kong-on-june-15-2026-31c · fresh · feed 0s old
24h sparkline · 60 pts▼ —
realized vol (ann.)
33.31%
max drawdown
91.67%
sharpe
—
ulcer index
69.60%
RMS drawdown
pain index
60.07%
mean drawdown
mod. VaR 95%
0.00%
Cornish-Fisher
martin ratio
—
ret / ulcer
CDaR 95%
91.67%
cond. drawdown
gain/pain
0.18
Σgain / Σ|loss|
sterling
—
ret / CDaR
omega (θ=0)
0.18
upside/downside
roll spread
127.6 bps
implied (price-only)
bars used
297
store
spread
—
24h Δ
—
flow lean
—
carry
flat
signalNEUTRALconfidence 20%
Same bundle via M2M API: /api/m2m/pm-highest-temperature-in-hong-kong-on-june-15-2026-31c/bundle · venue execution: polymarket →
LIVEPOLL0SRCFRESH93ms⏱--:--:-- 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=0.0533 · σ=0.0329 · range [0.0005, 0.1530] · R²=0.004▼ FALLING -96.34%σ EXTREME 61.65%LAST 0.00150.15300.11490.07670.03860.0005μ = 0.0533max 0.1530min 0.0005dataMA(5)OLS R²=0.00μ lineμ ± σ bandmaxminlive endpoint
25 ticks · last 0.15¢
YES / NO split · live
YES 0.1%NO 99.9%NO99.9%99.85¢ · odds 1/1.00
Σ 100.00% · fair
Σ-sides total = 100.00% (tight rounding)
H(p) entropy = 0.016 / 1.00 bits (2%) · informative — one side favoured
YES
0.1%0.1¢666.67×▬ +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=4,965 · μ=206.9 · σ=281.1 · CV=1.36BURSTY · concentratedcumulative energy ↗ · 50% by h=1802855708551,140μ = 2071,14050%h1h5h9h13h17h21#1 peak#2-3> μactivequietμ linecum energy
Σ 4965bp moved · peak 1140bp · n=24 ticks
Live numerics · pulse on poll
LIVE NUMERICS8 metrics·POLL 0
⏱snapshot age
93ms
▲YES mid
0.15¢ (0.15%)
▼NO mid
99.85¢ (99.85%)
ΣΣ sides
100.00%
⚖arb gap
0.000pp
$24h vol $
$25.9k
≋liquidity $
$28.6k
◳history points
25 ticks (live)

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

YES price · CLOB mid
n=25 · μ=0.0533 · σ=0.0329 · range [0.0005, 0.1530] · R²=0.004▼ FALLING -96.34%σ EXTREME 61.65%LAST 0.00150.15300.11490.07670.03860.0005μ = 0.0533max 0.1530min 0.0005dataMA(5)OLS R²=0.00μ lineμ ± σ bandmaxmin
25 YES observations from clob.polymarket.com · last 0.15¢
NO price · CLOB mid
n=25 · μ=0.9483 · σ=0.0344 · range [0.8470, 0.9995] · R²=0.005▲ RISING +7.31%σ NORMAL 3.63%LAST 0.99850.99950.96140.92330.88510.8470μ = 0.9483max 0.9995min 0.8470dataMA(5)OLS R²=0.00μ lineμ ± σ bandmaxmin
25 NO observations from clob.polymarket.com · last 99.85¢

