POLYMARKET · PREDICTION MARKET · WEATHER & CLIMATE

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

YES · live
0.1¢
NO · live
100.0¢

▸ Advanced metrics · M2M bundle

polymarket · highest-temperature-in-hong-kong-on-june-20-2026-30c · fresh · feed 14s old
24h sparkline · 60 pts▼ —
realized vol (ann.)
0.00%
max drawdown
0.00%
sharpe
—
ulcer index
0.00%
RMS drawdown
pain index
0.00%
mean drawdown
mod. VaR 95%
0.00%
Cornish-Fisher
martin ratio
—
ret / ulcer
CDaR 95%
0.00%
cond. drawdown
gain/pain
—
Σgain / Σ|loss|
sterling
—
ret / CDaR
omega (θ=0)
1.00
upside/downside
roll spread
0.0 bps
implied (price-only)
bars used
1048
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-20-2026-30c/bundle · venue execution: polymarket →
LIVEPOLL0SRCWARMING14.1s⏱--:--:-- UTC8NEXT8.0sUP0s--:--HIST0/30
▶ STREAMING·HYPERLIQUID·POLYMARKET·0 POLLS·SRC WARMING·UPTIME 0s·NEXT POLL 8.0s·CC0 OPEN DATA·HYPO.MARKETS·▶ STREAMING·HYPERLIQUID·POLYMARKET·0 POLLS·SRC WARMING·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=0.0363 · σ=0.0676 · range [0.0005, 0.2875] · R²=0.003▼ FALLING -98.75%σ EXTREME 186.23%LAST 0.00050.28750.21570.14400.07220.0005μ = 0.0363max 0.2875min 0.0005dataMA(5)OLS R²=0.00μ 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=6,585 · μ=274.4 · σ=667.2 · CV=2.43BURSTY · concentratedcumulative energy ↗ · 50% by h=1607181,4352,1532,870μ = 2742,87050%h1h5h9h13h17h21#1 peak#2-3> μactivequietμ linecum energy
Σ 6585bp moved · peak 2870bp · n=24 ticks
Live numerics · pulse on poll
LIVE NUMERICS8 metrics·POLL 0
⏱snapshot age
14.1s
▲YES mid
0.05¢ (0.05%)
▼NO mid
99.95¢ (99.95%)
ΣΣ sides
100.00%
⚖arb gap
0.000pp
$24h vol $
$34.3k
≋liquidity $
$9.6k
◳history points
25 ticks (live)

