POLYMARKET · PREDICTION MARKET · POLITICS

Will Keiko Fujimori win the 2026 Peruvian presidential election?

YES · live
98.8¢
NO · live
1.3¢

▸ Advanced metrics · M2M bundle

polymarket · will-keiko-fujimori-win-the-2026-peruvian-presidential-election · fresh · feed 0s old
realized vol (ann.)
—
max drawdown
—
sharpe
—
ulcer index
—
RMS drawdown
pain index
—
mean drawdown
mod. VaR 95%
—
Cornish-Fisher
martin ratio
—
ret / ulcer
CDaR 95%
—
cond. drawdown
gain/pain
—
Σgain / Σ|loss|
sterling
—
ret / CDaR
omega (θ=0)
—
upside/downside
roll spread
—
implied (price-only)
bars used
0
insufficient
spread
—
24h Δ
—
flow lean
—
carry
flat
signalNEUTRALconfidence 0%
  • insufficient history for risk metrics — directional read only
Same bundle via M2M API: /api/m2m/pm-will-keiko-fujimori-win-the-2026-peruvian-presidential-election/bundle · venue execution: polymarket →
LIVEPOLL0SRCFRESH3ms⏱--:--:-- 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
98.8¢
NO · live
1.3¢
YES price · live 24h
n=25 · μ=0.9827 · σ=0.0026 · range [0.9760, 0.9880] · R²=0.288▲ RISING +0.36%σ LOW 0.27%LAST 0.98750.98800.98500.98200.97900.9760μ = 0.9827max 0.9880min 0.9760dataMA(5)OLS R²=0.29μ lineμ ± σ bandmaxminlive endpoint
25 ticks · last 98.75¢
YES / NO split · live
YES 98.8%NO 1.3%YES98.8%98.75¢ · odds 1/1.01
Σ 100.00% · fair
Σ-sides total = 100.00% (tight rounding)
H(p) entropy = 0.097 / 1.00 bits (10%) · informative — one side favoured
YES
98.8%98.8¢1.01×▬ +0.00pp
NO
1.3%1.3¢80.00×▬ +0.00pp
Σ 100.00% · arb gap 0.00pp
Per-tick activity · |Δp| in basis points · live
n=24 · Σ=325 · μ=13.5 · σ=21.0 · CV=1.55BURSTY · concentratedcumulative energy ↗ · 50% by h=7015304560μ = 146050%h1h5h9h13h17h21#1 peak#2-3> μactivequietμ linecum energy
Σ 325bp moved · peak 60bp · n=24 ticks
Live numerics · pulse on poll
LIVE NUMERICS8 metrics·POLL 0
⏱snapshot age
3ms
▲YES mid
98.75¢ (98.75%)
▼NO mid
1.25¢ (1.25%)
ΣΣ sides
100.00%
⚖arb gap
0.000pp
$24h vol $
$149.2k
≋liquidity $
$147.7k
◳history points
25 ticks (live)

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

YES price · CLOB mid
n=25 · μ=0.9827 · σ=0.0026 · range [0.9760, 0.9880] · R²=0.288▲ RISING +0.36%σ LOW 0.27%LAST 0.98750.98800.98500.98200.97900.9760μ = 0.9827max 0.9880min 0.9760dataMA(5)OLS R²=0.29μ lineμ ± σ bandmaxmin
25 YES observations from clob.polymarket.com · last 98.75¢
NO price · CLOB mid
n=25 · μ=0.0173 · σ=0.0026 · range [0.0120, 0.0240] · R²=0.288▼ FALLING -21.87%σ EXTREME 15.18%LAST 0.01250.02400.02100.01800.01500.0120μ = 0.0173max 0.0240min 0.0120dataMA(5)OLS R²=0.29μ lineμ ± σ bandmaxmin
25 NO observations from clob.polymarket.com · last 1.25¢