§2 · Distribution of Δp

Histogram of hourly increments
n=24 · 10 bins · μ=-0.0022 · σ=0.0338 · skew=-0.39 (symmetric) · kurt=2.48 (leptokurtic (fat tails))1085301-10.43ppbin -10.43pp · n=1 · 10.0% peakbin -10.43pp · n=1 · 10.0% peak-8.48pp-6.54pp1-4.59ppbin -4.59pp · n=1 · 10.0% peakbin -4.59pp · n=1 · 10.0% peak3-2.65ppbin -2.65pp · n=3 · 30.0% peakbin -2.65pp · n=3 · 30.0% peak10-0.70ppbin -0.70pp · n=10 · 100.0% peakbin -0.70pp · n=10 · 100.0% peak61.24ppbin 1.24pp · n=6 · 60.0% peakbin 1.24pp · n=6 · 60.0% peak13.19ppbin 3.19pp · n=1 · 10.0% peakbin 3.19pp · n=1 · 10.0% peak5.13pp27.08ppbin 7.08pp · n=2 · 20.0% peakbin 7.08pp · n=2 · 20.0% 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=-0.67 · kurt=3.75 · near 9 / mid 14 / far 1 · OLS slope=0.93 intercept=-0.00LEPTOKURTIC — FAT TAILSUPPER TAIL NORMALLOWER 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=25LEPTOKURTIC · FAT TAILS (G₂=2.01)
μ MEAN5.33¢95% CI: [4.04¢, 6.62¢]
σ STD DEV3.29ppσ² = 10.797 · CV = 61.65%
med MEDIAN4.60¢Q₁ 4.10¢ · Q₃ 5.65¢
FIVE-NUMBER SUMMARY · BOX PLOTrange 15.25pp · IQR 1.55pp (1.349σ→4.43pp)
min 0.05¢Q₁ 4.10¢med 4.60¢Q₃ 5.65¢max 15.30¢μ
SKEWNESS · G₁1.259right-skewed
−3−10+1+3
EXCESS KURTOSIS · G₂2.012leptokurtic · fat tails
−30+2+4+6
μ ↔ medianμ > med · right-tailed|μ−med| / σ = 0.22
σ × 1.349 ↔ IQRdiverges from normalratio = 2.86
range ↔ σwide tails (range > 4σ)range / σ = 4.64
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: MEAN-REVERTING · ρ(1) -0.34 + ADF rejected
ρ(1) AUTOCORR-0.335within white-noise band
ρ(2) AUTOCORR-0.064lag-2 not significant
H · HURST EXPONENT0.702strongly persistent
OLS TREND · t-STAT+0.294fails 5% test
HURST EXPONENT [0, 1]strongly persistent · H = 0.702
H = 0.702STRONGLY 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=1-0.335k=2-0.064k=3+0.324k=4-0.377k=5+0.0800+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]NOT SIGNIFICANT (|t|=0.29)
−5 reject−1.960 retain H₀+1.96+5 reject
REGIME CLASSIFICATIONMEAN-REVERTING · ρ(1) -0.34 + ADF rejectedfrom Hurst + ρ(1) joint diagnosis
PREDICTABILITY · score 0.74very high · strong structure|ρ(1)| + 2·|H − 0.5| heuristic
TREND SIGNIFICANCENOT SIGNIFICANT (|t|=0.29)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 ID2528212
SLUGhighest-temperature-in-hong-kong-on-june-15-2026-31c
CATEGORYWeather & Climate
TWO-SIDED PRICINGFAVOURS NO (100¢)
PRIMARY · YES0.15¢implied prob 0.15% · decimal odds 666.67×
