POLYMARKET · PREDICTION MARKET · WEATHER & CLIMATE

Will the highest temperature in Hong Kong be 28°C on June 15?

YES · live
0.1¢
NO · live
100.0¢

▸ Advanced metrics · M2M bundle

polymarket · highest-temperature-in-hong-kong-on-june-15-2026-28c · fresh · feed 0s old
24h sparkline · 60 pts▼ —
realized vol (ann.)
11.82%
max drawdown
75.00%
sharpe
—
ulcer index
60.31%
RMS drawdown
pain index
48.50%
mean drawdown
mod. VaR 95%
0.00%
Cornish-Fisher
martin ratio
—
ret / ulcer
CDaR 95%
75.00%
cond. drawdown
gain/pain
0.00
Σgain / Σ|loss|
sterling
—
ret / CDaR
omega (θ=0)
0.00
upside/downside
roll spread
103.8 bps
implied (price-only)
bars used
283
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-15-2026-28c/bundle · venue execution: polymarket →
LIVEPOLL0SRCFRESH43ms⏱--:--:-- 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=0.1688 · σ=0.1277 · range [0.0005, 0.3200] · R²=0.686▼ FALLING -99.81%σ EXTREME 75.68%LAST 0.00050.32000.24010.16030.08040.0005μ = 0.1688max 0.3200min 0.0005dataMA(5)OLS R²=0.69μ 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=5,605 · μ=233.5 · σ=405.3 · CV=1.74BURSTY · concentratedcumulative energy ↗ · 50% by h=1204889751,4631,950μ = 2341,95050%h1h5h9h13h17h21#1 peak#2-3> μactivequietμ linecum energy
Σ 5605bp moved · peak 1950bp · n=24 ticks
Live numerics · pulse on poll
LIVE NUMERICS8 metrics·POLL 0
⏱snapshot age
43ms
▲YES mid
0.05¢ (0.05%)
▼NO mid
99.95¢ (99.95%)
ΣΣ sides
100.00%
⚖arb gap
0.000pp
$24h vol $
$23.8k
≋liquidity $
$16.0k
◳history points
25 ticks (live)

