POLYMARKET · PREDICTION MARKET · STRAIT OF HORMUZ TRAFFIC RETURNS TO NORMAL BY JULY 15?
Strait of Hormuz traffic returns to normal by July 15?
40.5¢
59.5¢
▸ Advanced metrics · M2M bundle
polymarket · strait-of-hormuz-traffic-returns-to-normal-by-july-15 · fresh · feed 0s old24h sparkline · 60 pts▼ —
realized vol (ann.)
144.13%
max drawdown
11.96%
sharpe
—
ulcer index
7.83%
RMS drawdown
pain index
6.94%
mean drawdown
mod. VaR 95%
0.00%
Cornish-Fisher
martin ratio
—
ret / ulcer
CDaR 95%
11.96%
cond. drawdown
gain/pain
0.21
Σgain / Σ|loss|
sterling
—
ret / CDaR
omega (θ=0)
0.21
upside/downside
roll spread
2.7 bps
implied (price-only)
bars used
948
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-july-15/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
40.5¢
NO · live
59.5¢
17 ticks · last 39.50¢
Σ 100.00% · fair
Σ-sides total = 100.00% (tight rounding)
H(p) entropy = 0.974 / 1.00 bits (97%) · max uncertainty (~50/50)
YES40.5%40.5¢2.47×▬ +0.00pp
NO59.5%59.5¢1.68×▬ +0.00pp
Σ 100.00% · arb gap 0.00pp
Σ 1300bp moved · peak 350bp · n=16 ticks
3ms
40.50¢ (40.50%)
59.50¢ (59.50%)
100.00%
0.000pp
$61.8k
$64.7k
17 ticks (live)
§1 · 24h price history (YES + NO tokens)
17 YES observations from clob.polymarket.com · last 39.50¢
17 NO observations from clob.polymarket.com · last 60.50¢
§2 · Distribution of Δp
n=16
reference line = identity (perfect normality). Heavy upper-right tail = fat positive tail.
§3 · Sample moments
SAMPLE MOMENTS · N=17PLATYKURTIC · THIN TAILS (G₂=-1.16)
FIVE-NUMBER SUMMARY · BOX PLOT
SKEWNESS · G₁-0.274approximately symmetric
−3−10+1+3
EXCESS KURTOSIS · G₂-1.163platykurtic · 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: MARTINGALE · UNPREDICTABLE
HURST EXPONENT [0, 1]
H = 0.962STRONGLY 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
40.50¢
59.50¢
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
YES2.47×(41¢)NO1.68×(60¢)
Kelly bet-size (% of bankroll) K* = 0.00%
Entropy H(p̂) = 0.974 bits (97% of max) · maximum uncertainty (~50/50)
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 2026-07-15 00:00 UTC
30days
09hrs
22min
YES →$1.00
NO →$0.00
current: $0.4050 · expected return per side: $0.59 on YES hit · $0.41 on NO hit
Theta progression · θ ∝ σ / √t_remainingθ_now = 10.027 pp/day
now30.39d left10.027 pp/day×1.00
−25%22.79d left11.578 pp/day×1.15
−50%15.20d left14.181 pp/day×1.41
−75%7.60d left20.054 pp/day×2.00
−90%3.04d left31.709 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
5 up bars · 5 down · best 2.00% · worst -3.50% · typical |Δ| 0.813%
§10 · Equity curve & underwater drawdown
final equity 0.9692 (-3.08%) · max DD -6.84% · time-under-water 10/17 bars
§11 · Rolling-window statistics (w = 4 bars)
latest -61.804 · range [-75.26, 114.63] · μ 4.999 · positive Sharpe = excess-return-per-risk earned by buying-and-holding through this window
latest 88.59% · range [38.21%, 180.74%] · μ 107.28% · σ̂ scaled to annualised (×√8760)
latest -0.262 · |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
REJECT H₀*H₀: Δp ~ Normal(μ, σ²)
STATISTIC
6.4397
p-VALUE (log scale)
0.0400
Ljung-Box(h=5)
FAIL TO REJECTnsH₀: No serial autocorrelation up to lag 5
STATISTIC
2.2054
p-VALUE (log scale)
0.8217
Dickey-Fuller (τ_μ)
FAIL TO REJECTnsH₀: p has a unit root (non-stationary)
STATISTIC
-0.3938
p-VALUE (log scale)
0.9062
Wald-Wolfowitz runs
FAIL TO REJECTnsH₀: Sign sequence of Δ is random
STATISTIC