COUNTER · NO99.85¢implied prob 99.85% · decimal odds 1.00×
0.15¢
99.85¢
Σ-SIDES ARBITRAGE TESTPERFECT · ARB-FREE Σ=100.00%
0%50%100% · target110%
Σ = 100.00% · |1 − Σ| = 0.000pp
24H ACTIVITY · LIQUIDITYACTIVE
24H VOLUME25.93k USD 24h
LIQUIDITY28.60k USD
MARKET QUALITYPERFECT · ARB-FREE Σ=100.00%|1−Σ| ≤ 0.5pp ⇒ fair · > 2pp ⇒ inefficient
PRICING SKEWFAVOURS NO (100¢)|primary − counter| = 0.997 · entropy 0.016 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 = 0.016 / 1.00 bits
Probability scale (YES)
0%25%50%
fair75%100%
Implied decimal odds
YES666.67×(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) = 0.016 bits (2% 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
04hrs
59min
5.0 hours·θ = 16.098 pp/day
YES →$1.00(P = 0.1%)
NO →$0.00(P = 99.9%)
current: $0.0015 · expected return per side: $1.00 on YES hit · $0.00 on NO hit
0%25%50%75%100%YES $1NO $0NOW+2.5hRESOLVESP projection · σ=3.29% · path funnel to settle at YES=1 or NO=0
Theta progression · θ ∝ σ / √t_remainingθ_now = 16.098 pp/day
now4.99h left
16.098 pp/day×1.00
−25%3.75h left
18.588 pp/day×1.15
−50%2.50h left
22.766 pp/day×1.41
−75%1.25h left
32.195 pp/day×2.00
−90%0.50h left
50.905 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 8.05% · worst -11.40% · typical |Δ| 2.07%MILD BEARISH -3.95%BEST+8.05%17hWORST-11.40%21hTYPICAL |Δ|2.07%mean absoluteCUMULATIVE-3.95%Σ signed ΔSTREAK↗ 1up-runASIA · 00-08 UTCμ +0.12% · Σ +0.85%EUROPE · 08-16 UTCμ +0.01% · Σ +0.05%US · 16-24 UTCμ -0.62% · Σ -4.95%CUMULATIVE Δ PATH · final -3.95%+11.20%-4.05%2.85% · 1h2.85% · 1h2.85%1h-2.65% · 2h-2.65% · 2h-2.65%2h-0.70% · 3h-0.70% · 3h-0.70%3h0.75% · 4h0.75% · 4h0.75%4h-0.45% · 5h-0.45% · 5h-0.45%5h0.90% · 6h0.90% · 6h0.90%6h0.15% · 7h0.15% · 7h0.15%7h-0.35% · 8h-0.35% · 8h-0.35%8h1.05% · 9h1.05% · 9h1.05%9h-0.05% · 10h-0.05% · 10h-0.05%10h-1.20% · 11h-1.20% · 11h-1.20%11h1.55% · 12h1.55% · 12h1.55%12h-1.55% · 13h-1.55% · 13h-1.55%13h0.35% · 14h0.35% · 14h0.35%14h0.25% · 15h0.25% · 15h0.25%15h-0.45% · 16h-0.45% · 16h-0.45%16h8.05% · 17h8.05% · 17h8.05%17h★ BEST-4.15% · 18h-4.15% · 18h-4.15%18h0.55% · 19h0.55% · 19h0.55%19h6.30% · 20h6.30% · 20h6.30%20h-11.40% · 21h-11.40% · 21h-11.40%21h▼ WORST-1.95% · 22h-1.95% · 22h-1.95%22h-1.90% · 23h-1.90% · 23h-1.90%23h0.10% · 24h0.10% · 24h0.10%24hTIME PATTERNAsia-led (+0.85%)RUNSup max 2 · down max 3BREADTH50% up · 50% down
12 up bars · 12 down · best 8.05% · worst -11.40% · typical |Δ| 2.069%

