POLYMARKET · PREDICTION MARKET · WEATHER & CLIMATE

Will the highest temperature in Hong Kong be 33°C on June 20?

YES · live
0.2¢
NO · live
99.8¢

▸ Advanced metrics · M2M bundle

polymarket · highest-temperature-in-hong-kong-on-june-20-2026-33c · fresh · feed 15s old
24h sparkline · 60 pts▼ —
realized vol (ann.)
36.86%
max drawdown
96.30%
sharpe
—
ulcer index
81.97%
RMS drawdown
pain index
80.23%
mean drawdown
mod. VaR 95%
0.00%
Cornish-Fisher
martin ratio
—
ret / ulcer
CDaR 95%
89.48%
cond. drawdown
gain/pain
0.44
Σgain / Σ|loss|
sterling
—
ret / CDaR
omega (θ=0)
0.44
upside/downside
roll spread
82.4 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-20-2026-33c/bundle · venue execution: polymarket →
LIVEPOLL0SRCWARMING14.5s⏱--:--:-- 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
0.2¢
NO · live
99.8¢
YES price · live 24h
n=25 · μ=0.1533 · σ=0.1241 · range [0.0015, 0.3850] · R²=0.877▼ FALLING -99.48%σ EXTREME 80.95%LAST 0.00200.38500.28910.19330.09740.0015μ = 0.1533max 0.3850min 0.0015dataMA(5)OLS R²=0.88μ lineμ ± σ bandmaxminlive endpoint
25 ticks · last 0.20¢
YES / NO split · live
YES 0.2%NO 99.8%NO99.8%99.80¢ · odds 1/1.00
Σ 100.00% · fair
Σ-sides total = 100.00% (tight rounding)
H(p) entropy = 0.021 / 1.00 bits (2%) · informative — one side favoured
YES
0.2%0.2¢500.00×▬ +0.00pp
NO
99.8%99.8¢1.00×▬ +0.00pp
Σ 100.00% · arb gap 0.00pp
Per-tick activity · |Δp| in basis points · live
n=24 · Σ=4,640 · μ=193.3 · σ=296.2 · CV=1.53BURSTY · concentratedcumulative energy ↗ · 50% by h=1402755508251,100μ = 1931,10050%h1h5h9h13h17h21#1 peak#2-3> μactivequietμ linecum energy
Σ 4640bp moved · peak 1100bp · n=24 ticks
Live numerics · pulse on poll
LIVE NUMERICS8 metrics·POLL 0
⏱snapshot age
14.5s
▲YES mid
0.20¢ (0.20%)
▼NO mid
99.80¢ (99.80%)
ΣΣ sides
100.00%
⚖arb gap
0.000pp
$24h vol $
$24.5k
≋liquidity $
$4.3k
◳history points
25 ticks (live)

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

YES price · CLOB mid
n=25 · μ=0.1533 · σ=0.1241 · range [0.0015, 0.3850] · R²=0.877▼ FALLING -99.48%σ EXTREME 80.95%LAST 0.00200.38500.28910.19330.09740.0015μ = 0.1533max 0.3850min 0.0015dataMA(5)OLS R²=0.88μ lineμ ± σ bandmaxmin
25 YES observations from clob.polymarket.com · last 0.20¢
NO price · CLOB mid
n=25 · μ=0.8467 · σ=0.1241 · range [0.6150, 0.9985] · R²=0.877▲ RISING +62.28%σ HIGH 14.65%LAST 0.99800.99850.90260.80680.71090.6150μ = 0.8467max 0.9985min 0.6150dataMA(5)OLS R²=0.88μ lineμ ± σ bandmaxmin
25 NO observations from clob.polymarket.com · last 99.80¢

