POLYMARKET · PREDICTION MARKET · POLITICS

Will Abelardo de la Espriella place 1st in Bogotá in the second round of the 2026 Colombia presidential election?

YES · live

58.5¢

NO · live

41.5¢

▸ Advanced metrics · M2M bundle

polymarket · will-abelardo-de-la-espriella-place-1st-in-bogota-in-the-second-round-of-the-2026-colombia-presidential-election-20260604170547991 · fresh · feed 9s old

24h sparkline · 60 pts▼ —

realized vol (ann.)

59.67%

max drawdown

1.71%

sharpe

—

ulcer index

1.50%

RMS drawdown

pain index

1.37%

mean drawdown

mod. VaR 95%

0.00%

Cornish-Fisher

martin ratio

—

ret / ulcer

CDaR 95%

1.71%

cond. drawdown

gain/pain

1.00

Σgain / Σ|loss|

sterling

—

ret / CDaR

omega (θ=0)

1.00

upside/downside

roll spread

0.0 bps

implied (price-only)

bars used

986

store

spread

—

24h Δ

—

flow lean

—

carry

flat

signalNEUTRALconfidence 20%

Same bundle via M2M API:

/api/m2m/pm-will-abelardo-de-la-espriella-place-1st-in-bogota-in-the-second-round-of-the-2026-colombia-presidential-election-20260604170547991/bundle

· venue execution: polymarket →

LIVEPOLL0SRCFRESH8.9s⏱--:--:-- UTCNEXT8.0sUP0s--:--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

58.5¢

NO · live

41.5¢

YES price · live 24h

25 ticks · last 58.50¢

YES / NO split · live

Σ 100.00% · fair

Σ-sides total = 100.00% (tight rounding)

H(p) entropy = 0.979 / 1.00 bits (98%) · max uncertainty (~50/50)

YES

58.5%58.5¢1.71×▬ +0.00pp

41.5%41.5¢2.41×▬ +0.00pp

Σ 100.00% · arb gap 0.00pp

Per-tick activity · |Δp| in basis points · live

Σ 1000bp moved · peak 300bp · n=24 ticks

Live numerics · pulse on poll

LIVE NUMERICS8 metrics·POLL 0

⏱snapshot age

8.9s

▲YES mid

58.50¢ (58.50%)

▼NO mid

41.50¢ (41.50%)

ΣΣ sides

100.00%

⚖arb gap

0.000pp

$24h vol $

$33.3k

≋liquidity $

$48.4k

◳history points

25 ticks (live)

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

YES price · CLOB mid

25 YES observations from clob.polymarket.com · last 58.50¢

NO price · CLOB mid

25 NO observations from clob.polymarket.com · last 41.50¢

§2 · Distribution of Δp

Histogram of hourly increments

n=24

Q-Q plot · standardised Δp vs N(0,1)

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 MEAN59.94¢95% CI: [59.40¢, 60.48¢]

σ STD DEV1.39ppσ² = 1.923 · CV = 2.31%

med MEDIAN60.50¢Q₁ 59.50¢ · Q₃ 60.50¢

FIVE-NUMBER SUMMARY · BOX PLOTrange 6.00pp · IQR 1.00pp (1.349σ→1.87pp)

SKEWNESS · G₁-0.241approximately symmetric

−3−10+1+3

EXCESS KURTOSIS · G₂0.381mesokurtic · normal-like

−30+2+4+6

μ ↔ medianμ < med · left-tailed|μ−med| / σ = 0.40

σ × 1.349 ↔ IQRdiverges from normalratio = 1.87

range ↔ σwide tails (range > 4σ)range / σ = 4.33

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) -0.33 + ADF rejected

ρ(1) AUTOCORR-0.332within white-noise band

ρ(2) AUTOCORR+0.034lag-2 not significant

H · HURST EXPONENT0.811strongly persistent

OLS TREND · t-STAT-5.525significant @ α=0.05

HURST EXPONENT [0, 1]strongly persistent · H = 0.811

H = 0.811STRONGLY 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

OLS TREND · t-STAT · [-5, +5]SIGNIFICANT @ 1% (|t|=5.53)

