POLYMARKET · PREDICTION MARKET · WEATHER & CLIMATE

Will the highest temperature in Shanghai be 22°C on June 14?

YES · live
81.0¢
NO · live
19.0¢

▸ Advanced metrics · M2M bundle

polymarket · highest-temperature-in-shanghai-on-june-14-2026-22c · fresh · feed 4s old
24h sparkline · 60 pts▼ —
realized vol (ann.)
2093.75%
max drawdown
43.61%
sharpe
—
ulcer index
22.38%
RMS drawdown
pain index
16.67%
mean drawdown
mod. VaR 95%
0.00%
Cornish-Fisher
martin ratio
—
ret / ulcer
CDaR 95%
42.46%
cond. drawdown
gain/pain
1.35
Σgain / Σ|loss|
sterling
—
ret / CDaR
omega (θ=0)
1.35
upside/downside
roll spread
7.9 bps
implied (price-only)
bars used
1146
store
spread
—
24h Δ
—
flow lean
—
carry
flat
signalNEUTRALconfidence 20%
Same bundle via M2M API: /api/m2m/pm-highest-temperature-in-shanghai-on-june-14-2026-22c/bundle · venue execution: polymarket →
LIVEPOLL0SRCFRESH3.9s⏱--:--:-- 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
81.0¢
NO · live
19.0¢
YES price · live 24h
n=25 · μ=0.2318 · σ=0.2858 · range [0.0155, 0.8255] · R²=0.688▲ RISING +1702.27%σ EXTREME 123.29%LAST 0.79300.82550.62300.42050.21800.0155μ = 0.2318max 0.8255min 0.0155dataMA(5)OLS R²=0.69μ lineμ ± σ bandmaxminlive endpoint
25 ticks · last 79.30¢
YES / NO split · live
YES 81.0%NO 19.0%YES81.0%81.00¢ · odds 1/1.23
Σ 100.00% · fair
Σ-sides total = 100.00% (tight rounding)
H(p) entropy = 0.701 / 1.00 bits (70%) · moderate uncertainty
YES
81.0%81.0¢1.23×▬ +0.00pp
NO
19.0%19.0¢5.26×▬ +0.00pp
Σ 100.00% · arb gap 0.00pp
Per-tick activity · |Δp| in basis points · live
n=24 · Σ=18,030 · μ=751.3 · σ=1046.1 · CV=1.39BURSTY · concentratedcumulative energy ↗ · 50% by h=2009991,9972,9963,995μ = 7513,99550%h1h5h9h13h17h21#1 peak#2-3> μactivequietμ linecum energy
Σ 18030bp moved · peak 3995bp · n=24 ticks
Live numerics · pulse on poll
LIVE NUMERICS8 metrics·POLL 0
⏱snapshot age
3.9s
▲YES mid
81.00¢ (81.00%)
▼NO mid
19.00¢ (19.00%)
ΣΣ sides
100.00%
⚖arb gap
0.000pp
$24h vol $
$35.7k
≋liquidity $
$975.7
◳history points
25 ticks (live)

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

YES price · CLOB mid
n=25 · μ=0.2318 · σ=0.2858 · range [0.0155, 0.8255] · R²=0.688▲ RISING +1702.27%σ EXTREME 123.29%LAST 0.79300.82550.62300.42050.21800.0155μ = 0.2318max 0.8255min 0.0155dataMA(5)OLS R²=0.69μ lineμ ± σ bandmaxmin
25 YES observations from clob.polymarket.com · last 79.30¢
NO price · CLOB mid
n=25 · μ=0.7681 · σ=0.2858 · range [0.1745, 0.9845] · R²=0.689▼ FALLING -78.32%σ EXTREME 37.20%LAST 0.20700.98450.78200.57950.37700.1745μ = 0.7681max 0.9845min 0.1745dataMA(5)OLS R²=0.69μ lineμ ± σ bandmaxmin
25 NO observations from clob.polymarket.com · last 20.70¢

