POLYMARKET · PREDICTION MARKET · POLITICS
Will Robert Kenyon win the 2026 Makerfield by-election?
26.5¢
73.5¢
▸ Advanced metrics · M2M bundle
polymarket · will-robert-kenyon-win-the-2026-makerfield-by-election · fresh · feed 17s old24h sparkline · 60 pts▼ —
realized vol (ann.)
29.60%
max drawdown
3.64%
sharpe
—
ulcer index
1.23%
RMS drawdown
pain index
0.42%
mean drawdown
mod. VaR 95%
0.00%
Cornish-Fisher
martin ratio
—
ret / ulcer
CDaR 95%
3.64%
cond. drawdown
gain/pain
0.00
Σgain / Σ|loss|
sterling
—
ret / CDaR
omega (θ=0)
0.00
upside/downside
roll spread
0.4 bps
implied (price-only)
bars used
2000
store
spread
—
24h Δ
—
flow lean
—
carry
flat
signalNEUTRALconfidence 20%
Same bundle via M2M API:
/api/m2m/pm-will-robert-kenyon-win-the-2026-makerfield-by-election/bundle · venue execution: polymarket →LIVEPOLL0SRCWARMING⏱--:--:-- UTCNEXT8.0sUP0s--:--HIST
▶ 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
26.5¢
NO · live
73.5¢
25 ticks · last 26.50¢
Σ 100.00% · fair
Σ-sides total = 100.00% (tight rounding)
H(p) entropy = 0.834 / 1.00 bits (83%) · high uncertainty
YES26.5%26.5¢3.77×▬ +0.00pp
NO73.5%73.5¢1.36×▬ +0.00pp
Σ 100.00% · arb gap 0.00pp
Σ 900bp moved · peak 400bp · n=24 ticks
17.4s
26.50¢ (26.50%)
73.50¢ (73.50%)
100.00%
0.000pp
$197.6k
$136.0k
25 ticks (live)
§1 · 24h price history (YES + NO tokens)
25 YES observations from clob.polymarket.com · last 26.50¢
25 NO observations from clob.polymarket.com · last 73.50¢
§2 · Distribution of Δp
n=24
reference line = identity (perfect normality). Heavy upper-right tail = fat positive tail.
§3 · Sample moments
SAMPLE MOMENTS · N=25PLATYKURTIC · THIN TAILS (G₂=-1.36)
FIVE-NUMBER SUMMARY · BOX PLOT
SKEWNESS · G₁-0.474approximately symmetric
−3−10+1+3
EXCESS KURTOSIS · G₂-1.358platykurtic · thin tails
−30+2+4+6
μ = mean YES probability · σ = standard deviation · 95% CI = μ ± 1.96·SE. Skew/kurt diagnose departure from normality.
§5 · Time-series structure
TIME-SERIES STRUCTUREREGIME: MEAN-REVERTING · ρ(1) -0.21 + ADF rejected
HURST EXPONENT [0, 1]
H = 0.765STRONGLY PERSISTENT
0
anti-persistent0.45
mean-reverting0.5
random walk0.55
persistent1
strongly trending
anti-persistent0.45
mean-reverting0.5
random walk0.55
persistent1
strongly trending
AUTOCORRELATION FUNCTION · ρ(k) for k=1..5
OLS TREND · t-STAT · [-5, +5]
−5 reject−1.960 retain H₀+1.96+5 reject
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
MICROSTRUCTURE · MARKET QUALITYPERFECT · ARB-FREE Σ=100.00%
TWO-SIDED PRICING
26.50¢
73.50¢
Σ-SIDES ARBITRAGE TEST
Σ = 100.00% · |1 − Σ| = 0.000pp
24H ACTIVITY · LIQUIDITY
Σ-sides = YES + NO implied probabilities. Perfect arb-free Σ = 100%. |1−Σ| > 2pp suggests synthetic outright arbitrage.