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

YES price · CLOB mid
n=25 · μ=0.1688 · σ=0.1277 · range [0.0005, 0.3200] · R²=0.686▼ FALLING -99.81%σ EXTREME 75.68%LAST 0.00050.32000.24010.16030.08040.0005μ = 0.1688max 0.3200min 0.0005dataMA(5)OLS R²=0.69μ lineμ ± σ bandmaxmin
25 YES observations from clob.polymarket.com · last 0.05¢
NO price · CLOB mid
n=25 · μ=0.8310 · σ=0.1280 · range [0.6750, 0.9995] · R²=0.684▲ RISING +35.99%σ EXTREME 15.40%LAST 0.99950.99950.91840.83730.75610.6750μ = 0.8310max 0.9995min 0.6750dataMA(5)OLS R²=0.68μ 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=-0.0122 · σ=0.0421 · skew=-2.63 (left-skewed) · kurt=8.44 (leptokurtic (fat tails))13107301-18.22ppbin -18.22pp · n=1 · 7.7% peakbin -18.22pp · n=1 · 7.7% peak-15.68pp-13.13pp-10.57pp-8.03pp2-5.47ppbin -5.47pp · n=2 · 15.4% peakbin -5.47pp · n=2 · 15.4% peak3-2.92ppbin -2.92pp · n=3 · 23.1% peakbin -2.92pp · n=3 · 23.1% peak13-0.38ppbin -0.38pp · n=13 · 100.0% peakbin -0.38pp · n=13 · 100.0% peak42.18ppbin 2.18pp · n=4 · 30.8% peakbin 2.18pp · n=4 · 30.8% peak14.73ppbin 4.73pp · n=1 · 7.7% peakbin 4.73pp · n=1 · 7.7% 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=-2.72 · kurt=9.34 · near 6 / mid 17 / far 1 · OLS slope=0.84 intercept=-0.00LEPTOKURTIC — FAT TAILSUPPER TAIL NORMALLOWER TAIL NORMAL-3σ-3σ-2σ-2σ-1σ-1σ+0σ+0σ+1σ+1σ+2σ+2σ+3σ+3σΔ=-2.08σsample ↓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=-1.72)
μ MEAN16.88¢95% CI: [11.87¢, 21.88¢]
σ STD DEV12.77ppσ² = 163.145 · CV = 75.68%
med MEDIAN24.50¢Q₁ 0.20¢ · Q₃ 26.00¢
FIVE-NUMBER SUMMARY · BOX PLOTrange 31.95pp · IQR 25.80pp (1.349σ→17.23pp)
min 0.05¢Q₁ 0.20¢med 24.50¢Q₃ 26.00¢max 32.00¢μ
SKEWNESS · G₁-0.469approximately symmetric
−3−10+1+3
EXCESS KURTOSIS · G₂-1.718platykurtic · thin tails
−30+2+4+6
μ ↔ medianμ < med · left-tailed|μ−med| / σ = 0.60
σ × 1.349 ↔ IQRdiverges from normalratio = 0.67
range ↔ σconcentrated (range < 4σ)range / σ = 2.50
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+0.012within white-noise band
ρ(2) AUTOCORR+0.010lag-2 not significant
H · HURST EXPONENT0.834strongly persistent
OLS TREND · t-STAT-7.083significant @ α=0.05
HURST EXPONENT [0, 1]strongly persistent · H = 0.834
H = 0.834STRONGLY 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+0.012k=2+0.010k=3-0.003k=4-0.019k=5-0.0530+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|=7.08)
−5 reject−1.960 retain H₀+1.96+5 reject
REGIME CLASSIFICATIONINDETERMINATE · weak signal at n=24from Hurst + ρ(1) joint diagnosis
PREDICTABILITY · score 0.68very high · strong structure|ρ(1)| + 2·|H − 0.5| heuristic
TREND SIGNIFICANCESIGNIFICANT @ 1% (|t|=7.08)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 ID2528209
SLUGhighest-temperature-in-hong-kong-on-june-15-2026-28c
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 VOLUME23.84k USD 24h
LIQUIDITY16.00k 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
04hrs
58min
5.0 hours·θ = 62.574 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+2.5hRESOLVESP projection · σ=12.77% · path funnel to settle at YES=1 or NO=0
Theta progression · θ ∝ σ / √t_remainingθ_now = 62.574 pp/day
now4.98h left
62.574 pp/day×1.00
−25%3.73h left
72.254 pp/day×1.15
−50%2.49h left
88.493 pp/day×1.41
−75%1.24h left
125.148 pp/day×2.00
−90%0.50h left
197.876 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 6.00% · worst -19.50% · typical |Δ| 2.34%BEARISH SESSION -26.45%BEST+6.00%9hWORST-19.50%16hTYPICAL |Δ|2.34%mean absoluteCUMULATIVE-26.45%Σ signed ΔSTREAK▬ 0flat-runASIA · 00-08 UTCμ +0.71% · Σ +5.00%EUROPE · 08-16 UTCμ -1.13% · Σ -9.00%US · 16-24 UTCμ -2.81% · Σ -22.45%CUMULATIVE Δ PATH · final -26.45%+5.50%-26.45%-2.00% · 1h-2.00% · 1h-2.00%1h-1.00% · 2h-1.00% · 2h-1.00%2h1.00% · 3h1.00% · 3h1.00%3h0.00% · 4h0.00% · 4h·4h1.00% · 5h1.00% · 5h1.00%5h3.00% · 6h3.00% · 6h3.00%6h3.00% · 7h3.00% · 7h3.00%7h-5.50% · 8h-5.50% · 8h-5.50%8h6.00% · 9h6.00% · 9h6.00%9h★ BEST-4.50% · 10h-4.50% · 10h-4.50%10h-0.50% · 11h-0.50% · 11h-0.50%11h-1.50% · 12h-1.50% · 12h-1.50%12h-1.50% · 13h-1.50% · 13h-1.50%13h0.50% · 14h0.50% · 14h0.50%14h-2.00% · 15h-2.00% · 15h-2.00%15h-19.50% · 16h-19.50% · 16h-19.50%16h▼ WORST-2.80% · 17h-2.80% · 17h-2.80%17h-0.15% · 18h-0.15% · 18h-0.15%18h0.20% · 19h0.20% · 19h0.20%19h-0.15% · 20h-0.15% · 20h-0.15%20h0.10% · 21h0.10% · 21h0.10%21h-0.15% · 22h-0.15% · 22h-0.15%22h0.00% · 23h0.00% · 23h·23h0.00% · 24h0.00% · 24h·24hTIME PATTERNAsia-led (+5.00%)RUNSup max 3 · down max 4BREADTH33% up · 54% down · 13% flat
8 up bars · 13 down · best 6.00% · worst -19.50% · typical |Δ| 2.335%