§2 · Distribution of Δp

Histogram of hourly increments
n=24 · 10 bins · μ=0.0003 · σ=0.0023 · skew=0.12 (symmetric) · kurt=1.34 (leptokurtic (fat tails))1296301-0.54ppbin -0.54pp · n=1 · 8.3% peakbin -0.54pp · n=1 · 8.3% peak1-0.42ppbin -0.42pp · n=1 · 8.3% peakbin -0.42pp · n=1 · 8.3% peak-0.30pp1-0.18ppbin -0.18pp · n=1 · 8.3% peakbin -0.18pp · n=1 · 8.3% peak6-0.06ppbin -0.06pp · n=6 · 50.0% peakbin -0.06pp · n=6 · 50.0% peak120.06ppbin 0.06pp · n=12 · 100.0% peakbin 0.06pp · n=12 · 100.0% peak0.18pp0.30pp10.42ppbin 0.42pp · n=1 · 8.3% peakbin 0.42pp · n=1 · 8.3% peak20.54ppbin 0.54pp · n=2 · 16.7% peakbin 0.54pp · n=2 · 16.7% 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=0.42 · kurt=1.89 · near 8 / mid 16 / far 0 · OLS slope=0.91 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=25APPROXIMATELY NORMAL · WELL-BEHAVED
μ MEAN98.27¢95% CI: [98.16¢, 98.37¢]
σ STD DEV0.26ppσ² = 0.069 · CV = 0.27%
med MEDIAN98.25¢Q₁ 98.20¢ · Q₃ 98.35¢
FIVE-NUMBER SUMMARY · BOX PLOTrange 1.20pp · IQR 0.15pp (1.349σ→0.36pp)
min 97.60¢Q₁ 98.20¢med 98.25¢Q₃ 98.35¢max 98.80¢μ
SKEWNESS · G₁-0.106approximately symmetric
−3−10+1+3
EXCESS KURTOSIS · G₂0.651mesokurtic · normal-like
−30+2+4+6
μ ↔ median≈ equal · symmetric|μ−med| / σ = 0.06
σ × 1.349 ↔ IQRdiverges from normalratio = 2.37
range ↔ σwide tails (range > 4σ)range / σ = 4.56
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) -0.28 + ADF rejected
ρ(1) AUTOCORR-0.283within white-noise band
ρ(2) AUTOCORR+0.042lag-2 not significant
H · HURST EXPONENT0.729strongly persistent
OLS TREND · t-STAT+3.049significant @ α=0.05
HURST EXPONENT [0, 1]strongly persistent · H = 0.729
H = 0.729STRONGLY PERSISTENT
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=1-0.283k=2+0.042k=3-0.340k=4+0.227k=5-0.0310+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|=3.05)
−5 reject−1.960 retain H₀+1.96+5 reject
REGIME CLASSIFICATIONMEAN-REVERTING · ρ(1) -0.28 + ADF rejectedfrom Hurst + ρ(1) joint diagnosis
PREDICTABILITY · score 0.74very high · strong structure|ρ(1)| + 2·|H − 0.5| heuristic
TREND SIGNIFICANCESIGNIFICANT @ 1% (|t|=3.05)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 ID947269