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

YES price · CLOB mid
n=25 · μ=0.0363 · σ=0.0676 · range [0.0005, 0.2875] · R²=0.003▼ FALLING -98.75%σ EXTREME 186.23%LAST 0.00050.28750.21570.14400.07220.0005μ = 0.0363max 0.2875min 0.0005dataMA(5)OLS R²=0.00μ lineμ ± σ bandmaxmin
25 YES observations from clob.polymarket.com · last 0.05¢
NO price · CLOB mid
n=25 · μ=0.9637 · σ=0.0676 · range [0.7125, 0.9995] · R²=0.003▲ RISING +4.11%σ HIGH 7.01%LAST 0.99950.99950.92780.85600.78430.7125μ = 0.9637max 0.9995min 0.7125dataMA(5)OLS R²=0.00μ 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=0.0046 · σ=0.0655 · skew=-2.37 (left-skewed) · kurt=9.88 (leptokurtic (fat tails))18149501-26.38ppbin -26.38pp · n=1 · 5.6% peakbin -26.38pp · n=1 · 5.6% peak-21.75pp-17.11pp-12.48pp-7.84pp3-3.21ppbin -3.21pp · n=3 · 16.7% peakbin -3.21pp · n=3 · 16.7% peak181.43ppbin 1.43pp · n=18 · 100.0% peakbin 1.43pp · n=18 · 100.0% peak16.06ppbin 6.06pp · n=1 · 5.6% peakbin 6.06pp · n=1 · 5.6% peak10.70pp115.33ppbin 15.33pp · n=1 · 5.6% peakbin 15.33pp · n=1 · 5.6% 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=-2.01 · kurt=9.69 · near 6 / mid 15 / far 3 · OLS slope=0.74 intercept=-0.00LEPTOKURTIC — FAT TAILSUPPER TAIL NORMALLOWER TAIL NORMAL-3σ-3σ-2σ-2σ-1σ-1σ+0σ+0σ+1σ+1σ+2σ+2σ+3σ+3σΔ=-1.99σsample ↓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=6.70)
μ MEAN3.63¢95% CI: [0.98¢, 6.28¢]
σ STD DEV6.76ppσ² = 45.699 · CV = 186.23%
med MEDIAN1.55¢Q₁ 0.05¢ · Q₃ 3.85¢
FIVE-NUMBER SUMMARY · BOX PLOTrange 28.70pp · IQR 3.80pp (1.349σ→9.12pp)
min 0.05¢Q₁ 0.05¢med 1.55¢Q₃ 3.85¢max 28.75¢μ
SKEWNESS · G₁2.759right-skewed
−3−10+1+3
EXCESS KURTOSIS · G₂6.697leptokurtic · fat tails
−30+2+4+6
μ ↔ medianμ > med · right-tailed|μ−med| / σ = 0.31
σ × 1.349 ↔ IQRdiverges from normalratio = 2.40
range ↔ σwide tails (range > 4σ)range / σ = 4.25
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 · ADF rejects unit root
ρ(1) AUTOCORR-0.020within white-noise band
ρ(2) AUTOCORR-0.415lag-2 dependence detected
H · HURST EXPONENT0.748strongly persistent
OLS TREND · t-STAT-0.257fails 5% test
HURST EXPONENT [0, 1]strongly persistent · H = 0.748
H = 0.748STRONGLY 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=2
k=1-0.020k=2 ★-0.415k=3-0.102k=4+0.026k=5+0.0410+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|=0.26)
−5 reject−1.960 retain H₀+1.96+5 reject
REGIME CLASSIFICATIONMEAN-REVERTING · ADF rejects unit rootfrom Hurst + ρ(1) joint diagnosis
PREDICTABILITY · score 0.52high · clear structure|ρ(1)| + 2·|H − 0.5| heuristic
TREND SIGNIFICANCENOT SIGNIFICANT (|t|=0.26)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 ID2592056
SLUGhighest-temperature-in-hong-kong-on-june-20-2026-30c
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 VOLUME34.26k USD 24h
LIQUIDITY9.63k 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.

§9 · Hourly return heatmap

24-hour signed Δp grid · green = up · red = down
HOURLY RETURN HEATMAP · n=24 bars · best 17.65% · worst -28.70% · typical |Δ| 2.74%BEARISH SESSION -3.95%BEST+17.65%15hWORST-28.70%17hTYPICAL |Δ|2.74%mean absoluteCUMULATIVE-3.95%Σ signed ΔSTREAK▬ 0flat-runASIA · 00-08 UTCμ -0.23% · Σ -1.60%EUROPE · 08-16 UTCμ +2.41% · Σ +19.30%US · 16-24 UTCμ -2.71% · Σ -21.65%CUMULATIVE Δ PATH · final -3.95%+24.75%-3.95%0.55% · 1h0.55% · 1h0.55%1h-0.10% · 2h-0.10% · 2h-0.10%2h-0.60% · 3h-0.60% · 3h-0.60%3h-0.90% · 4h-0.90% · 4h-0.90%4h-0.40% · 5h-0.40% · 5h-0.40%5h-1.15% · 6h-1.15% · 6h-1.15%6h1.00% · 7h1.00% · 7h1.00%7h-0.65% · 8h-0.65% · 8h-0.65%8h-0.30% · 9h-0.30% · 9h-0.30%9h0.10% · 10h0.10% · 10h0.10%10h1.30% · 11h1.30% · 11h1.30%11h-1.50% · 12h-1.50% · 12h-1.50%12h-0.60% · 13h-0.60% · 13h-0.60%13h3.30% · 14h3.30% · 14h3.30%14h17.65% · 15h17.65% · 15h17.65%15h★ BEST7.05% · 16h7.05% · 16h7.05%16h-28.70% · 17h-28.70% · 17h-28.70%17h▼ WORST0.00% · 18h0.00% · 18h·18h0.00% · 19h0.00% · 19h·19h0.00% · 20h0.00% · 20h·20h0.00% · 21h0.00% · 21h·21h0.00% · 22h0.00% · 22h·22h0.00% · 23h0.00% · 23h·23h0.00% · 24h0.00% · 24h·24hTIME PATTERNEurope-led (+19.30%)RUNSup max 3 · down max 5BREADTH29% up · 42% down · 29% flat
7 up bars · 10 down · best 17.65% · worst -28.70% · typical |Δ| 2.744%