§2 · Distribution of Δp

Histogram of hourly increments
n=24 · 10 bins · μ=0.0329 · σ=0.1170 · skew=0.91 (right-skewed) · kurt=1.51 (leptokurtic (fat tails))15118402-18.10ppbin -18.10pp · n=2 · 13.3% peakbin -18.10pp · n=2 · 13.3% peak-11.99pp1-5.88ppbin -5.88pp · n=1 · 6.7% peakbin -5.88pp · n=1 · 6.7% peak150.23ppbin 0.23pp · n=15 · 100.0% peakbin 0.23pp · n=15 · 100.0% peak16.35ppbin 6.35pp · n=1 · 6.7% peakbin 6.35pp · n=1 · 6.7% peak112.46ppbin 12.46pp · n=1 · 6.7% peakbin 12.46pp · n=1 · 6.7% peak218.56ppbin 18.56pp · n=2 · 13.3% peakbin 18.56pp · n=2 · 13.3% peak124.67ppbin 24.67pp · n=1 · 6.7% peakbin 24.67pp · n=1 · 6.7% peak30.78pp136.90ppbin 36.90pp · n=1 · 6.7% peakbin 36.90pp · n=1 · 6.7% 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=0.95 · kurt=1.90 · near 13 / mid 11 / far 0 · OLS slope=0.94 intercept=-0.00APPROXIMATELY NORMALMILDLY HEAVY UPPERLOWER 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=25STRONGLY RIGHT-SKEWED (G₁=1.04)
μ MEAN23.18¢95% CI: [11.98¢, 34.38¢]
σ STD DEV28.58ppσ² = 816.623 · CV = 123.29%
med MEDIAN5.15¢Q₁ 3.65¢ · Q₃ 41.55¢
FIVE-NUMBER SUMMARY · BOX PLOTrange 81.00pp · IQR 37.90pp (1.349σ→38.55pp)
min 1.55¢Q₁ 3.65¢med 5.15¢Q₃ 41.55¢max 82.55¢μ
SKEWNESS · G₁1.042right-skewed
−3−10+1+3
EXCESS KURTOSIS · G₂-0.583mesokurtic · normal-like
−30+2+4+6
μ ↔ medianμ > med · right-tailed|μ−med| / σ = 0.63
σ × 1.349 ↔ IQRconsistent with normalratio = 1.02
range ↔ σconcentrated (range < 4σ)range / σ = 2.83
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) -0.20 + ADF rejected
ρ(1) AUTOCORR-0.203within white-noise band
ρ(2) AUTOCORR-0.445lag-2 dependence detected
H · HURST EXPONENT0.979strongly persistent
OLS TREND · t-STAT+7.130significant @ α=0.05
HURST EXPONENT [0, 1]strongly persistent · H = 0.979
H = 0.979STRONGLY PERSISTENT
0
anti-persistent0.45
mean-reverting0.5
random walk0.55
persistent1
strongly trending
AUTOCORRELATION FUNCTION · ρ(k) for k=1..52 SIGNIFICANT LAGS · k=2,3
k=1-0.203k=2-0.445k=3 ★+0.449k=4+0.095k=5-0.1330+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|=7.13)
−5 reject−1.960 retain H₀+1.96+5 reject
REGIME CLASSIFICATIONMEAN-REVERTING · ρ(1) -0.20 + ADF rejectedfrom Hurst + ρ(1) joint diagnosis
PREDICTABILITY · score 1.00very high · strong structure|ρ(1)| + 2·|H − 0.5| heuristic
TREND SIGNIFICANCESIGNIFICANT @ 1% (|t|=7.13)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 ID2513945
SLUGhighest-temperature-in-shanghai-on-june-14-2026-22c
CATEGORYWeather & Climate
TWO-SIDED PRICINGFAVOURS YES (81¢)
PRIMARY · YES81.00¢implied prob 81.00% · decimal odds 1.23×
