POLYMARKET · PREDICTION MARKET · WHAT WILL WTI CRUDE OIL (WTI) HIT IN JUNE 2026?
Will WTI Crude Oil (WTI) hit (LOW) $80 in June?
96.3¢
3.7¢
▸ Advanced metrics · M2M bundle
polymarket · will-wti-dip-to-80-in-june-2026-848-561-294-989-956-135-789 · fresh · feed 0s old24h sparkline · 60 pts▼ —
realized vol (ann.)
1085.82%
max drawdown
2.73%
sharpe
—
ulcer index
0.93%
RMS drawdown
pain index
0.38%
mean drawdown
mod. VaR 95%
0.00%
Cornish-Fisher
martin ratio
—
ret / ulcer
CDaR 95%
2.73%
cond. drawdown
gain/pain
7.97
Σgain / Σ|loss|
sterling
—
ret / CDaR
omega (θ=0)
7.97
upside/downside
roll spread
12.5 bps
implied (price-only)
bars used
521
store
spread
—
24h Δ
—
flow lean
—
carry
flat
signalNEUTRALconfidence 20%
Same bundle via M2M API:
/api/m2m/pm-will-wti-dip-to-80-in-june-2026-848-561-294-989-956-135-789/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
96.3¢
NO · live
3.7¢
25 ticks · last 94.25¢
Σ 100.00% · fair
Σ-sides total = 100.00% (tight rounding)
H(p) entropy = 0.228 / 1.00 bits (23%) · informative — one side favoured
YES96.3%96.3¢1.04×▬ +0.00pp
NO3.7%3.7¢27.03×▬ +0.00pp
Σ 100.00% · arb gap 0.00pp
Σ 6925bp moved · peak 2250bp · n=24 ticks
5ms
96.30¢ (96.30%)
3.70¢ (3.70%)
100.00%
0.000pp
$46.1k
$26.1k
25 ticks (live)
§1 · 24h price history (YES + NO tokens)
25 YES observations from clob.polymarket.com · last 94.25¢
25 NO observations from clob.polymarket.com · last 5.75¢
§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 · G₁0.236approximately symmetric
−3−10+1+3
EXCESS KURTOSIS · G₂0.691mesokurtic · 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: MARTINGALE · UNPREDICTABLE
HURST EXPONENT [0, 1]
H = 0.708STRONGLY 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
96.30¢
3.70¢
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
YES1.04×(96¢)NO27.03×(4¢)
Kelly bet-size (% of bankroll) K* = 0.00%
Entropy H(p̂) = 0.228 bits (23% of max) · informative — one side strongly favoured
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 2026-07-01 03:59 UTC
16days
05hrs
29min
YES →$1.00
NO →$0.00
current: $0.9630 · expected return per side: $0.04 on YES hit · $0.96 on NO hit
Theta progression · θ ∝ σ / √t_remainingθ_now = 28.841 pp/day
now16.23d left28.841 pp/day×1.00
−25%12.17d left33.302 pp/day×1.15
−50%8.11d left40.787 pp/day×1.41
−75%4.06d left57.682 pp/day×2.00
−90%1.62d left91.203 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
6 up bars · 10 down · best 22.50% · worst -8.00% · typical |Δ| 2.885%
§10 · Equity curve & underwater drawdown
final equity 1.0654 (6.54%) · max DD -18.00% · time-under-water 22/25 bars
§11 · Rolling-window statistics (w = 6 bars)
latest 17.583 · range [-38.21, 38.21] · μ -5.754 · positive Sharpe = excess-return-per-risk earned by buying-and-holding through this window
latest 1017.18% · range [0.00%, 1017.18%] · μ 346.76% · σ̂ scaled to annualised (×√8760)
latest 0.011 · |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
129.8599
p-VALUE (log scale)
< 0.0001
Ljung-Box(h=5)
FAIL TO REJECTnsH₀: No serial autocorrelation up to lag 5
STATISTIC
3.0897
p-VALUE (log scale)
0.6888
Dickey-Fuller (τ_μ)
FAIL TO REJECTnsH₀: p has a unit root (non-stationary)
STATISTIC
-2.1990
p-VALUE (log scale)
0.2129
Wald-Wolfowitz runs
FAIL TO REJECTnsH₀: Sign sequence of Δ is random
STATISTIC
0.2774
p-VALUE (log scale)
0.7815
KPSS (μ stationarity)
FAIL TO REJECTnsH₀: p IS level-stationary
STATISTIC
0.1005
p-VALUE (log scale)
0.5000
Variance ratio q=3