§10 · Equity curve & underwater drawdown

Cumulative compounded return + running peak-to-trough
EQUITY & DRAWDOWN ANALYSIS · n=25 barsSEVERE DRAWDOWN -25.39%FINAL-25.39%MAX DD-29.06%RECOVERYONGOING · 15 barsMAX RUN-UP+5.18%UNDERWATER21/25 (84%)STREAK▬ 0EQUITY CURVE · end 0.7461 · peak 1.0518 · range [0.7461, 1.0518]1.05180.7461break-even = 1★ PEAK 1.0518UNDERWATER DRAWDOWN · max -29.06% · severe0%-29.06%▼ TROUGH -29.06%TOP DRAWDOWN PERIODS · 3 total#1 -29.06%bar 11-25 · 15 bars · ONGOING#2 -5.50%bar 9-9 · 1 bars · recovered#3 -2.98%bar 2-6 · 5 bars · recoveredDD SEVERITYsevere (max -29.06%)RECOVERYongoing · 15 barsTIME UNDER WATER84% of session · 21/25 bars
final equity 0.7461 (-25.39%) · max DD -29.06% · time-under-water 21/25 bars

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

Rolling annualised Sharpe ratio · green positive · red negative
n=19 · +6 / −12 (32% positive) · μ=-18.28 · σ=37.70UNPROFITABLE STRATEGYLAST 0.00 (+0.48σ vs μ)87.9143.950.00-43.95-87.91μ = -18.2817.8217.8268.1668.1612.4312.4330.0330.0310.2610.265.125.12-10.65-10.65-28.91-28.91-6.71-6.71-87.91-87.91-50.25-50.25-56.15-56.15-52.43-52.43-47.96-47.96-49.73-49.73-44.52-44.52-40.34-40.34-15.51-15.510.000.00v > 0 · positivev < 0 · negativeμ mean lineμ ± σ bandlatest bar (outlined)
latest 0.000 · range [-87.91, 68.16] · μ -18.276 · positive Sharpe = excess-return-per-risk earned by buying-and-holding through this window
Rolling annualised volatility (%)
n=19 · μ=395.9338 · σ=255.6328 · range [12.9012, 731.3627] · R²=0.013▼ FALLING -92.13%σ EXTREME 64.56%LAST 12.9012731.3627551.7473372.1319192.516612.9012μ = 395.9338max 731.3627min 12.9012dataMA(3)OLS R²=0.01μ lineμ ± σ bandmaxmin
latest 12.90% · range [12.90%, 731.36%] · μ 395.93% · σ̂ scaled to annualised (×√8760)
Rolling lag-1 autocorrelation ρ(1)
n=19 · +5 / −14 (26% positive) · μ=-0.273 · σ=0.354MEAN-REVERSIONLAST -0.632 (-1.01σ vs μ)0.7970.3980.000-0.398-0.797μ = -0.2730.2320.2320.2970.297-0.154-0.154-0.540-0.540-0.654-0.654-0.623-0.623-0.788-0.788-0.695-0.695-0.403-0.403-0.264-0.2640.0180.018-0.095-0.095-0.093-0.093-0.065-0.065-0.045-0.0450.0990.0990.0140.014-0.797-0.797-0.632-0.632v > 0 · positivev < 0 · negativeμ mean lineμ ± σ bandlatest bar (outlined)
latest -0.632 · |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
175.9186
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
0.1122
p-VALUE (log scale)
0.9993
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
-0.5030
p-VALUE (log scale)
0.8853
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
0.0454
p-VALUE (log scale)
0.9638
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
0.7247
p-VALUE (log scale)
0.0113
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
0.3767
p-VALUE (log scale)
0.7064
α
10⁻⁴10⁻³10⁻²10⁻¹1
