POLYMARKET · PREDICTION MARKET · NOTTINGHAM OPEN: EMMA NAVARRO VS VIKTORIJA GOLUBIC
Nottingham Open: Emma Navarro vs Viktorija Golubic
69.5¢
30.5¢
▸ Advanced metrics · M2M bundle
polymarket · wta-navarro-golubic-2026-06-20 · fresh · feed 7s old24h sparkline · 60 pts▼ —
realized vol (ann.)
118.25%
max drawdown
2.80%
sharpe
—
ulcer index
1.64%
RMS drawdown
pain index
1.32%
mean drawdown
mod. VaR 95%
0.00%
Cornish-Fisher
martin ratio
—
ret / ulcer
CDaR 95%
2.80%
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
1004
store
spread
—
24h Δ
—
flow lean
—
carry
flat
signalNEUTRALconfidence 20%
Same bundle via M2M API:
/api/m2m/pm-wta-navarro-golubic-2026-06-20/bundle · venue execution: polymarket →LIVEPOLL0SRCFRESH⏱--:--:-- UTCNEXT8.0sUP0s--:--HIST
▶ 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
69.5¢
NO · live
30.5¢
14 ticks · last 69.50¢
Σ 100.00% · fair
Σ-sides total = 100.00% (tight rounding)
H(p) entropy = 0.887 / 1.00 bits (89%) · high uncertainty
YES69.5%69.5¢1.44×▬ +0.00pp
NO30.5%30.5¢3.28×▬ +0.00pp
Σ 100.00% · arb gap 0.00pp
Σ 600bp moved · peak 100bp · n=13 ticks
7.0s
69.50¢ (69.50%)
30.50¢ (30.50%)
100.00%
0.000pp
$153.8k
$97.1k
14 ticks (live)
§1 · 24h price history (YES + NO tokens)
14 YES observations from clob.polymarket.com · last 69.50¢
14 NO observations from clob.polymarket.com · last 30.50¢
§2 · Distribution of Δp
n=13
reference line = identity (perfect normality). Heavy upper-right tail = fat positive tail.
§3 · Sample moments
SAMPLE MOMENTS · N=14PLATYKURTIC · THIN TAILS (G₂=-1.24)
FIVE-NUMBER SUMMARY · BOX PLOT
SKEWNESS · G₁-0.154approximately symmetric
−3−10+1+3
EXCESS KURTOSIS · G₂-1.236platykurtic · 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) -0.41 + ADF rejected
HURST EXPONENT [0, 1]
H = 0.500RANDOM-WALK
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
69.50¢
30.50¢
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
YES1.44×(70¢)NO3.28×(31¢)
Kelly bet-size (% of bankroll) K* = 0.00%
Entropy H(p̂) = 0.887 bits (89% 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.
§8 · Time decay & θ projection
⏱ URGENCY · LOWresolves 2026-06-27 11:30 UTC
6days
23hrs
30min
YES →$1.00
NO →$0.00
current: $0.6950 · expected return per side: $0.31 on YES hit · $0.69 on NO hit
Theta progression · θ ∝ σ / √t_remainingθ_now = 4.939 pp/day
now6.98d left4.939 pp/day×1.00
−25%5.23d left5.703 pp/day×1.15
−50%3.49d left6.985 pp/day×1.41
−75%1.74d left9.878 pp/day×2.00
−90%16.75h left15.619 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
4 up bars · 2 down · best 1.00% · worst -1.00% · typical |Δ| 0.462%
§10 · Equity curve & underwater drawdown
final equity 1.0199 (1.99%) · max DD -1.01% · time-under-water 4/14 bars
§11 · Rolling-window statistics (w = 4 bars)
latest -24.439 · range [-24.44, 81.06] · μ 32.486 · positive Sharpe = excess-return-per-risk earned by buying-and-holding through this window
latest 89.61% · range [46.80%, 89.61%] · μ 64.05% · σ̂ scaled to annualised (×√8760)
latest -0.750 · |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)
1 of 6 REJECT · mixed evidence1 reject·5 pass·α = 0.05
Jarque-Bera
FAIL TO REJECTnsH₀: Δp ~ Normal(μ, σ²)
STATISTIC
0.2230
p-VALUE (log scale)
0.8945
Ljung-Box(h=5)
FAIL TO REJECTnsH₀: No serial autocorrelation up to lag 5
STATISTIC
4.6300
p-VALUE (log scale)
0.3272
Dickey-Fuller (τ_μ)
FAIL TO REJECTnsH₀: p has a unit root (non-stationary)
STATISTIC
-1.8661
p-VALUE (log scale)
0.3590
Wald-Wolfowitz runs
FAIL TO REJECTnsH₀: Sign sequence of Δ is random
STATISTIC
