POLYMARKET · PREDICTION MARKET · POLITICS
Will Pete Buttigieg win the 2028 Democratic presidential nomination?
4.3¢
95.7¢
▸ Advanced metrics · M2M bundle
polymarket · will-pete-buttigieg-win-the-2028-democratic-presidential-nomination-687 · fresh · feed 10s old24h 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
944
store
spread
—
24h Δ
—
flow lean
—
carry
flat
signalNEUTRALconfidence 20%
Same bundle via M2M API:
/api/m2m/pm-will-pete-buttigieg-win-the-2028-democratic-presidential-nomination-687/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
4.3¢
NO · live
95.7¢
25 ticks · last 4.35¢
Σ 100.00% · fair
Σ-sides total = 100.00% (tight rounding)
H(p) entropy = 0.258 / 1.00 bits (26%) · informative — one side favoured
YES4.3%4.3¢22.99×▬ +0.00pp
NO95.7%95.7¢1.05×▬ +0.00pp
Σ 100.00% · arb gap 0.00pp
Σ 10bp moved · peak 10bp · n=24 ticks
10.3s
4.35¢ (4.35%)
95.65¢ (95.65%)
100.00%
0.000pp
$35.5k
$448.4k
25 ticks (live)
§1 · 24h price history (YES + NO tokens)
25 YES observations from clob.polymarket.com · last 4.35¢
25 NO observations from clob.polymarket.com · last 95.65¢
§2 · Distribution of Δp
n=24
reference line = identity (perfect normality). Heavy upper-right tail = fat positive tail.
§3 · Sample moments
SAMPLE MOMENTS · N=25LEPTOKURTIC · FAT TAILS (G₂=6.76)
FIVE-NUMBER SUMMARY · BOX PLOT
SKEWNESS · G₁-2.912left-skewed
−3−10+1+3
EXCESS KURTOSIS · G₂6.757leptokurtic · fat 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 · ADF rejects unit root
HURST EXPONENT [0, 1]
H = 1.597STRONGLY 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
4.35¢
95.65¢
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
YES22.99×(4¢)NO1.05×(96¢)
Kelly bet-size (% of bankroll) K* = 0.00%
Entropy H(p̂) = 0.258 bits (26% of max) · informative — one side strongly favoured
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
⏱ URGENCY · DISTANTresolves 2028-11-07 00:00 UTC
870days
12hrs
21min
YES →$1.00
NO →$0.00
current: $0.0435 · expected return per side: $0.96 on YES hit · $0.04 on NO hit
Theta progression · θ ∝ σ / √t_remainingθ_now = 0.136 pp/day
now870.52d left0.136 pp/day×1.00
−25%652.89d left0.157 pp/day×1.15
−50%435.26d left0.192 pp/day×1.41
−75%217.63d left0.271 pp/day×2.00
−90%87.05d left0.429 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
1 up bars · 0 down · best 0.10% · worst 0.00% · typical |Δ| 0.004%
§10 · Equity curve & underwater drawdown
final equity 1.0010 (0.10%) · max DD 0.00% · time-under-water 0/25 bars
§11 · Rolling-window statistics (w = 6 bars)
latest 0.000 · range [0.00, 38.21] · μ 4.022 · positive Sharpe = excess-return-per-risk earned by buying-and-holding through this window
latest 0.00% · range [0.00%, 3.82%] · μ 0.40% · σ̂ scaled to annualised (×√8760)
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)
2 of 5 REJECT · mixed evidence2 reject·3 pass·1 n/a·α = 0.05
Jarque-Bera
REJECT H₀***H₀: Δp ~ Normal(μ, σ²)
STATISTIC
672.0000
p-VALUE (log scale)
< 0.0001
Ljung-Box(h=5)
FAIL TO REJECTnsH₀: No serial autocorrelation up to lag 5
STATISTIC
0.0612
p-VALUE (log scale)
0.9997
Dickey-Fuller (τ_μ)
REJECT H₀***H₀: p has a unit root (non-stationary)
STATISTIC
-4.4907
p-VALUE (log scale)
0.0004
Wald-Wolfowitz runs
N/An/aH₀: Sign sequence of Δ is random
STATISTIC
—
p-VALUE (log scale)
—
KPSS (μ stationarity)
FAIL TO REJECTnsH₀: p IS level-stationary
STATISTIC
0.3741