§10 · Equity curve & underwater drawdown

Cumulative compounded return + running peak-to-trough
EQUITY & DRAWDOWN ANALYSIS · n=25 barsSEVERE DRAWDOWN -5.26%FINAL-5.26%MAX DD-14.78%RECOVERYONGOING · 4 barsMAX RUN-UP+11.06%UNDERWATER21/25 (84%)STREAK↗ 1EQUITY CURVE · end 0.9474 · peak 1.1106 · range [0.9464, 1.1106]1.11060.9464break-even = 1★ PEAK 1.1106UNDERWATER DRAWDOWN · max -14.78% · significant0%-14.78%▼ TROUGH -14.78%TOP DRAWDOWN PERIODS · 3 total#1 -14.78%bar 22-25 · 4 bars · ONGOING#2 -4.15%bar 19-20 · 2 bars · recovered#3 -3.33%bar 3-17 · 15 bars · recoveredDD SEVERITYsignificant (max -14.78%)RECOVERYongoing · 4 barsTIME UNDER WATER84% of session · 21/25 bars
final equity 0.9474 (-5.26%) · max DD -14.78% · time-under-water 21/25 bars

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

Rolling annualised Sharpe ratio · green positive · red negative
n=19 · +11 / −8 (58% positive) · μ=5.50 · σ=22.36MIXED EDGELAST -22.48 (-1.25σ vs μ)49.0924.540.00-24.54-49.09μ = 5.505.905.90-24.01-24.017.067.0649.0949.0930.8130.819.389.3818.1718.17-7.04-7.041.911.91-8.99-8.99-14.42-14.4237.3037.309.539.5318.0318.0336.1336.13-2.42-2.42-5.68-5.68-33.74-33.74-22.48-22.48v > 0 · positivev < 0 · negativeμ mean lineμ ± σ bandlatest bar (outlined)
latest -22.478 · range [-33.74, 49.09] · μ 5.502 · positive Sharpe = excess-return-per-risk earned by buying-and-holding through this window
Rolling annualised volatility (%)
n=19 · μ=263.4198 · σ=216.5418 · range [59.2254, 667.9466] · R²=0.736▲ RISING +211.21%σ EXTREME 82.20%LAST 539.1151667.9466515.7663363.5860211.405759.2254μ = 263.4198max 667.9466min 59.2254dataMA(3)OLS R²=0.74μ lineμ ± σ bandmaxmin
latest 539.12% · range [59.23%, 667.95%] · μ 263.42% · σ̂ scaled to annualised (×√8760)
Rolling lag-1 autocorrelation ρ(1)
n=19 · +1 / −18 (5% positive) · μ=-0.440 · σ=0.218MEAN-REVERSIONLAST -0.343 (+0.45σ vs μ)0.7480.3740.000-0.374-0.748μ = -0.440-0.387-0.3870.0920.092-0.572-0.572-0.579-0.579-0.575-0.575-0.102-0.102-0.452-0.452-0.607-0.607-0.638-0.638-0.748-0.748-0.737-0.737-0.111-0.111-0.492-0.492-0.540-0.540-0.444-0.444-0.420-0.420-0.337-0.337-0.372-0.372-0.343-0.343v > 0 · positivev < 0 · negativeμ mean lineμ ± σ bandlatest bar (outlined)
latest -0.343 · |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
1 of 6 REJECT · mixed evidence1 reject·5 pass·α = 0.05
𝒩

Jarque-Bera

REJECT H₀***

H₀: Δp ~ Normal(μ, σ²)

STATISTIC
26.6355
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
10.9250
p-VALUE (log scale)
0.0523
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
-2.7264
p-VALUE (log scale)
0.0730
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
1.6697
p-VALUE (log scale)
0.0950
α
10⁻⁴10⁻³10⁻²10⁻¹1
p ≥ α · null retainedsigns appear random (17 runs)
χ

KPSS (μ stationarity)

FAIL TO REJECTns

H₀: p IS level-stationary

STATISTIC
0.1074
p-VALUE (log scale)
0.5000
α
10⁻⁴10⁻³10⁻²10⁻¹1
p ≥ α · null retainedstationary not rejected (crit 0.463)
χ