0.3536
p-VALUE (log scale)
0.7237
KPSS (μ stationarity)
REJECT H₀*H₀: p IS level-stationary
STATISTIC
0.4724
p-VALUE (log scale)
0.0479
Variance ratio q=1
FAIL TO REJECTnsH₀: Δp is a random walk · VR = 1
STATISTIC
0.0000
p-VALUE (log scale)
1.0000
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 ≈ 2.17h (freq 0.462) · concentrates 31.5% of total energy · Σ|X̂|²/n = 2.846e-4
▸ Depth section using sovereign-store price series (1004 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 7.0 d · σ/bar 0.089pp · expected |Δp| over horizon 1.16ppterminal variance p(1−p) = 0.2120 · n = 1004✓ n = 1004
μ per bar
+0.000pp
average Δp · drift
σ per bar
0.089pp
one-bar volatility · logit-free
Per-day movedaily
0.44pp
σ × √24
Per-horizon move7d
1.16pp
σ × √167.5106211111111
Terminal variancebinary
0.2120
p(1−p) at resolution
Current pricep
69.5¢
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 0.15pp · ES₉₅ 0.18pp · method parametric · drift-correcteddrift +0.000pp/bar · quantised: yes · median step 1.00pp · unique ratio 0.00✓ n = 1004
VaR 95%
0.15pp
1.645·σ (parametric) of Δp
ES 95%
0.18pp
mean of the tail
Max drawdown
2.8pp
peak 71.5¢ → trough 69.5¢
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
69.5%
= price
Decimal oddsEU
1.439
total return per $1
AmericanUS
-228
risk $228 to win $100
FractionalUK
0.44 / 1
profit per $1 risked
Profit per $100stake
+$43.88
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)
0.887 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.887 bit
Δ +0.000 bit vs market
Surprise · YES−log₂ p
0.52 bit
self-information
Surprise · NO−log₂(1−p)
1.71 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
113076130322351607037766184340672376427922394394285882341401743165092221580857- NO token ID
34641847233506337362390410341270728095869646948086797212131244649175150920300- Snapshot fetched
- 2026-06-20 11:59:14 UTC
- Snapshot age
- 7.0s
- History points
- 14 CLOB mids
- Page rendered
- 2026-06-20 11:59:21 UTC
- Storage policy
- no persistence — fetched on every request
- SHA-256 attestation
0bb50f68bfeafa4ffb1538d00b0e32e24cd76e2aa4bd9b0a737d22083c09e8f2· deterministic hash of source snapshot- Open data licence
- CC0 / public domain
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Also see: /arb opportunities · RSS feed · more in Nottingham Open: Emma Navarro vs Viktorija Golubic
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
0.695000
(best bid + best ask) / 2
Spread
143.9bp
(bestAsk − bestBid) / mid
Imbalance (whole book)
+0.045
bid-heavy
Imbalance (top-5)
-0.721
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-wta-navarro-golubic-2026-06-20/slippage?size=10000&side=buy
| Side | Notional | Avg fill | Slippage | Worst fill | Levels | Status |
|---|---|---|---|---|---|---|
| BUY | $1.00K | 0.700000 | 71.94bp | 0.700000 | 1 | FILLED |
| BUY | $10.00K | 0.704373 | 134.86bp | 0.710000 | 2 | FILLED |
| BUY | $100.00K | 0.717185 | 319.21bp | 0.720000 | 3 | FILLED |
| SELL | $1.00K | 0.690000 | 71.94bp | 0.690000 | 1 | FILLED |
| SELL | $10.00K | 0.689698 | 76.29bp | 0.680000 | 2 | FILLED |
| SELL | $100.00K | 0.098098 | 8588.52bp | 0.010000 | 34 | PARTIAL |
Risk metrics
▸ sovereign store · 1,004 barsperiods/year ≈ 1.75MRealized vol (annualised)
168.10%
σ per bar = 0.001270
Mean return (annualised)
-0.00%
μ per bar = -0.000000
Sharpe (rf=0)
-0.00
annualised; risk-free assumed zero
Max drawdown
2.80%
peak 0.71 → trough 0.69 over 193 bars
/api/asset/pm-wta-navarro-golubic-2026-06-20/risk · same metrics, JSON