COUNTER · NO19.00¢implied prob 19.00% · decimal odds 5.26×
81.00¢
19.00¢
Σ-SIDES ARBITRAGE TESTPERFECT · ARB-FREE Σ=100.00%
0%50%100% · target110%
Σ = 100.00% · |1 − Σ| = 0.000pp
24H ACTIVITY · LIQUIDITYACTIVE
24H VOLUME35.69k USD 24h
LIQUIDITY976 USD
MARKET QUALITYPERFECT · ARB-FREE Σ=100.00%|1−Σ| ≤ 0.5pp ⇒ fair · > 2pp ⇒ inefficient
PRICING SKEWFAVOURS YES (81¢)|primary − counter| = 0.620 · entropy 0.701 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 81.0%NO 19.0%YES p̂81.0%H = 0.701 / 1.00 bits
Probability scale (YES)
0%25%50%
fair75%100%
Implied decimal odds
YES1.23×(81¢)NO5.26×(19¢)
Kelly bet-size (% of bankroll) K* = 0.00%
K* full
0.00%
½K half
0.00%
¼K quarter
0.00%
Entropy H(p̂) = 0.701 bits (70% of max) · moderate uncertainty
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 · CRITICALresolves 2026-06-14 12:00 UTC
0days
00hrs
52min
52 minutes·θ = 139.996 pp/day
YES →$1.00(P = 81.0%)
NO →$0.00(P = 19.0%)
current: $0.8100 · expected return per side: $0.19 on YES hit · $0.81 on NO hit
0%25%50%75%100%YES $1NO $0NOW+0.4hRESOLVESP projection · σ=28.58% · path funnel to settle at YES=1 or NO=0
Theta progression · θ ∝ σ / √t_remainingθ_now = 139.996 pp/day
now0.87h left
139.996 pp/day×1.00
−25%0.65h left
161.654 pp/day×1.15
−50%0.44h left
197.985 pp/day×1.41
−75%0.22h left
279.993 pp/day×2.00
−90%0.09h left
442.707 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 39.95% · worst -21.15% · typical |Δ| 7.51%MILD BULLISH +74.90%BEST+39.95%20hWORST-21.15%22hTYPICAL |Δ|7.51%mean absoluteCUMULATIVE+74.90%Σ signed ΔSTREAK↘ 1down-runASIA · 00-08 UTCμ -0.15% · Σ -1.05%EUROPE · 08-16 UTCμ +1.18% · Σ +9.40%US · 16-24 UTCμ +8.41% · Σ +67.30%CUMULATIVE Δ PATH · final +74.90%+78.15%-2.85%0.15% · 1h0.15% · 1h0.15%1h-0.65% · 2h-0.65% · 2h-0.65%2h1.30% · 3h1.30% · 3h1.30%3h-0.05% · 4h-0.05% · 4h-0.05%4h-1.80% · 5h-1.80% · 5h-1.80%5h1.25% · 6h1.25% · 6h1.25%6h-1.25% · 7h-1.25% · 7h-1.25%7h0.30% · 8h0.30% · 8h0.30%8h-0.50% · 9h-0.50% · 9h-0.50%9h-1.60% · 10h-1.60% · 10h-1.60%10h0.70% · 11h0.70% · 11h0.70%11h1.60% · 12h1.60% · 12h1.60%12h-0.80% · 13h-0.80% · 13h-0.80%13h6.80% · 14h6.80% · 14h6.80%14h2.90% · 15h2.90% · 15h2.90%15h11.15% · 16h11.15% · 16h11.15%16h24.25% · 17h24.25% · 17h24.25%17h-6.60% · 18h-6.60% · 18h-6.60%18h-17.55% · 19h-17.55% · 19h-17.55%19h39.95% · 20h39.95% · 20h39.95%20h★ BEST18.60% · 21h18.60% · 21h18.60%21h-21.15% · 22h-21.15% · 22h-21.15%22h▼ WORST18.65% · 23h18.65% · 23h18.65%23h-0.75% · 24h-0.75% · 24h-0.75%24hTIME PATTERNUS-led (+67.30%)RUNSup max 4 · down max 2BREADTH54% up · 46% down
13 up bars · 11 down · best 39.95% · worst -21.15% · typical |Δ| 7.512%