p-VALUE (log scale)
0.0883
Variance ratio q=3
FAIL TO REJECTnsH₀: Δp is a random walk · VR = 1
STATISTIC
-1.0101
p-VALUE (log scale)
0.3125
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 ≈ 12.00h (freq 0.083) · concentrates 8.3% of total energy · Σ|X̂|²/n = 5.000e-7
▸ Depth section using sovereign-store price series (1089 bars · effective 1752616 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 870.5 d · σ/bar 0.003pp · expected |Δp| over horizon 0.44ppterminal variance p(1−p) = 0.0416 · n = 1089✓ n = 1089
μ per bar
-0.000pp
average Δp · drift
σ per bar
0.003pp
one-bar volatility · logit-free
Per-day movedaily
0.01pp
σ × √24
Per-horizon move871d
0.44pp
σ × √20892.36467361111
Terminal variancebinary
0.0416
p(1−p) at resolution
Current pricep
4.3¢
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 0.01pp · ES₉₅ 0.01pp · method parametric · drift-correcteddrift -0.000pp/bar · quantised: yes · median step 0.10pp · unique ratio 0.00✓ n = 1089
VaR 95%
0.01pp
1.645·σ (parametric) of Δp
ES 95%
0.01pp
mean of the tail
Max drawdown
2.2pp
peak 4.5¢ → trough 4.3¢
Median step
0.10pp
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
4.3%
= price
Decimal oddsEU
22.989
total return per $1
AmericanUS
+2199
$100 wins $2199
FractionalUK
21.99 / 1
profit per $1 risked
Profit per $100stake
+$2198.85
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)
0.258 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.258 bit
Δ +0.000 bit vs market
Surprise · YES−log₂ p
4.52 bit
self-information
Surprise · NO−log₂(1−p)
0.06 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
91031279171981959197361710127213577102576826515163085396576756946418341946256- NO token ID
18494065527924073750217237765784380365430319396356251245973222791140100738948- Snapshot fetched
- 2026-06-20 11:37:56 UTC
- Snapshot age
- 10.3s
- History points
- 25 CLOB mids
- Page rendered
- 2026-06-20 11:38:07 UTC
- Storage policy
- no persistence — fetched on every request
- SHA-256 attestation
4611a208a9fb720b6aa39a0c4c957f7ce8d8402f381cfd7defa5016f932dc6bd· 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 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
0.043500
(best bid + best ask) / 2
Spread
229.9bp
(bestAsk − bestBid) / mid
Imbalance (whole book)
-0.622
ask-heavy
Imbalance (top-5)
+0.348
bid-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-pete-buttigieg-win-the-2028-democratic-presidential-nomination-687/slippage?size=10000&side=buy
| Side | Notional | Avg fill | Slippage | Worst fill | Levels | Status |
|---|---|---|---|---|---|---|
| BUY | $1.00K | 0.044000 | 114.94bp | 0.044000 | 1 | FILLED |
| BUY | $10.00K | 0.053618 | 2325.93bp | 0.068000 | 16 | FILLED |
| BUY | $100.00K | 0.220652 | 40724.59bp | 0.640000 | 68 | FILLED |
| SELL | $1.00K | 0.041437 | 474.23bp | 0.040000 | 4 | FILLED |
| SELL | $10.00K | 0.037225 | 1442.55bp | 0.031000 | 13 | FILLED |
| SELL | $100.00K | 0.006547 | 8494.88bp | 0.001000 | 24 | PARTIAL |
Risk metrics
▸ sovereign store · 1,089 barsperiods/year ≈ 1.75MRealized vol (annualised)
91.22%
σ per bar = 0.000689
Mean return (annualised)
-3661.20%
μ per bar = -0.000021
Sharpe (rf=0)
-40.14
annualised; risk-free assumed zero
Max drawdown
2.25%
peak 0.04 → trough 0.04 over 3 bars
/api/asset/pm-will-pete-buttigieg-win-the-2028-democratic-presidential-nomination-687/risk · same metrics, JSON