§7 · Position sizing & edge analysis
FAIR MARKET · no edge
Probability scale (YES)
Implied decimal odds
YES3.77×(27¢)NO1.36×(74¢)
Kelly bet-size (% of bankroll) K* = 0.00%
Entropy H(p̂) = 0.834 bits (83% of max) · high uncertainty
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
3 up bars · 4 down · best 4.00% · worst -1.00% · typical |Δ| 0.375%
§10 · Equity curve & underwater drawdown
final equity 1.0294 (2.94%) · max DD -1.99% · time-under-water 14/25 bars
§11 · Rolling-window statistics (w = 6 bars)
latest -38.210 · range [-60.42, 60.42] · μ 6.340 · positive Sharpe = excess-return-per-risk earned by buying-and-holding through this window
latest 38.21% · range [0.00%, 171.73%] · μ 71.64% · σ̂ scaled to annualised (×√8760)
latest -0.233 · |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)
2 of 6 REJECT · mixed evidence2 reject·4 pass·α = 0.05
Jarque-Bera
REJECT H₀***H₀: Δp ~ Normal(μ, σ²)
STATISTIC
225.6628
p-VALUE (log scale)
< 0.0001
Ljung-Box(h=5)
FAIL TO REJECTnsH₀: No serial autocorrelation up to lag 5
STATISTIC
3.4363
p-VALUE (log scale)
0.6356
Dickey-Fuller (τ_μ)
FAIL TO REJECTnsH₀: p has a unit root (non-stationary)
STATISTIC
-1.8956
p-VALUE (log scale)
0.3450
Wald-Wolfowitz runs
FAIL TO REJECTnsH₀: Sign sequence of Δ is random
STATISTIC
-0.3638
p-VALUE (log scale)
0.7160
KPSS (μ stationarity)
REJECT H₀*H₀: p IS level-stationary
STATISTIC
0.6575
p-VALUE (log scale)
0.0174
Variance ratio q=3
FAIL TO REJECTnsH₀: Δp is a random walk · VR = 1
STATISTIC
-0.9640
p-VALUE (log scale)
0.3350
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)
dominant period ≈ 2.00h (freq 0.500) · concentrates 23.4% of total energy · Σ|X̂|²/n = 1.140e-3
▸ Depth section using sovereign-store price series (3067 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
Horizon 7.0 d · σ/bar 0.078pp · expected |Δp| over horizon 1.01ppterminal variance p(1−p) = 0.1948 · n = 3067✓ n = 3067
μ per bar
+0.000pp
average Δp · drift
σ per bar
0.078pp
one-bar volatility · logit-free
Per-day movedaily
0.38pp
σ × √24
Per-horizon move7d
1.01pp
σ × √168
Terminal variancebinary
0.1948
p(1−p) at resolution
Current pricep
26.5¢
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
VaR₉₅ 0.13pp · ES₉₅ 0.16pp · method parametric · drift-correcteddrift +0.000pp/bar · quantised: yes · median step 1.00pp · unique ratio 0.00✓ n = 3067
VaR 95%
0.13pp
1.645·σ (parametric) of Δp
ES 95%
0.16pp
mean of the tail
Max drawdown
7.0pp
peak 28.5¢ → trough 26.5¢
Median step
1.00pp
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
Implied probabilityP
26.5%
= price
Decimal oddsEU
3.774
total return per $1
AmericanUS
+277
$100 wins $277
FractionalUK
2.77 / 1
profit per $1 risked
Profit per $100stake
+$277.36
clean dollar framing
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
Market entropyH(p)
0.834 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.834 bit
Δ +0.000 bit vs market
Surprise · YES−log₂ p
1.92 bit
self-information
Surprise · NO−log₂(1−p)
0.44 bit
self-information
Market entropy only — model entropy requires an external q.
§19 · Model-dependent surfaces
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
32749652958490459738077534958372321998219313230738592738299008092673106086919- NO token ID
69647131137181263161209582692292085273656986396122522741327860094193790245800- Snapshot fetched
- 2026-06-14 12:25:20 UTC
- Snapshot age
- 17.4s
- History points
- 25 CLOB mids
- Page rendered
- 2026-06-14 12:25:38 UTC
- Storage policy
- no persistence — fetched on every request
- SHA-256 attestation
480638b8225e822232730cd79983f49357117556bef19c39437af1e80cbd1d50· deterministic hash of source snapshot- Open data licence
- CC0 / public domain
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Also see: /arb opportunities · RSS feed · more in Politics
Market depth
▸ live order book · Polymarket YESDepth 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
0.265000
(best bid + best ask) / 2
Spread
377.4bp
(bestAsk − bestBid) / mid
Imbalance (whole book)
-0.458
ask-heavy
Imbalance (top-5)
-0.294
ask-heavy top-of-book
Slippage scenarios
▸ live book walk · Polymarket YESSimulating 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-will-robert-kenyon-win-the-2026-makerfield-by-election/slippage?size=10000&side=buy
| Side | Notional | Avg fill | Slippage | Worst fill | Levels | Status |
|---|---|---|---|---|---|---|
| BUY | $1.00K | 0.270000 | 188.68bp | 0.270000 | 1 | FILLED |
| BUY | $10.00K | 0.276397 | 430.09bp | 0.280000 | 2 | FILLED |
| BUY | $100.00K | 0.480123 | 8117.83bp | 0.890000 | 31 | FILLED |
| SELL | $1.00K | 0.260000 | 188.68bp | 0.260000 | 1 | FILLED |
| SELL | $10.00K | 0.247121 | 674.70bp | 0.230000 | 4 | FILLED |
| SELL | $100.00K | 0.116716 | 5595.63bp | 0.010000 | 21 | PARTIAL |
Risk metrics
▸ sovereign store · 3,067 barsperiods/year ≈ 1.75MRealized vol (annualised)
389.15%
σ per bar = 0.002939
Mean return (annualised)
2199.09%
μ per bar = 0.000013
Sharpe (rf=0)
5.65
annualised; risk-free assumed zero
Max drawdown
7.02%
peak 0.28 → trough 0.27 over 2545 bars
/api/asset/pm-will-robert-kenyon-win-the-2026-makerfield-by-election/risk · same metrics, JSON