§10 · Equity curve & underwater drawdown

Cumulative compounded return + running peak-to-trough
EQUITY & DRAWDOWN ANALYSIS · n=25 barsPROFITABLE +77.58%FINAL+77.58%MAX DD-22.99%RECOVERYONGOING · 2 barsMAX RUN-UP+91.25%UNDERWATER16/25 (64%)STREAK↘ 1EQUITY CURVE · end 1.7758 · peak 1.9125 · range [0.9713, 1.9125]1.91250.9713break-even = 1★ PEAK 1.9125UNDERWATER DRAWDOWN · max -22.99% · severe0%-22.99%▼ TROUGH -22.99%TOP DRAWDOWN PERIODS · 4 total#1 -22.99%bar 19-20 · 2 bars · recovered#2 -21.15%bar 23-25 · 3 bars · ONGOING#3 -3.63%bar 5-14 · 10 bars · recoveredDD SEVERITYsevere (max -22.99%)RECOVERYongoing · 7 barsTIME UNDER WATER64% of session · 16/25 bars
final equity 1.7758 (77.58%) · max DD -22.99% · time-under-water 16/25 bars

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

Rolling annualised Sharpe ratio · green positive · red negative
n=19 · +12 / −7 (63% positive) · μ=18.76 · σ=35.05MIXED EDGELAST 24.85 (+0.17σ vs μ)78.2139.100.00-39.10-78.21μ = 18.762.652.65-14.58-14.58-3.06-3.06-29.17-29.17-47.11-47.11-15.27-15.27-9.60-9.60-4.08-4.0831.7731.7749.6249.6278.1978.1978.2178.2154.8754.8722.6022.6040.4140.4151.9851.9823.5123.5120.5920.5924.8524.85v > 0 · positivev < 0 · negativeμ mean lineμ ± σ bandlatest bar (outlined)
latest 24.848 · range [-47.11, 78.21] · μ 18.757 · positive Sharpe = excess-return-per-risk earned by buying-and-holding through this window
Rolling annualised volatility (%)
n=19 · μ=832.1909 · σ=880.9139 · range [102.5885, 2328.4384] · R²=0.829▲ RISING +1912.52%σ EXTREME 105.85%LAST 2218.08482328.43841771.97591215.5135659.0510102.5885μ = 832.1909max 2328.4384min 102.5885dataMA(3)OLS R²=0.83μ lineμ ± σ bandmaxmin
latest 2218.08% · range [102.59%, 2328.44%] · μ 832.19% · σ̂ scaled to annualised (×√8760)
Rolling lag-1 autocorrelation ρ(1)
n=19 · +3 / −16 (16% positive) · μ=-0.260 · σ=0.268MEAN-REVERSIONLAST -0.410 (-0.56σ vs μ)0.8120.4060.000-0.406-0.812μ = -0.260-0.451-0.451-0.550-0.550-0.521-0.521-0.812-0.812-0.565-0.565-0.475-0.4750.0160.016-0.095-0.095-0.149-0.149-0.062-0.062-0.066-0.0660.2480.248-0.289-0.2890.1490.149-0.287-0.287-0.152-0.152-0.210-0.210-0.262-0.262-0.410-0.410v > 0 · positivev < 0 · negativeμ mean lineμ ± σ bandlatest bar (outlined)
latest -0.410 · |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
3 of 6 REJECT · mixed evidence3 reject·3 pass·α = 0.05
𝒩

Jarque-Bera

REJECT H₀**

H₀: Δp ~ Normal(μ, σ²)

STATISTIC
11.2278
p-VALUE (log scale)
0.0036
α
10⁻⁴10⁻³10⁻²10⁻¹1
p < α · rejection zonenon-normal · fat tails or skew present
ρ

Ljung-Box(h=5)

REJECT H₀*

H₀: No serial autocorrelation up to lag 5

STATISTIC
13.5859
p-VALUE (log scale)
0.0185
α
10⁻⁴10⁻³10⁻²10⁻¹1
p < α · rejection zoneserial dependence detected
Ψ

Dickey-Fuller (τ_μ)

FAIL TO REJECTns

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

STATISTIC
-0.2206
p-VALUE (log scale)
0.9296
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
1.2965
p-VALUE (log scale)
0.1948
α
10⁻⁴10⁻³10⁻²10⁻¹1
p ≥ α · null retainedsigns appear random (16 runs)
χ

KPSS (μ stationarity)

REJECT H₀**

H₀: p IS level-stationary

STATISTIC
0.7423
p-VALUE (log scale)
0.0098
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
-1.7963
p-VALUE (log scale)
0.0724
α
10⁻⁴10⁻³10⁻²10⁻¹1
p ≥ α · null retainedVR 0.453 ≈ 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=1.52e-2 · top T=3.43h (24.8%) · top-3 cover 64.9%2 SIGNIFICANT CYCLEScumulative energy ↗ (2 bins above 2× noise)4.5e-23.4e-22.3e-21.1e-20.0e+0μ noise floor2× noise (significance)period 24.0 · power 1.46e-2 · 8.0% energyperiod 24.0 · power 1.46e-2 · 8.0% energyperiod 12.0 · power 9.56e-4 · 0.5% energyperiod 12.0 · power 9.56e-4 · 0.5% energyperiod 8.0 · power 1.00e-3 · 0.6% energyperiod 8.0 · power 1.00e-3 · 0.6% energyperiod 6.0 · power 4.57e-3 · 2.5% energyperiod 6.0 · power 4.57e-3 · 2.5% energyperiod 4.8 · power 1.27e-2 · 7.0% energyperiod 4.8 · power 1.27e-2 · 7.0% energyperiod 4.0 · power 2.81e-2 · 15.4% energyperiod 4.0 · power 2.81e-2 · 15.4% energyperiod 3.4 · power 4.53e-2 · 24.8% energyperiod 3.4 · power 4.53e-2 · 24.8% energyperiod 3.0 · power 4.50e-2 · 24.7% energyperiod 3.0 · power 4.50e-2 · 24.7% energyperiod 2.7 · power 1.83e-2 · 10.0% energyperiod 2.7 · power 1.83e-2 · 10.0% energyperiod 2.4 · power 6.98e-3 · 3.8% energyperiod 2.4 · power 6.98e-3 · 3.8% energyperiod 2.2 · power 4.06e-3 · 2.2% energyperiod 2.2 · power 4.06e-3 · 2.2% energyperiod 2.0 · power 8.64e-4 · 0.5% energyperiod 2.0 · power 8.64e-4 · 0.5% energy50% by T=3.4h#1 dominantT=3.43h#2T=3.00h#3T=4.00hT=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 ≈ 3.43h (freq 0.292) · concentrates 24.8% of total energy · Σ|X̂|²/n = 1.823e-1

