POLYMARKET · PREDICTION MARKET · POLITICS

Will Flávio Bolsonaro win the 2026 Brazilian presidential election?

YES · live

25.1¢

NO · live

75.0¢

▸ Advanced metrics · M2M bundle

polymarket · will-flvio-bolsonaro-win-the-2026-brazilian-presidential-election · fresh · feed 2s old

24h 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

704

store

spread

—

24h Δ

—

flow lean

—

carry

flat

signalNEUTRALconfidence 20%

Same bundle via M2M API: /api/m2m/pm-will-flvio-bolsonaro-win-the-2026-brazilian-presidential-election/bundle · venue execution: polymarket →

LIVEPOLL0SRCFRESH2.4s⏱--:--:-- 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

25.1¢

NO · live

75.0¢

YES price · live 24h

25 ticks · last 25.05¢

YES / NO split · live

Σ 100.00% · fair

Σ-sides total = 100.00% (tight rounding)

H(p) entropy = 0.812 / 1.00 bits (81%) · high uncertainty

YES

25.1%25.1¢3.99×▬ +0.00pp

75.0%75.0¢1.33×▬ +0.00pp

Σ 100.00% · arb gap 0.00pp

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

Σ 340bp moved · peak 140bp · n=24 ticks

Live numerics · pulse on poll

LIVE NUMERICS8 metrics·POLL 0

⏱snapshot age

2.4s

▲YES mid

25.05¢ (25.05%)

▼NO mid

74.95¢ (74.95%)

ΣΣ sides

100.00%

⚖arb gap

0.000pp

$24h vol $

$36.6k

≋liquidity $

$260.6k

◳history points

25 ticks (live)

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

YES price · CLOB mid

25 YES observations from clob.polymarket.com · last 25.05¢

NO price · CLOB mid

25 NO observations from clob.polymarket.com · last 74.95¢

§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 MEAN25.19¢95% CI: [25.05¢, 25.33¢]

σ STD DEV0.36ppσ² = 0.131 · CV = 1.44%

med MEDIAN25.10¢Q₁ 25.05¢ · Q₃ 25.40¢

FIVE-NUMBER SUMMARY · BOX PLOTrange 1.40pp · IQR 0.35pp (1.349σ→0.49pp)

SKEWNESS · G₁-0.478approximately symmetric

−3−10+1+3

EXCESS KURTOSIS · G₂0.118mesokurtic · normal-like

−30+2+4+6

μ ↔ medianμ > med · right-tailed|μ−med| / σ = 0.25

σ × 1.349 ↔ IQRdiverges from normalratio = 1.40

range ↔ σconcentrated (range < 4σ)range / σ = 3.86

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: MARTINGALE · UNPREDICTABLE

ρ(1) AUTOCORR+0.044within white-noise band

ρ(2) AUTOCORR-0.281lag-2 not significant

H · HURST EXPONENT1.007strongly persistent

OLS TREND · t-STAT-0.797fails 5% test

HURST EXPONENT [0, 1]strongly persistent · H = 1.007

H = 1.007STRONGLY 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]NOT SIGNIFICANT (|t|=0.80)

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

REGIME CLASSIFICATIONMARTINGALE · UNPREDICTABLEfrom Hurst + ρ(1) joint diagnosis

PREDICTABILITY · score 1.00very high · strong structure|ρ(1)| + 2·|H − 0.5| heuristic

TREND SIGNIFICANCENOT SIGNIFICANT (|t|=0.80)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 ID601826

SLUGwill-flvio-bolso…ial-election

CATEGORYPolitics

TWO-SIDED PRICINGFAVOURS NO (75¢)

PRIMARY · YES25.05¢implied prob 25.05% · decimal odds 3.99×

COUNTER · NO74.95¢implied prob 74.95% · decimal odds 1.33×

25.05¢

74.95¢

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

0%50%100% · target110%

Σ = 100.00% · |1 − Σ| = 0.000pp

24H ACTIVITY · LIQUIDITYACTIVE

24H VOLUME36.56k USD 24h

LIQUIDITY260.64k USD

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

PRICING SKEWFAVOURS NO (75¢)|primary − counter| = 0.499 · entropy 0.812 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

YES3.99×(25¢)NO1.33×(75¢)

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

K* full

0.00%

½K half

0.00%

¼K quarter

0.00%

Entropy H(p̂) = 0.812 bits (81% of max) · high 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 · DISTANTresolves 2026-10-04 00:00 UTC

105days

13hrs

34min

YES →$1.00(P = 25.1%)

NO →$0.00(P = 75.0%)

current: $0.2505 · expected return per side: $0.75 on YES hit · $0.25 on NO hit

Theta progression · θ ∝ σ / √t_remainingθ_now = 1.776 pp/day

now105.57d left

1.776 pp/day×1.00

−25%79.17d left

2.051 pp/day×1.15

−50%52.78d left

2.512 pp/day×1.41

−75%26.39d left

3.552 pp/day×2.00

−90%10.56d left

5.617 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

1 up bars · 11 down · best 1.40% · worst -0.60% · typical |Δ| 0.142%

§10 · Equity curve & underwater drawdown

Cumulative compounded return + running peak-to-trough

final equity 0.9939 (-0.61%) · max DD -1.29% · time-under-water 21/25 bars

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

Rolling annualised Sharpe ratio · green positive · red negative

latest -38.210 · range [-133.86, 27.12] · μ -51.794 · positive Sharpe = excess-return-per-risk earned by buying-and-holding through this window

Rolling annualised volatility (%)

latest 1.91% · range [1.91%, 67.60%] · μ 23.16% · σ̂ scaled to annualised (×√8760)