SLUGwill-keiko-fujim…ial-election
CATEGORYPolitics
TWO-SIDED PRICINGFAVOURS YES (99¢)
PRIMARY · YES98.75¢implied prob 98.75% · decimal odds 1.01×
COUNTER · NO1.25¢implied prob 1.25% · decimal odds 80.00×
98.75¢
1.25¢
Σ-SIDES ARBITRAGE TESTPERFECT · ARB-FREE Σ=100.00%
0%50%100% · target110%
Σ = 100.00% · |1 − Σ| = 0.000pp
24H ACTIVITY · LIQUIDITYDEEP
24H VOLUME149.21k USD 24h
LIQUIDITY147.67k USD
MARKET QUALITYPERFECT · ARB-FREE Σ=100.00%|1−Σ| ≤ 0.5pp ⇒ fair · > 2pp ⇒ inefficient
PRICING SKEWFAVOURS YES (99¢)|primary − counter| = 0.975 · entropy 0.097 bits
LIQUIDITY DEPTHDEEP100k+ 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 98.8%NO 1.3%YES p̂98.8%H = 0.097 / 1.00 bits
Probability scale (YES)
0%25%50%
fair75%100%
Implied decimal odds
YES1.01×(99¢)NO80.00×(1¢)
Kelly bet-size (% of bankroll) K* = 0.00%
K* full
0.00%
½K half
0.00%
¼K quarter
0.00%
Entropy H(p̂) = 0.097 bits (10% 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 0.60% · worst -0.60% · typical |Δ| 0.14%MILD BULLISH +0.35%BEST+0.60%4hWORST-0.60%3hTYPICAL |Δ|0.14%mean absoluteCUMULATIVE+0.35%Σ signed ΔSTREAK▬ 0flat-runASIA · 00-08 UTCμ -0.08% · Σ -0.55%EUROPE · 08-16 UTCμ +0.06% · Σ +0.45%US · 16-24 UTCμ +0.06% · Σ +0.45%CUMULATIVE Δ PATH · final +0.35%+0.40%-0.80%-0.05% · 1h-0.05% · 1h-0.05%1h-0.15% · 2h-0.15% · 2h-0.15%2h-0.60% · 3h-0.60% · 3h-0.60%3h▼ WORST0.60% · 4h0.60% · 4h0.60%4h★ BEST-0.05% · 5h-0.05% · 5h-0.05%5h0.10% · 6h0.10% · 6h0.10%6h-0.40% · 7h-0.40% · 7h-0.40%7h0.10% · 8h0.10% · 8h0.10%8h0.00% · 9h0.00% · 9h·9h0.40% · 10h0.40% · 10h0.40%10h0.00% · 11h0.00% · 11h·11h0.00% · 12h0.00% · 12h·12h0.00% · 13h0.00% · 13h·13h0.00% · 14h0.00% · 14h·14h-0.05% · 15h-0.05% · 15h-0.05%15h-0.05% · 16h-0.05% · 16h-0.05%16h0.00% · 17h0.00% · 17h·17h0.00% · 18h0.00% · 18h·18h0.00% · 19h0.00% · 19h·19h-0.05% · 20h-0.05% · 20h-0.05%20h0.00% · 21h0.00% · 21h·21h0.60% · 22h0.60% · 22h0.60%22h-0.05% · 23h-0.05% · 23h-0.05%23h0.00% · 24h0.00% · 24h·24hTIME PATTERNUS-led (+0.45%)RUNSup max 1 · down max 3BREADTH21% up · 38% down · 42% flat
5 up bars · 9 down · best 0.60% · worst -0.60% · typical |Δ| 0.135%