§10 · Equity curve & underwater drawdown

Cumulative compounded return + running peak-to-trough
EQUITY & DRAWDOWN ANALYSIS · n=25 barsSEVERE DRAWDOWN -10.24%FINAL-10.24%MAX DD-28.70%RECOVERYONGOING · 8 barsMAX RUN-UP+25.88%UNDERWATER21/25 (84%)STREAK▬ 0EQUITY CURVE · end 0.8976 · peak 1.2588 · range [0.8976, 1.2588]1.25880.8976break-even = 1★ PEAK 1.2588UNDERWATER DRAWDOWN · max -28.70% · severe0%-28.70%▼ TROUGH -28.70%TOP DRAWDOWN PERIODS · 2 total#1 -28.70%bar 18-25 · 8 bars · ONGOING#2 -3.77%bar 3-15 · 13 bars · recoveredDD SEVERITYsevere (max -28.70%)RECOVERYongoing · 8 barsTIME UNDER WATER84% of session · 21/25 bars
final equity 0.8976 (-10.24%) · max DD -28.70% · time-under-water 21/25 bars

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

Rolling annualised Sharpe ratio · green positive · red negative
n=19 · +4 / −13 (21% positive) · μ=-11.51 · σ=32.73UNPROFITABLE STRATEGYLAST 0.00 (+0.35σ vs μ)66.8933.440.00-33.44-66.89μ = -11.51-66.89-66.89-44.10-44.10-55.69-55.69-49.63-49.63-29.84-29.844.924.92-0.75-0.75-27.54-27.5421.1421.1443.9443.9459.6459.64-2.82-2.82-1.31-1.31-0.71-0.71-4.06-4.06-26.78-26.78-38.21-38.210.000.000.000.00v > 0 · positivev < 0 · negativeμ mean lineμ ± σ bandlatest bar (outlined)
latest 0.000 · range [-66.89, 59.64] · μ -11.509 · positive Sharpe = excess-return-per-risk earned by buying-and-holding through this window
Rolling annualised volatility (%)
n=19 · μ=535.2118 · σ=600.0711 · range [0.0000, 1448.2175] · R²=0.283▼ FALLING -100.00%σ EXTREME 112.12%LAST 0.00001448.21751086.1631724.1087362.05440.0000μ = 535.2118max 1448.2175min 0.0000dataMA(3)OLS R²=0.28μ lineμ ± σ bandmaxmin
latest 0.00% · range [0.00%, 1448.22%] · μ 535.21% · σ̂ scaled to annualised (×√8760)
Rolling lag-1 autocorrelation ρ(1)
n=19 · +3 / −14 (16% positive) · μ=-0.156 · σ=0.246MEAN-REVERSIONLAST 0.000 (+0.63σ vs μ)0.5550.2770.000-0.277-0.555μ = -0.1560.1690.169-0.329-0.329-0.453-0.453-0.501-0.501-0.555-0.555-0.335-0.335-0.421-0.421-0.215-0.215-0.195-0.1950.1370.1370.2910.291-0.007-0.007-0.018-0.018-0.017-0.017-0.078-0.078-0.401-0.401-0.033-0.0330.0000.0000.0000.000v > 0 · positivev < 0 · negativeμ mean lineμ ± σ bandlatest bar (outlined)
latest 0.000 · |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
171.3270
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
5.2847
p-VALUE (log scale)
0.3824
α
10⁻⁴10⁻³10⁻²10⁻¹1
p ≥ α · null retainedconsistent with white noise
Ψ

Dickey-Fuller (τ_μ)

REJECT H₀*

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

STATISTIC
-2.8652
p-VALUE (log scale)
0.0495
α
10⁻⁴10⁻³10⁻²10⁻¹1
p < α · rejection zonestationary · mean-reverting (crit ≈ -2.86)
±

Wald-Wolfowitz runs

FAIL TO REJECTns

H₀: Sign sequence of Δ is random

STATISTIC
-0.6401
p-VALUE (log scale)
0.5221
α
10⁻⁴10⁻³10⁻²10⁻¹1
p ≥ α · null retainedsigns appear random (8 runs)
χ