Rolling lag-1 autocorrelation ρ(1)

latest -0.033 · |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 5 REJECT · mixed evidence1 reject·4 pass·1 n/a·α = 0.05

𝒩

Jarque-Bera

REJECT H₀***

H₀: Δp ~ Normal(μ, σ²)

STATISTIC

249.3013

p-VALUE (log scale)

< 0.0001

10⁻⁴10⁻³10⁻²10⁻¹1

Ljung-Box(h=5)

FAIL TO REJECTns

H₀: No serial autocorrelation up to lag 5

STATISTIC

5.3263

p-VALUE (log scale)

0.3776

10⁻⁴10⁻³10⁻²10⁻¹1

Dickey-Fuller (τ_μ)

FAIL TO REJECTns

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

STATISTIC

-2.6794

p-VALUE (log scale)

0.0811

10⁻⁴10⁻³10⁻²10⁻¹1

Wald-Wolfowitz runs

N/An/a

H₀: Sign sequence of Δ is random

STATISTIC

—

p-VALUE (log scale)

—

KPSS (μ stationarity)

FAIL TO REJECTns

H₀: p IS level-stationary

STATISTIC

0.1012

p-VALUE (log scale)

0.5000

10⁻⁴10⁻³10⁻²10⁻¹1

Variance ratio q=3

FAIL TO REJECTns

H₀: Δp is a random walk · VR = 1

STATISTIC

-0.2938

p-VALUE (log scale)

0.7689

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 ≈ 3.43h (freq 0.292) · concentrates 17.3% of total energy · Σ|X̂|²/n = 1.388e-4

▸ Depth section using sovereign-store price series (4159 bars · effective 1752518 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 105.6 d · σ/bar 0.034pp · expected |Δp| over horizon 1.71ppterminal variance p(1−p) = 0.1877 · n = 4159✓ n = 4159

μ per bar

-0.001pp

average Δp · drift

σ per bar

0.034pp

one-bar volatility · logit-free

Per-day movedaily

0.17pp

σ × √24

Per-horizon move106d

1.71pp

σ × √2533.5669308333336

Terminal variancebinary

0.1877

p(1−p) at resolution

Current pricep

25.1¢

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 0.06pp · ES₉₅ 0.07pp · method parametric · drift-correcteddrift -0.001pp/bar · quantised: yes · median step 0.05pp · unique ratio 0.01✓ n = 4159

VaR 95%

0.06pp

1.645·σ (parametric) of Δp

ES 95%

0.07pp

mean of the tail

Max drawdown

14.4pp

peak 27.9¢ → trough 23.8¢

Median step

0.05pp

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

25.1%

= price

Decimal oddsEU

3.992

total return per $1

AmericanUS

+299

$100 wins $299

FractionalUK

2.99 / 1

profit per $1 risked

Profit per $100stake

+$299.20

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)

0.812 bit

max 1.0 at p = 0.5

Your entropyH(q)

0.812 bit

Δ +0.000 bit vs market

Surprise · YES−log₂ p

2.00 bit

self-information

Surprise · NO−log₂(1−p)

0.42 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: 109876868437950584369987384406356259939519193117253465815665152916226511121427
NO token ID: 38310927461258927563020508025396887688249787380193911540547071417200646834355
Snapshot fetched: 2026-06-20 10:25:56 UTC
Snapshot age: 2.4s
History points: 25 CLOB mids
Page rendered: 2026-06-20 10:25:59 UTC
Storage policy: no persistence — fetched on every request
SHA-256 attestation: 355c2a8570f5eb1bef4d8922d8d5669af79de3b3f4172c20e61615b8dfdcaa27 · deterministic hash of source snapshot
Open data licence: CC0 / public domain

§∞-2 · Related markets · explore more

HL PREDSpain88.5¢HL PREDEcuador86.3¢HL PREDBelgium67.7¢POLYMARKETWill USA win the 2026 FIFA World Cup?3¢POLYMARKET Iran agrees to end enrichment of uranium by June 30?6¢POLYMARKETWill Egypt win the 2026 FIFA World Cup?0¢HL PERPBTC-USD perpetual$63,636 HL PERPHYPE-USD perpetual$70.85 HL PERPETH-USD perpetual$1,727.7

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

$764

bid $378 · ask $386

Mid price

0.250500

(best bid + best ask) / 2

Spread

39.9bp

(bestAsk − bestBid) / mid

Imbalance (whole book)

-0.857

ask-heavy

Imbalance (top-5)

-0.306

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-flvio-bolsonaro-win-the-2026-brazilian-presidential-election/slippage?size=10000&side=buy

Side	Notional	Avg fill	Slippage	Worst fill	Levels	Status
BUY	$1.00K	0.252530	81.04bp	0.254000	4	FILLED
BUY	$10.00K	0.261974	458.05bp	0.266000	16	FILLED
BUY	$100.00K	0.345218	3781.15bp	0.650000	134	FILLED
SELL	$1.00K	0.246222	170.77bp	0.242000	7	FILLED
SELL	$10.00K	0.228492	878.56bp	0.220000	26	FILLED
SELL	$100.00K	0.030788	8770.94bp	0.001000	75	PARTIAL

Risk metrics

▸ sovereign store · 4,159 barsperiods/year ≈ 1.75M

Realized vol (annualised)

175.02%

σ per bar = 0.001322

Mean return (annualised)

-4465.98%

μ per bar = -0.000025

Sharpe (rf=0)

-25.52

annualised; risk-free assumed zero

Max drawdown

14.36%

peak 0.28 → trough 0.24 over 1801 bars

/api/asset/pm-will-flvio-bolsonaro-win-the-2026-brazilian-presidential-election/risk · same metrics, JSON