§10 · Equity curve & underwater drawdown

Cumulative compounded return + running peak-to-trough
EQUITY & DRAWDOWN ANALYSIS · n=25 barsPROFITABLE +0.34%FINAL+0.34%MAX DD-0.80%RECOVERYONGOING · 21 barsMAX RUN-UP+0.39%UNDERWATER23/25 (92%)STREAK▬ 0EQUITY CURVE · end 1.0034 · peak 1.0039 · range [0.9920, 1.0039]1.00390.9920break-even = 1★ PEAK 1.0039UNDERWATER DRAWDOWN · max -0.80% · shallow0%-0.80%▼ TROUGH -0.80%TOP DRAWDOWN PERIODS · 2 total#1 -0.80%bar 2-22 · 21 bars · recovered#2 -0.05%bar 24-25 · 2 bars · ONGOINGDD SEVERITYshallow (max -0.80%)RECOVERYongoing · 24 barsTIME UNDER WATER92% of session · 23/25 bars
final equity 1.0034 (0.34%) · max DD -0.80% · time-under-water 23/25 bars

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

Rolling annualised Sharpe ratio · green positive · red negative
n=19 · +10 / −9 (53% positive) · μ=-8.55 · σ=42.90MIXED EDGELAST 30.67 (+0.91σ vs μ)85.4442.720.00-42.72-85.44μ = -8.55-6.03-6.03-18.66-18.66-9.23-9.2316.9016.908.998.9912.0812.086.096.0948.6848.6838.2138.2132.3932.39-60.42-60.42-60.42-60.42-60.42-60.42-60.42-60.42-85.44-85.44-60.42-60.4234.3434.3430.6730.6730.6730.67v > 0 · positivev < 0 · negativeμ mean lineμ ± σ bandlatest bar (outlined)
latest 30.671 · range [-85.44, 48.68] · μ -8.548 · positive Sharpe = excess-return-per-risk earned by buying-and-holding through this window
Rolling annualised volatility (%)
n=19 · μ=18.3912 · σ=13.0754 · range [2.4166, 39.5339] · R²=0.378▼ FALLING -34.50%σ EXTREME 71.10%LAST 23.800839.533930.254620.975311.69592.4166μ = 18.3912max 39.5339min 2.4166dataMA(3)OLS R²=0.38μ lineμ ± σ bandmaxmin
latest 23.80% · range [2.42%, 39.53%] · μ 18.39% · σ̂ scaled to annualised (×√8760)
Rolling lag-1 autocorrelation ρ(1)
n=19 · +5 / −14 (26% positive) · μ=-0.131 · σ=0.250MEAN-REVERSIONLAST -0.243 (-0.45σ vs μ)0.5230.2610.000-0.261-0.523μ = -0.131-0.402-0.402-0.398-0.398-0.523-0.523-0.199-0.199-0.238-0.238-0.253-0.253-0.148-0.148-0.314-0.314-0.233-0.233-0.024-0.0240.4170.4170.1670.1670.1670.1670.1670.1670.1670.167-0.333-0.333-0.012-0.012-0.256-0.256-0.243-0.243v > 0 · positivev < 0 · negativeμ mean lineμ ± σ bandlatest bar (outlined)
latest -0.243 · |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
1 of 6 REJECT · mixed evidence1 reject·5 pass·α = 0.05
𝒩

Jarque-Bera

REJECT H₀*

H₀: Δp ~ Normal(μ, σ²)

STATISTIC
7.8588
p-VALUE (log scale)
0.0197
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
7.2997
p-VALUE (log scale)
0.1981
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
-2.2167
p-VALUE (log scale)
0.2055
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
0.9591
p-VALUE (log scale)
0.3375
α
10⁻⁴10⁻³10⁻²10⁻¹1
p ≥ α · null retainedsigns appear random (9 runs)
χ

KPSS (μ stationarity)

FAIL TO REJECTns

H₀: p IS level-stationary

STATISTIC
0.4558
p-VALUE (log scale)
0.0531
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
-1.0025
p-VALUE (log scale)
0.3161
α
10⁻⁴10⁻³10⁻²10⁻¹1
p ≥ α · null retainedVR 0.695 ≈ 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=7.36e-6 · top T=2.00h (35.7%) · top-3 cover 62.1%1 SIGNIFICANT CYCLEcumulative energy ↗ (1 bin above 2× noise)3.2e-52.4e-51.6e-57.9e-60.0e+0μ noise floor2× noise (significance)period 24.0 · power 2.19e-7 · 0.2% energyperiod 24.0 · power 2.19e-7 · 0.2% energyperiod 12.0 · power 4.94e-6 · 5.6% energyperiod 12.0 · power 4.94e-6 · 5.6% energyperiod 8.0 · power 1.90e-6 · 2.1% energyperiod 8.0 · power 1.90e-6 · 2.1% energyperiod 6.0 · power 1.28e-5 · 14.4% energyperiod 6.0 · power 1.28e-5 · 14.4% energyperiod 4.8 · power 4.46e-6 · 5.0% energyperiod 4.8 · power 4.46e-6 · 5.0% energyperiod 4.0 · power 4.68e-6 · 5.3% energyperiod 4.0 · power 4.68e-6 · 5.3% energyperiod 3.4 · power 5.53e-6 · 6.3% energyperiod 3.4 · power 5.53e-6 · 6.3% energyperiod 3.0 · power 9.45e-6 · 10.7% energyperiod 3.0 · power 9.45e-6 · 10.7% energyperiod 2.7 · power 1.96e-6 · 2.2% energyperiod 2.7 · power 1.96e-6 · 2.2% energyperiod 2.4 · power 3.54e-7 · 0.4% energyperiod 2.4 · power 3.54e-7 · 0.4% energyperiod 2.2 · power 1.06e-5 · 12.0% energyperiod 2.2 · power 1.06e-5 · 12.0% energyperiod 2.0 · power 3.15e-5 · 35.7% energyperiod 2.0 · power 3.15e-5 · 35.7% energy50% by T=2.7h#1 dominantT=2.00h#2T=6.00h#3T=2.18hT=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 ≈ 2.00h (freq 0.500) · concentrates 35.7% of total energy · Σ|X̂|²/n = 8.838e-5