KPSS (μ stationarity)

FAIL TO REJECTns

H₀: p IS level-stationary

STATISTIC
0.0828
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
-0.7789
p-VALUE (log scale)
0.4361
α
10⁻⁴10⁻³10⁻²10⁻¹1
p ≥ α · null retainedVR 0.763 ≈ 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=5.06e-3 · top T=4.00h (16.4%) · top-3 cover 45.3%WHITE NOISE · no dominant cyclecumulative energy ↗ (0 bins above 2× noise)9.9e-37.5e-35.0e-32.5e-30.0e+0μ noise floorperiod 24.0 · power 6.29e-4 · 1.0% energyperiod 24.0 · power 6.29e-4 · 1.0% energyperiod 12.0 · power 2.83e-3 · 4.7% energyperiod 12.0 · power 2.83e-3 · 4.7% energyperiod 8.0 · power 4.91e-3 · 8.1% energyperiod 8.0 · power 4.91e-3 · 8.1% energyperiod 6.0 · power 7.73e-3 · 12.7% energyperiod 6.0 · power 7.73e-3 · 12.7% energyperiod 4.8 · power 9.84e-3 · 16.2% energyperiod 4.8 · power 9.84e-3 · 16.2% energyperiod 4.0 · power 9.94e-3 · 16.4% energyperiod 4.0 · power 9.94e-3 · 16.4% energyperiod 3.4 · power 7.48e-3 · 12.3% energyperiod 3.4 · power 7.48e-3 · 12.3% energyperiod 3.0 · power 5.52e-3 · 9.1% energyperiod 3.0 · power 5.52e-3 · 9.1% energyperiod 2.7 · power 4.74e-3 · 7.8% energyperiod 2.7 · power 4.74e-3 · 7.8% energyperiod 2.4 · power 3.21e-3 · 5.3% energyperiod 2.4 · power 3.21e-3 · 5.3% energyperiod 2.2 · power 2.83e-3 · 4.7% energyperiod 2.2 · power 2.83e-3 · 4.7% energyperiod 2.0 · power 1.10e-3 · 1.8% energyperiod 2.0 · power 1.10e-3 · 1.8% energy50% by T=4.0h#1 dominantT=4.00h#2T=4.80h#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 ≈ 4.00h (freq 0.250) · concentrates 16.4% of total energy · Σ|X̂|²/n = 6.075e-2

▸ Depth section using sovereign-store price series (1048 bars · effective 1752713 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 0.000pp · expected |Δp| over horizon 0.00ppterminal variance p(1−p) = 0.0005 · n = 1048✓ n = 1048
μ per bar
+0.000pp
average Δp · drift
σ per bar
0.000pp
one-bar volatility · logit-free
Per-day movedaily
0.00pp
σ × √24
Per-horizon move0d
0.00pp
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 0.00pp · ES₉₅ 0.00pp · method parametric · drift-correcteddrift +0.000pp/bar · quantised: yes · median step 0.00pp · unique ratio 0.00✓ n = 1048
VaR 95%
0.00pp
1.645·σ (parametric) of Δp
ES 95%
0.00pp
mean of the tail
Max drawdown
0.0pp
peak 0.1¢ → trough 0.1¢
Median step
0.00pp
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
56760642343608881015248854761925735279376029430874004242942176182414561104659
NO token ID
32195680299736121445242355770283722187682210971274397543347251209150336446871
Snapshot fetched
2026-06-20 12:10:29 UTC
Snapshot age
14.1s
History points
25 CLOB mids
Page rendered
2026-06-20 12:10:43 UTC
Storage policy
no persistence — fetched on every request
SHA-256 attestation
6afe28d617630a43348f7d3159ee25a1e21e38208be16bc63dc4f791f641a568 · 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-hong-kong-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 · 1,048 barsperiods/year ≈ 1.75M
Realized vol (annualised)
0.00%
σ per bar = 0.000000
Mean return (annualised)
0.00%
μ per bar = 0.000000
Sharpe (rf=0)
0.00
annualised; risk-free assumed zero
Max drawdown
0.00%
peak 0.00 → trough 0.00 over 0 bars

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