§2 · Distribution of Δp

Histogram of hourly increments
n=24 · 10 bins · μ=-0.0172 · σ=0.0290 · skew=-1.50 (left-skewed) · kurt=1.54 (leptokurtic (fat tails))14117401-10.30ppbin -10.30pp · n=1 · 7.1% peakbin -10.30pp · n=1 · 7.1% peak-8.90pp1-7.50ppbin -7.50pp · n=1 · 7.1% peakbin -7.50pp · n=1 · 7.1% peak2-6.10ppbin -6.10pp · n=2 · 14.3% peakbin -6.10pp · n=2 · 14.3% peak-4.70pp2-3.30ppbin -3.30pp · n=2 · 14.3% peakbin -3.30pp · n=2 · 14.3% peak1-1.90ppbin -1.90pp · n=1 · 7.1% peakbin -1.90pp · n=1 · 7.1% peak14-0.50ppbin -0.50pp · n=14 · 100.0% peakbin -0.50pp · n=14 · 100.0% peak20.90ppbin 0.90pp · n=2 · 14.3% peakbin 0.90pp · n=2 · 14.3% peak12.30ppbin 2.30pp · n=1 · 7.1% peakbin 2.30pp · n=1 · 7.1% 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=-1.56 · kurt=1.89 · near 7 / mid 17 / far 0 · OLS slope=0.90 intercept=-0.00LEFT-SKEWED · HEAVY NEGATIVE TAILTHIN UPPER TAILFAT LOWER TAIL-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=-1.54)
μ MEAN15.33¢95% CI: [10.46¢, 20.19¢]
σ STD DEV12.41ppσ² = 153.903 · CV = 80.95%
med MEDIAN21.00¢Q₁ 0.55¢ · Q₃ 24.50¢
FIVE-NUMBER SUMMARY · BOX PLOTrange 38.35pp · IQR 23.95pp (1.349σ→16.74pp)
min 0.15¢Q₁ 0.55¢med 21.00¢Q₃ 24.50¢max 38.50¢μ
SKEWNESS · G₁-0.080approximately symmetric
−3−10+1+3
EXCESS KURTOSIS · G₂-1.538platykurtic · thin tails
−30+2+4+6
μ ↔ medianμ < med · left-tailed|μ−med| / σ = 0.46
σ × 1.349 ↔ IQRdiverges from normalratio = 0.70
range ↔ σconcentrated (range < 4σ)range / σ = 3.09
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+0.386within white-noise band
ρ(2) AUTOCORR-0.050lag-2 not significant
H · HURST EXPONENT0.669persistent
OLS TREND · t-STAT-12.823significant @ α=0.05
HURST EXPONENT [0, 1]persistent · H = 0.669
H = 0.669PERSISTENT
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+0.386k=2-0.050k=3-0.263k=4-0.162k=5-0.0620+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|=12.82)
−5 reject−1.960 retain H₀+1.96+5 reject
REGIME CLASSIFICATIONTRENDING · variance ratio > 1from Hurst + ρ(1) joint diagnosis
PREDICTABILITY · score 0.72very high · strong structure|ρ(1)| + 2·|H − 0.5| heuristic
TREND SIGNIFICANCESIGNIFICANT @ 1% (|t|=12.82)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 ID2592059
SLUGhighest-temperature-in-hong-kong-on-june-20-2026-33c
CATEGORYWeather & Climate
TWO-SIDED PRICINGFAVOURS NO (100¢)
PRIMARY · YES0.20¢implied prob 0.20% · decimal odds 500.00×
COUNTER · NO99.80¢implied prob 99.80% · decimal odds 1.00×
0.20¢
99.80¢
Σ-SIDES ARBITRAGE TESTPERFECT · ARB-FREE Σ=100.00%
0%50%100% · target110%
Σ = 100.00% · |1 − Σ| = 0.000pp
24H ACTIVITY · LIQUIDITYACTIVE
24H VOLUME24.45k USD 24h
LIQUIDITY4.30k USD
MARKET QUALITYPERFECT · ARB-FREE Σ=100.00%|1−Σ| ≤ 0.5pp ⇒ fair · > 2pp ⇒ inefficient
PRICING SKEWFAVOURS NO (100¢)|primary − counter| = 0.996 · entropy 0.021 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 0.2%NO 99.8%YES p̂0.2%H = 0.021 / 1.00 bits
Probability scale (YES)
0%25%50%
fair75%100%
Implied decimal odds
YES500.00×(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) = 0.021 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.

§9 · Hourly return heatmap

24-hour signed Δp grid · green = up · red = down
HOURLY RETURN HEATMAP · n=24 bars · best 3.00% · worst -11.00% · typical |Δ| 1.93%BEARISH SESSION -38.30%BEST+3.00%12hWORST-11.00%15hTYPICAL |Δ|1.93%mean absoluteCUMULATIVE-38.30%Σ signed ΔSTREAK↗ 1up-runASIA · 00-08 UTCμ -2.50% · Σ -17.50%EUROPE · 08-16 UTCμ -1.81% · Σ -14.50%US · 16-24 UTCμ -0.79% · Σ -6.35%CUMULATIVE Δ PATH · final -38.30%+0.00%-38.35%-8.00% · 1h-8.00% · 1h-8.00%1h-3.00% · 2h-3.00% · 2h-3.00%2h-0.50% · 3h-0.50% · 3h-0.50%3h0.50% · 4h0.50% · 4h0.50%4h-0.50% · 5h-0.50% · 5h-0.50%5h-6.00% · 6h-6.00% · 6h-6.00%6h0.00% · 7h0.00% · 7h·7h0.00% · 8h0.00% · 8h·8h0.00% · 9h0.00% · 9h·9h0.00% · 10h0.00% · 10h·10h0.50% · 11h0.50% · 11h0.50%11h3.00% · 12h3.00% · 12h3.00%12h★ BEST-1.00% · 13h-1.00% · 13h-1.00%13h-6.00% · 14h-6.00% · 14h-6.00%14h-11.00% · 15h-11.00% · 15h-11.00%15h▼ WORST-3.00% · 16h-3.00% · 16h-3.00%16h-2.20% · 17h-2.20% · 17h-2.20%17h-0.75% · 18h-0.75% · 18h-0.75%18h-0.15% · 19h-0.15% · 19h-0.15%19h-0.20% · 20h-0.20% · 20h-0.20%20h0.00% · 21h0.00% · 21h·21h-0.05% · 22h-0.05% · 22h-0.05%22h0.00% · 23h0.00% · 23h·23h0.05% · 24h0.05% · 24h0.05%24hTIME PATTERNUS-led (+-6.35%)RUNSup max 2 · down max 8BREADTH17% up · 58% down · 25% flat
4 up bars · 14 down · best 3.00% · worst -11.00% · typical |Δ| 1.933%