§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 0.251pp · expected |Δp| over horizon 0.62ppterminal variance p(1−p) = 0.0123 · n = 25⚠ low confidence · n < 100
μ per bar
+0.015pp
average Δp · drift
σ per bar
0.251pp
one-bar volatility · logit-free
Per-day movedaily
1.23pp
σ × √24
Per-horizon move0d
0.62pp
σ × √6
Terminal variancebinary
0.0123
p(1−p) at resolution
Current pricep
98.8¢
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 0.38pp · ES₉₅ 0.51pp · method empirical · drift-correcteddrift +0.015pp/bar · quantised: no · median step 0.05pp · unique ratio 0.44⊘ disabled · n < 30
VaR 95%
0.38pp
5th percentile of Δp
ES 95%
0.51pp
mean of the tail
Max drawdown
0.8pp
peak 98.4¢ → trough 97.6¢
Median step
0.05pp
price bucket granularity
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
98.8%
= price
Decimal oddsEU
1.013
total return per $1
AmericanUS
-7900
risk $7900 to win $100
FractionalUK
0.01 / 1
profit per $1 risked
Profit per $100stake
+$1.27
clean dollar framing
-1000-5000+500+1000020406080100you · 98.8%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)
0.097 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.097 bit
Δ +0.000 bit vs market
Surprise · YES−log₂ p
0.02 bit
self-information
Surprise · NO−log₂(1−p)
6.32 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
64703998724474008677827057135436893758254552168142785204605792475717308499827
NO token ID
92827417009887627656279362525317849309821905918650547490799438436173703158107
Snapshot fetched
2026-06-14 19:08:03 UTC
Snapshot age
3ms
History points
25 CLOB mids
Page rendered
2026-06-14 19:08:03 UTC
Storage policy
no persistence — fetched on every request
SHA-256 attestation
74ad728ba5a1e99d4addbd4aefbc0f93580fe50b37151818e5ea5c989e4287b6 · deterministic hash of source snapshot
Open data licence
CC0 / public domain

§∞-2 · Related markets · explore more

HL PREDGermany100.0¢HL PREDSpain89.5¢HL PREDUruguay66.9¢POLYMARKETWill Curaçao win on 2026-06-14?0¢POLYMARKETWill Australia win the 2026 FIFA World Cup?0¢POLYMARKETWill Scotland win the 2026 FIFA World Cup?0¢HL PERPBTC-USD perpetual$63,768.5HL PERPETH-USD perpetual$1,661.65HL PERPHYPE-USD perpetual$60.36

Also see: /arb opportunities · RSS feed · more in Politics

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
$6.66K
bid $6.56K · ask $100
Depth within 50bp
$199.89K
bid $9.40K · ask $190.49K
Mid price
0.987500
(best bid + best ask) / 2
Spread
10.1bp
(bestAsk − bestBid) / mid
Imbalance (whole book)
-0.059
ask-heavy
Imbalance (top-5)
-0.785
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-will-keiko-fujimori-win-the-2026-peruvian-presidential-election/slippage?size=10000&side=buy

SideNotionalAvg fillSlippageWorst fillLevelsStatus
BUY$1.00K0.98890014.18bp0.9890002FILLED
BUY$10.00K0.98969422.21bp0.9900003FILLED
BUY$100.00K0.99084333.85bp0.9910004FILLED
SELL$1.00K0.9870005.06bp0.9870001FILLED
SELL$10.00K0.98635511.60bp0.9810003FILLED
SELL$100.00K0.972107155.88bp0.93200035FILLED

Risk metrics

▸ upstream candles · 25 bars
Realized vol (annualised)
—
σ per bar = 0.002562
Mean return (annualised)
—
μ per bar = 0.000148
Sharpe (rf=0)
—
annualised; risk-free assumed zero
Max drawdown
0.81%
peak 0.98 → trough 0.98 over 3 bars

/api/asset/pm-will-keiko-fujimori-win-the-2026-peruvian-presidential-election/risk · same metrics, JSON