▸ Depth section using sovereign-store price series (1146 bars · effective 1752810 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 1.582pp · expected |Δp| over horizon 3.88ppterminal variance p(1−p) = 0.1539 · n = 1146✓ n = 1146
μ per bar
+0.024pp
average Δp · drift
σ per bar
1.582pp
one-bar volatility · logit-free
Per-day movedaily
7.75pp
σ × √24
Per-horizon move0d
3.88pp
σ × √6
Terminal variancebinary
0.1539
p(1−p) at resolution
Current pricep
81.0¢
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 2.58pp · ES₉₅ 3.24pp · method parametric · drift-correcteddrift +0.024pp/bar · quantised: yes · median step 1.15pp · unique ratio 0.02✓ n = 1146
VaR 95%
2.58pp
1.645·σ (parametric) of Δp
ES 95%
3.24pp
mean of the tail
Max drawdown
43.6pp
peak 58.7¢ → trough 33.1¢
Median step
1.15pp
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
81.0%
= price
Decimal oddsEU
1.235
total return per $1
AmericanUS
-426
risk $426 to win $100
FractionalUK
0.23 / 1
profit per $1 risked
Profit per $100stake
+$23.46
clean dollar framing
-1000-5000+500+1000020406080100you · 81.0%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)
0.701 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.701 bit
Δ +0.000 bit vs market
Surprise · YES−log₂ p
0.30 bit
self-information
Surprise · NO−log₂(1−p)
2.40 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
14771402931013407210367786110294392898835815487381410757307406059868151418958
NO token ID
97536014117070946447046435236357052270983215580750442873777958055737690311653
Snapshot fetched
2026-06-14 11:07:38 UTC
Snapshot age
3.9s
History points
25 CLOB mids
Page rendered
2026-06-14 11:07:42 UTC
Storage policy
no persistence — fetched on every request
SHA-256 attestation
dd9b6855d68edb71984174ffa72c3cb502388a949299e4e756e8026bdd7e4d04 · deterministic hash of source snapshot
Open data licence
CC0 / public domain

§∞-2 · Related markets · explore more

HL PREDGermany94.4¢HL PREDSpain90.4¢HL PREDUruguay66.6¢POLYMARKETWill Australia win the 2026 FIFA World Cup?0¢POLYMARKETWill Scotland win the 2026 FIFA World Cup?0¢POLYMARKETUS x Iran permanent peace deal by June 15, 2026?23¢HL PERPBTC-USD perpetual$64,474HL PERPETH-USD perpetual$1,673HL PERPHYPE-USD perpetual$60.81

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
0.802500
(best bid + best ask) / 2
Spread
361.4bp
(bestAsk − bestBid) / mid
Imbalance (whole book)
-0.086
ask-heavy
Imbalance (top-5)
+0.197
bid-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-shanghai-on-june-14-2026-22c/slippage?size=10000&side=buy

SideNotionalAvg fillSlippageWorst fillLevelsStatus
BUY$1.00K0.8967941175.00bp0.94000015FILLED
BUY$10.00K0.9574431930.76bp0.99900030PARTIAL
BUY$100.00K0.9574431930.76bp0.99900030PARTIAL
SELL$1.00K0.0565729295.05bp0.00100021PARTIAL
SELL$10.00K0.0565729295.05bp0.00100021PARTIAL
SELL$100.00K0.0565729295.05bp0.00100021PARTIAL

Risk metrics

▸ sovereign store · 1,146 barsperiods/year ≈ 1.75M
Realized vol (annualised)
3927.59%
σ per bar = 0.029666
Mean return (annualised)
65076.13%
μ per bar = 0.000371
Sharpe (rf=0)
16.57
annualised; risk-free assumed zero
Max drawdown
43.61%
peak 0.59 → trough 0.33 over 102 bars

/api/asset/pm-highest-temperature-in-shanghai-on-june-14-2026-22c/risk · same metrics, JSON