FAIL TO REJECTnsH₀: Δp is a random walk · VR = 1
STATISTIC
-0.4223
p-VALUE (log scale)
0.6728
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 ≈ 6.00h (freq 0.167) · concentrates 25.8% of total energy · Σ|X̂|²/n = 3.764e-2
▸ Depth section using sovereign-store price series (521 bars · effective 1753200 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 16.2 d · σ/bar 0.820pp · expected |Δp| over horizon 16.19ppterminal variance p(1−p) = 0.0356 · n = 521✓ n = 521
μ per bar
+0.050pp
average Δp · drift
σ per bar
0.820pp
one-bar volatility · logit-free
Per-day movedaily
4.02pp
σ × √24
Per-horizon move16d
16.19pp
σ × √389.4906991666667
Terminal variancebinary
0.0356
p(1−p) at resolution
Current pricep
96.3¢
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 1.30pp · ES₉₅ 1.64pp · method parametric · drift-correcteddrift +0.050pp/bar · quantised: yes · median step 4.00pp · unique ratio 0.01✓ n = 521
VaR 95%
1.30pp
1.645·σ (parametric) of Δp
ES 95%
1.64pp
mean of the tail
Max drawdown
2.7pp
peak 99.0¢ → trough 96.3¢
Median step
4.00pp
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
96.3%
= price
Decimal oddsEU
1.038
total return per $1
AmericanUS
-2603
risk $2603 to win $100
FractionalUK
0.04 / 1
profit per $1 risked
Profit per $100stake
+$3.84
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)
0.228 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.228 bit
Δ +0.000 bit vs market
Surprise · YES−log₂ p
0.05 bit
self-information
Surprise · NO−log₂(1−p)
4.76 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
63439902591578641938655732289374099439286477746042661076367925767947780626333- NO token ID
98250763696241942584869427468047574128044429574998074337027520521376267014070- Snapshot fetched
- 2026-06-14 22:30:33 UTC
- Snapshot age
- 5ms
- History points
- 25 CLOB mids
- Page rendered
- 2026-06-14 22:30:33 UTC
- Storage policy
- no persistence — fetched on every request
- SHA-256 attestation
c652c82cf2ceac8e489251e8349fcc316861c6663390431e4e64c0f228795a74· deterministic hash of source snapshot- Open data licence
- CC0 / public domain
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Also see: /arb opportunities · RSS feed · more in What will WTI Crude Oil (WTI) hit in June 2026?
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
0.942500
(best bid + best ask) / 2
Spread
307.7bp
(bestAsk − bestBid) / mid
Imbalance (whole book)
+0.958
bid-heavy
Imbalance (top-5)
+0.334
bid-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-will-wti-dip-to-80-in-june-2026-848-561-294-989-956-135-789/slippage?size=10000&side=buy
| Side | Notional | Avg fill | Slippage | Worst fill | Levels | Status |
|---|---|---|---|---|---|---|
| BUY | $1.00K | 0.968284 | 273.57bp | 0.969000 | 11 | FILLED |
| BUY | $10.00K | 0.979861 | 396.41bp | 0.999000 | 20 | PARTIAL |
| BUY | $100.00K | 0.979861 | 396.41bp | 0.999000 | 20 | PARTIAL |
| SELL | $1.00K | 0.905368 | 393.98bp | 0.902000 | 13 | FILLED |
| SELL | $10.00K | 0.835176 | 1138.72bp | 0.703000 | 21 | FILLED |
| SELL | $100.00K | 0.061495 | 9347.53bp | 0.001000 | 73 | PARTIAL |
Risk metrics
▸ sovereign store · 521 barsperiods/year ≈ 1.75MRealized vol (annualised)
1310.28%
σ per bar = 0.009896
Mean return (annualised)
105143.32%
μ per bar = 0.000600
Sharpe (rf=0)
80.25
annualised; risk-free assumed zero
Max drawdown
2.73%
peak 0.99 → trough 0.96 over 17 bars
/api/asset/pm-will-wti-dip-to-80-in-june-2026-848-561-294-989-956-135-789/risk · same metrics, JSON