−5 reject−1.960 retain H₀+1.96+5 reject

REGIME CLASSIFICATIONMEAN-REVERTING · ρ(1) -0.33 + ADF rejectedfrom Hurst + ρ(1) joint diagnosis

PREDICTABILITY · score 0.95very high · strong structure|ρ(1)| + 2·|H − 0.5| heuristic

TREND SIGNIFICANCESIGNIFICANT @ 1% (|t|=5.53)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 ID2446454

SLUGwill-abelardo-de…604170547991

CATEGORYPolitics

TWO-SIDED PRICINGFAVOURS YES (59¢)

PRIMARY · YES58.50¢implied prob 58.50% · decimal odds 1.71×

COUNTER · NO41.50¢implied prob 41.50% · decimal odds 2.41×

58.50¢

41.50¢

Σ-SIDES ARBITRAGE TESTPERFECT · ARB-FREE Σ=100.00%

0%50%100% · target110%

Σ = 100.00% · |1 − Σ| = 0.000pp

24H ACTIVITY · LIQUIDITYACTIVE

24H VOLUME33.34k USD 24h

LIQUIDITY48.37k USD

MARKET QUALITYPERFECT · ARB-FREE Σ=100.00%|1−Σ| ≤ 0.5pp ⇒ fair · > 2pp ⇒ inefficient

PRICING SKEWFAVOURS YES (59¢)|primary − counter| = 0.170 · entropy 0.979 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

Probability scale (YES)

0%25%50%
fair75%100%

Implied decimal odds

YES1.71×(59¢)NO2.41×(42¢)

Kelly bet-size (% of bankroll) K* = 0.00%

K* full

0.00%

½K half

0.00%

¼K quarter

0.00%

Entropy H(p̂) = 0.979 bits (98% of max) · maximum uncertainty (~50/50)

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 · MEDIUMresolves 2026-06-22 03:59 UTC

1days

16hrs

08min

YES →$1.00(P = 58.5%)

NO →$0.00(P = 41.5%)

current: $0.5850 · expected return per side: $0.42 on YES hit · $0.58 on NO hit

Theta progression · θ ∝ σ / √t_remainingθ_now = 6.794 pp/day

now1.67d left

6.794 pp/day×1.00

−25%1.25d left

7.845 pp/day×1.15

−50%20.07h left

9.608 pp/day×1.41

−75%10.03h left

13.588 pp/day×2.00

−90%4.01h left

21.485 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

2 up bars · 4 down · best 3.00% · worst -3.00% · typical |Δ| 0.417%

§10 · Equity curve & underwater drawdown

Cumulative compounded return + running peak-to-trough

final equity 0.9791 (-2.09%) · max DD -5.88% · time-under-water 21/25 bars

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

Rolling annualised Sharpe ratio · green positive · red negative

latest -20.722 · range [-85.44, 0.00] · μ -26.280 · positive Sharpe = excess-return-per-risk earned by buying-and-holding through this window

Rolling annualised volatility (%)

FAIL TO REJECTns

H₀: Δp is a random walk · VR = 1

STATISTIC

-1.3580

p-VALUE (log scale)

0.1745

10⁻⁴10⁻³10⁻²10⁻¹1

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

dominant period ≈ 2.67h (freq 0.375) · concentrates 16.8% of total energy · Σ|X̂|²/n = 1.167e-3

▸ Depth section using sovereign-store price series (986 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 1.7 d · σ/bar 0.045pp · expected |Δp| over horizon 0.29ppterminal variance p(1−p) = 0.2428 · n = 986✓ n = 986

μ per bar

+0.000pp

average Δp · drift

σ per bar

0.045pp

one-bar volatility · logit-free

Per-day movedaily

0.22pp

σ × √24

Per-horizon move2d

0.29pp

σ × √40.13825722222222

Terminal variancebinary

0.2428

p(1−p) at resolution

Current pricep

58.5¢

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

VaR · ES · max drawdown

VaR₉₅ 0.07pp · ES₉₅ 0.09pp · method parametric · drift-correcteddrift +0.000pp/bar · quantised: yes · median step 0.50pp · unique ratio 0.00✓ n = 986

