POLYMARKET · PREDICTION MARKET · STRAIT OF HORMUZ TRAFFIC RETURNS TO NORMAL BY END OF JUNE?
Strait of Hormuz traffic returns to normal by end of June?
21.0¢
79.0¢
▸ Advanced metrics · M2M bundle
polymarket · strait-of-hormuz-traffic-returns-to-normal-by-end-of-june · fresh · feed 0s old24h sparkline · 60 pts▼ —
realized vol (ann.)
142.76%
max drawdown
12.77%
sharpe
—
ulcer index
7.28%
RMS drawdown
pain index
5.97%
mean drawdown
mod. VaR 95%
0.00%
Cornish-Fisher
martin ratio
—
ret / ulcer
CDaR 95%
12.77%
cond. drawdown
gain/pain
0.72
Σgain / Σ|loss|
sterling
—
ret / CDaR
omega (θ=0)
0.72
upside/downside
roll spread
1.1 bps
implied (price-only)
bars used
2000
store
spread
—
24h Δ
—
flow lean
—
carry
flat
signalNEUTRALconfidence 20%
Same bundle via M2M API:
/api/m2m/pm-strait-of-hormuz-traffic-returns-to-normal-by-end-of-june/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
21.0¢
NO · live
79.0¢
25 ticks · last 21.50¢
Σ 100.00% · fair
Σ-sides total = 100.00% (tight rounding)
H(p) entropy = 0.741 / 1.00 bits (74%) · moderate uncertainty
YES21.0%21.0¢4.76×▬ +0.00pp
NO79.0%79.0¢1.27×▬ +0.00pp
Σ 100.00% · arb gap 0.00pp
Σ 3100bp moved · peak 350bp · n=24 ticks
93ms
21.00¢ (21.00%)
79.00¢ (79.00%)
100.00%
0.000pp
$974.9k
$474.2k
25 ticks (live)
§1 · 24h price history (YES + NO tokens)
25 YES observations from clob.polymarket.com · last 21.50¢
25 NO observations from clob.polymarket.com · last 78.50¢
§2 · Distribution of Δp
n=24
reference line = identity (perfect normality). Heavy upper-right tail = fat positive tail.
§3 · Sample moments
SAMPLE MOMENTS · N=25APPROXIMATELY NORMAL · WELL-BEHAVED
FIVE-NUMBER SUMMARY · BOX PLOT
SKEWNESS · G₁0.131approximately symmetric
−3−10+1+3
EXCESS KURTOSIS · G₂-0.346mesokurtic · normal-like
−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) -0.50 + ADF rejected
HURST EXPONENT [0, 1]
H = 0.927STRONGLY 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
21.00¢
79.00¢
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
YES4.76×(21¢)NO1.27×(79¢)
Kelly bet-size (% of bankroll) K* = 0.00%
Entropy H(p̂) = 0.741 bits (74% of max) · moderate 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 · DISTANTresolves 2026-06-30 00:00 UTC
15days
12hrs
50min
YES →$1.00
NO →$0.00
current: $0.2100 · expected return per side: $0.79 on YES hit · $0.21 on NO hit
Theta progression · θ ∝ σ / √t_remainingθ_now = 7.290 pp/day
now15.54d left7.290 pp/day×1.00
−25%11.65d left8.417 pp/day×1.15
−50%7.77d left10.309 pp/day×1.41
−75%3.88d left14.579 pp/day×2.00
−90%1.55d left23.052 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
10 up bars · 7 down · best 3.50% · worst -3.00% · typical |Δ| 1.292%
§10 · Equity curve & underwater drawdown
final equity 1.0065 (0.65%) · max DD -5.47% · time-under-water 22/25 bars
§11 · Rolling-window statistics (w = 6 bars)
latest -9.737 · range [-41.44, 60.42] · μ 3.444 · positive Sharpe = excess-return-per-risk earned by buying-and-holding through this window
latest 149.95% · range [38.21%, 258.73%] · μ 148.32% · σ̂ scaled to annualised (×√8760)
latest -0.483 · |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
0.6521
p-VALUE (log scale)
0.7218
Ljung-Box(h=5)
FAIL TO REJECTnsH₀: No serial autocorrelation up to lag 5
STATISTIC
8.4305
p-VALUE (log scale)
0.1328
Dickey-Fuller (τ_μ)
REJECT H₀**H₀: p has a unit root (non-stationary)
STATISTIC
-3.6190
p-VALUE (log scale)
0.0057
Wald-Wolfowitz runs
FAIL TO REJECTnsH₀: Sign sequence of Δ is random
STATISTIC
1.4327
p-VALUE (log scale)
0.1520
KPSS (μ stationarity)