-1.3416
p-VALUE (log scale)
0.1797
KPSS (μ stationarity)
FAIL TO REJECTnsH₀: p IS level-stationary
STATISTIC
0.2395
p-VALUE (log scale)
0.2878
Variance ratio q=2
FAIL TO REJECTnsH₀: Δp is a random walk · VR = 1
STATISTIC
0.1593
p-VALUE (log scale)
0.8734
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 ≈ 2.29h (freq 0.438) · concentrates 26.5% of total energy · Σ|X̂|²/n = 1.234e-3
▸ Depth section using sovereign-store price series (948 bars · effective 1753005 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 30.4 d · σ/bar 0.109pp · expected |Δp| over horizon 2.94ppterminal variance p(1−p) = 0.2410 · n = 948✓ n = 948
μ per bar
-0.006pp
average Δp · drift
σ per bar
0.109pp
one-bar volatility · logit-free
Per-day movedaily
0.53pp
σ × √24
Per-horizon move30d
2.94pp
σ × √729.3806505555556
Terminal variancebinary
0.2410
p(1−p) at resolution
Current pricep
40.5¢
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 0.18pp · ES₉₅ 0.23pp · method parametric · drift-correcteddrift -0.006pp/bar · quantised: yes · median step 0.50pp · unique ratio 0.01✓ n = 948
VaR 95%
0.18pp
1.645·σ (parametric) of Δp
ES 95%
0.23pp
mean of the tail
Max drawdown
12.0pp
peak 46.0¢ → trough 40.5¢
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
Implied probabilityP
40.5%
= price
Decimal oddsEU
2.469
total return per $1
AmericanUS
+147
$100 wins $147
FractionalUK
1.47 / 1
profit per $1 risked
Profit per $100stake
+$146.91
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)
0.974 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.974 bit
Δ +0.000 bit vs market
Surprise · YES−log₂ p
1.30 bit
self-information
Surprise · NO−log₂(1−p)
0.75 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
89075579425844467185868633488322759623361856543369509366205030098390192743019- NO token ID
71279521496039829536704041318414999273049358723733201938586896590878069795154- Snapshot fetched
- 2026-06-14 14:37:09 UTC
- Snapshot age
- 3ms
- History points
- 17 CLOB mids
- Page rendered
- 2026-06-14 14:37:09 UTC
- Storage policy
- no persistence — fetched on every request
- SHA-256 attestation
74719fbdf2f8750b9e27bc112747a1a168f31694308cc8dcd349eb4e90c4f03e· 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 July 15?
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
0.395000
(best bid + best ask) / 2
Spread
253.2bp
(bestAsk − bestBid) / mid
Imbalance (whole book)
+0.300
bid-heavy
Imbalance (top-5)
-0.884
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-july-15/slippage?size=10000&side=buy
| Side | Notional | Avg fill | Slippage | Worst fill | Levels | Status |
|---|---|---|---|---|---|---|
| BUY | $1.00K | 0.410535 | 393.28bp | 0.420000 | 3 | FILLED |
| BUY | $10.00K | 0.420408 | 643.24bp | 0.430000 | 4 | FILLED |
| BUY | $100.00K | 0.673049 | 7039.22bp | 0.900000 | 29 | FILLED |
| SELL | $1.00K | 0.356481 | 975.17bp | 0.340000 | 6 | FILLED |
| SELL | $10.00K | 0.275657 | 3021.35bp | 0.200000 | 18 | FILLED |
| SELL | $100.00K | 0.067941 | 8279.97bp | 0.010000 | 35 | PARTIAL |
Risk metrics
▸ sovereign store · 948 barsperiods/year ≈ 1.75MRealized vol (annualised)
335.04%
σ per bar = 0.002531
Mean return (annualised)
-23571.98%
μ per bar = -0.000134
Sharpe (rf=0)
-70.36
annualised; risk-free assumed zero
Max drawdown
11.96%
peak 0.46 → trough 0.41 over 897 bars
/api/asset/pm-strait-of-hormuz-traffic-returns-to-normal-by-july-15/risk · same metrics, JSON