§10 · Equity curve & underwater drawdown

Cumulative compounded return + running peak-to-trough
EQUITY & DRAWDOWN ANALYSIS · n=25 barsSEVERE DRAWDOWN -32.86%FINAL-32.86%MAX DD-32.89%RECOVERYONGOING · 24 barsMAX RUN-UP+0.00%UNDERWATER24/25 (96%)STREAK↗ 1EQUITY CURVE · end 0.6714 · peak 1.0000 · range [0.6711, 1.0000]1.00000.6711break-even = 1★ PEAK 1.0000UNDERWATER DRAWDOWN · max -32.89% · severe0%-32.89%▼ TROUGH -32.89%TOP DRAWDOWN PERIODS · 1 total#1 -32.89%bar 2-25 · 24 bars · ONGOINGDD SEVERITYsevere (max -32.89%)RECOVERYongoing · 24 barsTIME UNDER WATER96% of session · 24/25 bars
final equity 0.6714 (-32.86%) · max DD -32.89% · time-under-water 24/25 bars

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

Rolling annualised Sharpe ratio · green positive · red negative
n=19 · +2 / −17 (11% positive) · μ=-48.04 · σ=35.75UNPROFITABLE STRATEGYLAST -56.26 (-0.23σ vs μ)95.3247.660.00-47.66-95.32μ = -48.04-79.67-79.67-59.80-59.80-41.60-41.60-37.90-37.90-41.95-41.95-34.34-34.3445.4745.4728.7428.74-18.36-18.36-43.99-43.99-54.55-54.55-66.33-66.33-95.32-95.32-88.72-88.72-65.23-65.23-78.43-78.43-61.61-61.61-62.87-62.87-56.26-56.26v > 0 · positivev < 0 · negativeμ mean lineμ ± σ bandlatest bar (outlined)
latest -56.263 · range [-95.32, 45.47] · μ -48.038 · positive Sharpe = excess-return-per-risk earned by buying-and-holding through this window
Rolling annualised volatility (%)
n=19 · μ=250.0329 · σ=146.2392 · range [9.0824, 481.2785] · R²=0.046▼ FALLING -97.17%σ EXTREME 58.49%LAST 9.0824481.2785363.2295245.1805127.13149.0824μ = 250.0329max 481.2785min 9.0824dataMA(3)OLS R²=0.05μ lineμ ± σ bandmaxmin
latest 9.08% · range [9.08%, 481.28%] · μ 250.03% · σ̂ scaled to annualised (×√8760)
Rolling lag-1 autocorrelation ρ(1)
n=19 · +13 / −6 (68% positive) · μ=0.106 · σ=0.241MOMENTUM / PERSISTENCELAST 0.255 (+0.62σ vs μ)0.4870.2440.000-0.244-0.487μ = 0.1060.1580.158-0.287-0.287-0.174-0.174-0.156-0.156-0.160-0.160-0.027-0.0270.1200.120-0.340-0.3400.1270.1270.4250.4250.4090.4090.2350.2350.1130.1130.3310.3310.1810.1810.4870.4870.2410.2410.0710.0710.2550.255v > 0 · positivev < 0 · negativeμ mean lineμ ± σ bandlatest bar (outlined)
latest 0.255 · |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
18.1422
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
7.1114
p-VALUE (log scale)
0.2113
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
-1.5242
p-VALUE (log scale)
0.5218
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
-0.8840
p-VALUE (log scale)
0.3767
α
10⁻⁴10⁻³10⁻²10⁻¹1
p ≥ α · null retainedsigns appear random (6 runs)
χ