FAIL TO REJECTnsH₀: p IS level-stationary
STATISTIC
0.1203
p-VALUE (log scale)
0.4961
Variance ratio q=3
FAIL TO REJECTnsH₀: Δp is a random walk · VR = 1
STATISTIC
-1.9264
p-VALUE (log scale)
0.0541
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 ≈ 2.40h (freq 0.417) · concentrates 31.2% of total energy · Σ|X̂|²/n = 3.875e-3
▸ Depth section using sovereign-store price series (2831 bars · effective 1752810 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 15.5 d · σ/bar 0.098pp · expected |Δp| over horizon 1.90ppterminal variance p(1−p) = 0.1659 · n = 2831✓ n = 2831
μ per bar
-0.001pp
average Δp · drift
σ per bar
0.098pp
one-bar volatility · logit-free
Per-day movedaily
0.48pp
σ × √24
Per-horizon move16d
1.90pp
σ × √372.84761694444444
Terminal variancebinary
0.1659
p(1−p) at resolution
Current pricep
21.0¢
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 0.16pp · ES₉₅ 0.20pp · method parametric · drift-correcteddrift -0.001pp/bar · quantised: yes · median step 1.00pp · unique ratio 0.00✓ n = 2831
VaR 95%
0.16pp
1.645·σ (parametric) of Δp
ES 95%
0.20pp
mean of the tail
Max drawdown
16.3pp
peak 24.5¢ → trough 20.5¢
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
21.0%
= price
Decimal oddsEU
4.762
total return per $1
AmericanUS
+376
$100 wins $376
FractionalUK
3.76 / 1
profit per $1 risked
Profit per $100stake
+$376.19
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)
0.741 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.741 bit
Δ +0.000 bit vs market
Surprise · YES−log₂ p
2.25 bit
self-information
Surprise · NO−log₂(1−p)
0.34 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
46130022848920611732202507184264902690726361824951579816156441452797397798181- NO token ID
77669758102929718590160851391714019116736856202333459817343190730743895177270- Snapshot fetched
- 2026-06-14 11:09:08 UTC
- Snapshot age
- 93ms
- History points
- 25 CLOB mids
- Page rendered
- 2026-06-14 11:09:08 UTC
- Storage policy
- no persistence — fetched on every request
- SHA-256 attestation
3a28deb2d65775dfc456dddfc558759755945711b57c1db145a771ac04781060· deterministic hash of source snapshot- Open data licence
- CC0 / public domain
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Also see: /arb opportunities · RSS feed · more in Strait of Hormuz traffic returns to normal by end of June?
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
0.215000
(best bid + best ask) / 2
Spread
465.1bp
(bestAsk − bestBid) / mid
Imbalance (whole book)
+0.291
bid-heavy
Imbalance (top-5)
-0.403
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-strait-of-hormuz-traffic-returns-to-normal-by-end-of-june/slippage?size=10000&side=buy
| Side | Notional | Avg fill | Slippage | Worst fill | Levels | Status |
|---|---|---|---|---|---|---|
| BUY | $1.00K | 0.220000 | 232.56bp | 0.220000 | 1 | FILLED |
| BUY | $10.00K | 0.230286 | 710.98bp | 0.240000 | 3 | FILLED |
| BUY | $100.00K | 0.304007 | 4139.85bp | 0.450000 | 24 | FILLED |
| SELL | $1.00K | 0.204473 | 489.65bp | 0.200000 | 2 | FILLED |
| SELL | $10.00K | 0.188509 | 1232.12bp | 0.170000 | 5 | FILLED |
| SELL | $100.00K | 0.026208 | 8781.04bp | 0.010000 | 21 | PARTIAL |
Risk metrics
▸ sovereign store · 2,831 barsperiods/year ≈ 1.75MRealized vol (annualised)
587.70%
σ per bar = 0.004439
Mean return (annualised)
-6966.52%
μ per bar = -0.000040
Sharpe (rf=0)
-11.85
annualised; risk-free assumed zero
Max drawdown
16.33%
peak 0.24 → trough 0.20 over 761 bars
/api/asset/pm-strait-of-hormuz-traffic-returns-to-normal-by-end-of-june/risk · same metrics, JSON