VaR 95%

0.07pp

1.645·σ (parametric) of Δp

ES 95%

0.09pp

mean of the tail

Max drawdown

1.7pp

peak 58.5¢ → trough 57.5¢

Median step

0.50pp

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

58.5%

= price

Decimal oddsEU

1.709

total return per $1

AmericanUS

-141

risk $141 to win $100

FractionalUK

0.71 / 1

profit per $1 risked

Profit per $100stake

+$70.94

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

Binary entropy · uncertainty as bits of information

Market entropyH(p)

0.979 bit

max 1.0 at p = 0.5

Your entropyH(q)

0.979 bit

Δ +0.000 bit vs market

Surprise · YES−log₂ p

0.77 bit

self-information

Surprise · NO−log₂(1−p)

1.27 bit

self-information

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: 7842998641854640467498864847927196666887026414217538383618059089010287738821
NO token ID: 73377810827384780824303947274695960562511250713318827027771148534840046107237
Snapshot fetched: 2026-06-20 11:50:32 UTC
Snapshot age: 8.9s
History points: 25 CLOB mids
Page rendered: 2026-06-20 11:50:42 UTC
Storage policy: no persistence — fetched on every request
SHA-256 attestation: bf3ef74826b80550b5c6b272e6e2beea72de0d3e3de3e829c1fc5ce0d5338072 · deterministic hash of source snapshot
Open data licence: CC0 / public domain

§∞-2 · Related markets · explore more

HL PREDSpain88.5¢HL PREDEcuador86.5¢HL PREDBelgium67.7¢POLYMARKETWill USA win the 2026 FIFA World Cup?3¢POLYMARKET Iran agrees to end enrichment of uranium by June 30?5¢POLYMARKETWill Egypt win the 2026 FIFA World Cup?0¢HL PERPBTC-USD perpetual$63,738 HL PERPHYPE-USD perpetual$71.23 HL PERPETH-USD perpetual$1,728.8

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

Market depth

▸ live order book · Polymarket YES

Depth within 1bp

bid $0 · ask $0

Depth within 5bp

bid $0 · ask $0

Depth within 10bp

bid $0 · ask $0

Depth within 50bp

bid $0 · ask $0

Mid price

0.585000

(best bid + best ask) / 2

Spread

170.9bp

(bestAsk − bestBid) / mid

Imbalance (whole book)

-0.180

ask-heavy

Imbalance (top-5)

-0.438

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-abelardo-de-la-espriella-place-1st-in-bogota-in-the-second-round-of-the-2026-colombia-presidential-election-20260604170547991/slippage?size=10000&side=buy

Side	Notional	Avg fill	Slippage	Worst fill	Levels	Status
BUY	$1.00K	0.599483	247.58bp	0.600000	2	FILLED
BUY	$10.00K	0.606961	375.39bp	0.620000	4	FILLED
BUY	$100.00K	0.816125	3950.86bp	0.960000	36	FILLED
SELL	$1.00K	0.563914	360.45bp	0.560000	3	FILLED
SELL	$10.00K	0.409696	2996.66bp	0.230000	26	FILLED
SELL	$100.00K	0.092525	8418.38bp	0.010000	44	PARTIAL

Risk metrics

▸ sovereign store · 986 barsperiods/year ≈ 1.75M

Realized vol (annualised)

102.80%

σ per bar = 0.000776

Mean return (annualised)

0.00%

μ per bar = 0.000000

Sharpe (rf=0)

0.00

annualised; risk-free assumed zero

Max drawdown

1.71%

peak 0.58 → trough 0.57 over 93 bars

/api/asset/pm-will-abelardo-de-la-espriella-place-1st-in-bogota-in-the-second-round-of-the-2026-colombia-presidential-election-20260604170547991/risk · same metrics, JSON