KPSS (μ stationarity)

REJECT H₀**

H₀: p IS level-stationary

STATISTIC
0.8589
p-VALUE (log scale)
0.0051
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
1.4244
p-VALUE (log scale)
0.1543
α
10⁻⁴10⁻³10⁻²10⁻¹1
p ≥ α · null retainedVR 1.433 ≈ 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=9.69e-4 · top T=12.00h (26.7%) · top-3 cover 64.1%BROADBAND · 3 CYCLEScumulative energy ↗ (3 bins above 2× noise)3.1e-32.3e-31.6e-37.8e-40.0e+0μ noise floor2× noise (significance)period 24.0 · power 2.19e-4 · 1.9% energyperiod 24.0 · power 2.19e-4 · 1.9% energyperiod 12.0 · power 3.11e-3 · 26.7% energyperiod 12.0 · power 3.11e-3 · 26.7% energyperiod 8.0 · power 2.08e-3 · 17.9% energyperiod 8.0 · power 2.08e-3 · 17.9% energyperiod 6.0 · power 8.45e-4 · 7.3% energyperiod 6.0 · power 8.45e-4 · 7.3% energyperiod 4.8 · power 2.27e-3 · 19.5% energyperiod 4.8 · power 2.27e-3 · 19.5% energyperiod 4.0 · power 1.09e-3 · 9.4% energyperiod 4.0 · power 1.09e-3 · 9.4% energyperiod 3.4 · power 2.32e-4 · 2.0% energyperiod 3.4 · power 2.32e-4 · 2.0% energyperiod 3.0 · power 5.58e-5 · 0.5% energyperiod 3.0 · power 5.58e-5 · 0.5% energyperiod 2.7 · power 4.31e-4 · 3.7% energyperiod 2.7 · power 4.31e-4 · 3.7% energyperiod 2.4 · power 8.05e-4 · 6.9% energyperiod 2.4 · power 8.05e-4 · 6.9% energyperiod 2.2 · power 2.72e-4 · 2.3% energyperiod 2.2 · power 2.72e-4 · 2.3% energyperiod 2.0 · power 2.28e-4 · 2.0% energyperiod 2.0 · power 2.28e-4 · 2.0% energy50% by T=6.0h#1 dominantT=12.00h#2T=4.80h#3T=8.00hT=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 ≈ 12.00h (freq 0.083) · concentrates 26.7% of total energy · Σ|X̂|²/n = 1.163e-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 0.028pp · expected |Δp| over horizon 0.07ppterminal variance p(1−p) = 0.0020 · n = 1048✓ n = 1048
μ per bar
-0.001pp
average Δp · drift
σ per bar
0.028pp
one-bar volatility · logit-free
Per-day movedaily
0.14pp
σ × √24
Per-horizon move0d
0.07pp
σ × √6
Terminal variancebinary
0.0020
p(1−p) at resolution
Current pricep
0.2¢
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 0.05pp · ES₉₅ 0.06pp · method parametric · drift-correcteddrift -0.001pp/bar · quantised: yes · median step 0.05pp · unique ratio 0.02✓ n = 1048
VaR 95%
0.05pp
1.645·σ (parametric) of Δp
ES 95%
0.06pp
mean of the tail
Max drawdown
96.3pp
peak 1.4¢ → 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
0.2%
= price
Decimal oddsEU
500.000
total return per $1
AmericanUS
+49900
$100 wins $49900
FractionalUK
499.00 / 1
profit per $1 risked
Profit per $100stake
+$49900.00
clean dollar framing
-1000-5000+500+1000020406080100you · 0.2%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)
0.021 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.021 bit
Δ +0.000 bit vs market
Surprise · YES−log₂ p
8.97 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
102747607448950863390918375670306600569497178749235846226893413267381970792454
NO token ID
95379825897057446722777288767757155850357397782906176552346803090593177714423
Snapshot fetched
2026-06-20 12:10:29 UTC
Snapshot age
14.5s
History points
25 CLOB mids
Page rendered
2026-06-20 12:10:44 UTC
Storage policy
no persistence — fetched on every request
SHA-256 attestation
7e33e8b787c86740dd1cecee2ed782f72baa1ac9dbd9f562a825253f314d1bf1 · deterministic hash of source snapshot
Open data licence
CC0 / public domain

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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-20-2026-33c/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)
10984.86%
σ per bar = 0.082973
Mean return (annualised)
-319663.82%
μ per bar = -0.001824
Sharpe (rf=0)
-29.10
annualised; risk-free assumed zero
Max drawdown
96.30%
peak 0.01 → trough 0.00 over 660 bars

/api/asset/pm-highest-temperature-in-hong-kong-on-june-20-2026-33c/risk · same metrics, JSON