p ≥ α · null retainedVR 1.115 ≈ 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=2.17e-3 · top T=2.00h (15.8%) · top-3 cover 40.6%WHITE NOISE · no dominant cyclecumulative energy ↗ (0 bins above 2× noise)4.1e-33.1e-32.1e-31.0e-30.0e+0μ noise floorperiod 24.0 · power 3.47e-3 · 13.3% energyperiod 24.0 · power 3.47e-3 · 13.3% energyperiod 12.0 · power 1.59e-3 · 6.1% energyperiod 12.0 · power 1.59e-3 · 6.1% energyperiod 8.0 · power 2.29e-3 · 8.8% energyperiod 8.0 · power 2.29e-3 · 8.8% energyperiod 6.0 · power 1.68e-3 · 6.4% energyperiod 6.0 · power 1.68e-3 · 6.4% energyperiod 4.8 · power 2.16e-3 · 8.3% energyperiod 4.8 · power 2.16e-3 · 8.3% energyperiod 4.0 · power 2.47e-3 · 9.5% energyperiod 4.0 · power 2.47e-3 · 9.5% energyperiod 3.4 · power 4.72e-4 · 1.8% energyperiod 3.4 · power 4.72e-4 · 1.8% energyperiod 3.0 · power 2.99e-3 · 11.5% energyperiod 3.0 · power 2.99e-3 · 11.5% energyperiod 2.7 · power 2.95e-3 · 11.3% energyperiod 2.7 · power 2.95e-3 · 11.3% energyperiod 2.4 · power 4.75e-4 · 1.8% energyperiod 2.4 · power 4.75e-4 · 1.8% energyperiod 2.2 · power 1.38e-3 · 5.3% energyperiod 2.2 · power 1.38e-3 · 5.3% energyperiod 2.0 · power 4.12e-3 · 15.8% energyperiod 2.0 · power 4.12e-3 · 15.8% energy50% by T=4.0h#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 15.8% of total energy · Σ|X̂|²/n = 2.604e-2

▸ Depth section using sovereign-store price series (283 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 0.009pp · expected |Δp| over horizon 0.02ppterminal variance p(1−p) = 0.0005 · n = 283✓ n = 283
μ per bar
-0.001pp
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
0.0005
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 0.02pp · ES₉₅ 0.02pp · method parametric · drift-correcteddrift -0.001pp/bar · quantised: yes · median step 0.15pp · unique ratio 0.01✓ n = 283
VaR 95%
0.02pp
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
0.15pp
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
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
75410262400948150987653618618440992181462561390288852882209629749510316901925
NO token ID
36146131100819522755789472593983900891932888008996125559137513853842490191400
Snapshot fetched
2026-06-15 07:01:19 UTC
Snapshot age
43ms
History points
25 CLOB mids
Page rendered
2026-06-15 07:01:19 UTC
Storage policy
no persistence — fetched on every request
SHA-256 attestation
7e604c29561822f88d90dc44f3fefb74b58923ba3a5f73749b0ba4a279daeb42 · 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?93¢POLYMARKETWill Mexico win the 2026 FIFA World Cup?1¢HL PERPBTC-USD perpetual$65,714.5HL PERPETH-USD perpetual$1,717.25HL PERPHYPE-USD perpetual$64.87

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-15-2026-28c/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 · 283 barsperiods/year ≈ 1.75M
Realized vol (annualised)
10930.36%
σ per bar = 0.082553
Mean return (annualised)
-861814.28%
μ per bar = -0.004916
Sharpe (rf=0)
-78.85
annualised; risk-free assumed zero
Max drawdown
75.00%
peak 0.00 → trough 0.00 over 100 bars

/api/asset/pm-highest-temperature-in-hong-kong-on-june-15-2026-28c/risk · same metrics, JSON