Variance ratio q=3

FAIL TO REJECTns

H₀: Δp is a random walk · VR = 1

STATISTIC
-1.4986
p-VALUE (log scale)
0.1340
α
10⁻⁴10⁻³10⁻²10⁻¹1
p ≥ α · null retainedVR 0.544 ≈ 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=1.19e-3 · top T=2.67h (38.6%) · top-3 cover 62.7%1 SIGNIFICANT CYCLEcumulative energy ↗ (1 bin above 2× noise)5.5e-34.1e-32.8e-31.4e-30.0e+0μ noise floor2× noise (significance)period 24.0 · power 3.99e-4 · 2.8% energyperiod 24.0 · power 3.99e-4 · 2.8% energyperiod 12.0 · power 7.97e-4 · 5.6% energyperiod 12.0 · power 7.97e-4 · 5.6% energyperiod 8.0 · power 8.91e-4 · 6.3% energyperiod 8.0 · power 8.91e-4 · 6.3% energyperiod 6.0 · power 5.74e-4 · 4.0% energyperiod 6.0 · power 5.74e-4 · 4.0% energyperiod 4.8 · power 4.20e-4 · 2.9% energyperiod 4.8 · power 4.20e-4 · 2.9% energyperiod 4.0 · power 1.00e-3 · 7.0% energyperiod 4.0 · power 1.00e-3 · 7.0% energyperiod 3.4 · power 9.74e-4 · 6.8% energyperiod 3.4 · power 9.74e-4 · 6.8% energyperiod 3.0 · power 1.34e-3 · 9.4% energyperiod 3.0 · power 1.34e-3 · 9.4% energyperiod 2.7 · power 5.50e-3 · 38.6% energyperiod 2.7 · power 5.50e-3 · 38.6% energyperiod 2.4 · power 2.08e-3 · 14.6% energyperiod 2.4 · power 2.08e-3 · 14.6% energyperiod 2.2 · power 1.66e-4 · 1.2% energyperiod 2.2 · power 1.66e-4 · 1.2% energyperiod 2.0 · power 9.01e-5 · 0.6% energyperiod 2.0 · power 9.01e-5 · 0.6% energy50% by T=2.7h#1 dominantT=2.67h#2T=2.40h#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 ≈ 2.67h (freq 0.375) · concentrates 38.6% of total energy · Σ|X̂|²/n = 1.424e-2

▸ Depth section using sovereign-store price series (297 bars · effective 1753103 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 0.025pp · expected |Δp| over horizon 0.06ppterminal variance p(1−p) = 0.0015 · n = 297✓ n = 297
μ per bar
-0.002pp
average Δp · drift
σ per bar
0.025pp
one-bar volatility · logit-free
Per-day movedaily
0.12pp
σ × √24
Per-horizon move0d
0.06pp
σ × √6
Terminal variancebinary
0.0015
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 0.15pp · unique ratio 0.02✓ n = 297
VaR 95%
0.04pp
1.645·σ (parametric) of Δp
ES 95%
0.05pp
mean of the tail
Max drawdown
91.7pp
peak 0.6¢ → trough 0.1¢
Median step
0.15pp
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
666.667
total return per $1
AmericanUS
+66567
$100 wins $66567
FractionalUK
665.67 / 1
profit per $1 risked
Profit per $100stake
+$66566.67
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)
0.016 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.016 bit
Δ +0.000 bit vs market
Surprise · YES−log₂ p
9.38 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
105717220944315446649882522595793248977045127050018937484197636874723325029484
NO token ID
42604525664682038160814049972468681646585755699511563006963835635523704448148
Snapshot fetched
2026-06-15 07:00:18 UTC
Snapshot age
93ms
History points
25 CLOB mids
Page rendered
2026-06-15 07:00:18 UTC
Storage policy
no persistence — fetched on every request
SHA-256 attestation
d3caab6fcd555e83592aabad130b725ce982a56b590e4ddac52258c672c86299 · deterministic hash of source snapshot
Open data licence
CC0 / public domain

§∞-2 · Related markets · explore more

HL PREDBrazil93.4¢HL PREDSpain91.9¢HL PREDNorway78.9¢POLYMARKETUS x Iran permanent peace deal by June 15, 2026?86¢POLYMARKETUS x Iran permanent peace deal by June 30, 2026?94¢POLYMARKETWill Mexico win the 2026 FIFA World Cup?1¢HL PERPBTC-USD perpetual$65,784.5HL PERPETH-USD perpetual$1,719.95HL PERPHYPE-USD perpetual$65.21

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-hong-kong-on-june-15-2026-31c/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 · 297 barsperiods/year ≈ 1.75M
Realized vol (annualised)
18159.21%
σ per bar = 0.137149
Mean return (annualised)
-821052.79%
μ per bar = -0.004683
Sharpe (rf=0)
-45.21
annualised; risk-free assumed zero
Max drawdown
91.67%
peak 0.01 → trough 0.00 over 100 bars

/api/asset/pm-highest-temperature-in-hong-kong-on-june-15-2026-31c/risk · same metrics, JSON