POLYMARKET · PREDICTION MARKET · WHO WILL TRUMP SPEAK TO IN JUNE?
Will Trump speak to Ahmed al-Sharaa in June?
41.0¢
59.0¢
▸ Advanced metrics · M2M bundle
polymarket · will-trump-speak-to-ahmed-al-sharaa-in-june · fresh · feed 0s oldrealized vol (ann.)
—
max drawdown
—
sharpe
—
ulcer index
—
RMS drawdown
pain index
—
mean drawdown
mod. VaR 95%
—
Cornish-Fisher
martin ratio
—
ret / ulcer
CDaR 95%
—
cond. drawdown
gain/pain
—
Σgain / Σ|loss|
sterling
—
ret / CDaR
omega (θ=0)
—
upside/downside
roll spread
—
implied (price-only)
bars used
0
insufficient
spread
—
24h Δ
—
flow lean
—
carry
flat
signalNEUTRALconfidence 0%
- insufficient history for risk metrics — directional read only
Same bundle via M2M API:
/api/m2m/pm-will-trump-speak-to-ahmed-al-sharaa-in-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
41.0¢
NO · live
59.0¢
25 ticks · last 41.00¢
Σ 100.00% · fair
Σ-sides total = 100.00% (tight rounding)
H(p) entropy = 0.977 / 1.00 bits (98%) · max uncertainty (~50/50)
YES41.0%41.0¢2.44×▬ +0.00pp
NO59.0%59.0¢1.69×▬ +0.00pp
Σ 100.00% · arb gap 0.00pp
Σ 10750bp moved · peak 1500bp · n=24 ticks
3ms
41.00¢ (41.00%)
59.00¢ (59.00%)
100.00%
0.000pp
$33.1k
$15.4k
25 ticks (live)
§1 · 24h price history (YES + NO tokens)
25 YES observations from clob.polymarket.com · last 41.00¢
25 NO observations from clob.polymarket.com · last 59.00¢
§2 · Distribution of Δp
n=24
reference line = identity (perfect normality). Heavy upper-right tail = fat positive tail.
§3 · Sample moments
SAMPLE MOMENTS · N=25PLATYKURTIC · THIN TAILS (G₂=-1.41)
FIVE-NUMBER SUMMARY · BOX PLOT
SKEWNESS · G₁0.334approximately symmetric
−3−10+1+3
EXCESS KURTOSIS · G₂-1.412platykurtic · 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: INDETERMINATE · weak signal at n=24
HURST EXPONENT [0, 1]
H = 0.809STRONGLY 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
41.00¢
59.00¢
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
YES2.44×(41¢)NO1.69×(59¢)
Kelly bet-size (% of bankroll) K* = 0.00%
Entropy H(p̂) = 0.977 bits (98% 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 2026-06-30 00:00 UTC
15days
04hrs
49min
YES →$1.00
NO →$0.00
current: $0.4100 · expected return per side: $0.59 on YES hit · $0.41 on NO hit
Theta progression · θ ∝ σ / √t_remainingθ_now = 52.683 pp/day
now15.20d left52.683 pp/day×1.00
−25%11.40d left60.833 pp/day×1.15
−50%7.60d left74.505 pp/day×1.41
−75%3.80d left105.366 pp/day×2.00
−90%1.52d left166.598 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
9 up bars · 9 down · best 10.00% · worst -15.00% · typical |Δ| 4.479%
§10 · Equity curve & underwater drawdown
final equity 0.9386 (-6.14%) · max DD -29.83% · time-under-water 20/25 bars
§11 · Rolling-window statistics (w = 6 bars)
latest 12.492 · range [-70.61, 54.05] · μ -12.308 · positive Sharpe = excess-return-per-risk earned by buying-and-holding through this window
latest 525.92% · range [249.39%, 802.95%] · μ 570.67% · σ̂ scaled to annualised (×√8760)
latest -0.522 · |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
0.8895
p-VALUE (log scale)
0.6410
Ljung-Box(h=5)
FAIL TO REJECTnsH₀: No serial autocorrelation up to lag 5
STATISTIC
2.4230
p-VALUE (log scale)
0.7901
Dickey-Fuller (τ_μ)
FAIL TO REJECTnsH₀: p has a unit root (non-stationary)
STATISTIC
-1.4103
p-VALUE (log scale)
0.5761
Wald-Wolfowitz runs
FAIL TO REJECTnsH₀: Sign sequence of Δ is random
STATISTIC
0.0000
p-VALUE (log scale)
1.0000
KPSS (μ stationarity)
REJECT H₀*H₀: p IS level-stationary
STATISTIC
0.5473
p-VALUE (log scale)
0.0310
Variance ratio q=3
FAIL TO REJECTnsH₀: Δp is a random walk · VR = 1
STATISTIC
0.2688
p-VALUE (log scale)
0.7881
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 ≈ 2.67h (freq 0.375) · concentrates 21.8% of total energy · Σ|X̂|²/n = 4.716e-2
§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 15.2 d · σ/bar 6.404pp · expected |Δp| over horizon 122.31ppterminal variance p(1−p) = 0.2419 · n = 25⚠ low confidence · n < 100
μ per bar
-0.063pp
average Δp · drift
σ per bar
6.404pp
one-bar volatility · logit-free
Per-day movedaily
31.37pp
σ × √24
Per-horizon move15d
122.31pp
σ × √364.8321608333333
Terminal variancebinary
0.2419
p(1−p) at resolution
Current pricep
41.0¢
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 10.60pp · ES₉₅ 13.27pp · method parametric · drift-correcteddrift -0.063pp/bar · quantised: yes · median step 2.00pp · unique ratio 0.68⊘ disabled · n < 30
VaR 95%
10.60pp
1.645·σ (parametric) of Δp
ES 95%
13.27pp
mean of the tail
Max drawdown
49.3pp
peak 68.0¢ → trough 34.5¢
Median step
2.00pp
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
41.0%
= price
Decimal oddsEU
2.439
total return per $1
AmericanUS
+144
$100 wins $144
FractionalUK
1.44 / 1
profit per $1 risked
Profit per $100stake
+$143.90
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)
0.977 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.977 bit
Δ +0.000 bit vs market
Surprise · YES−log₂ p
1.29 bit
self-information
Surprise · NO−log₂(1−p)
0.76 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
77880220756029001316833489963451185413859341337766246695796778971852855364193- NO token ID
37467331232390403592117157227775823672290715404178863367925865951366572489504- Snapshot fetched
- 2026-06-14 19:10:04 UTC
- Snapshot age
- 3ms
- History points
- 25 CLOB mids
- Page rendered
- 2026-06-14 19:10:04 UTC
- Storage policy
- no persistence — fetched on every request
- SHA-256 attestation
9b468759f511c0a6d661b64e9da183a9878f286478d8bf8395f1b1622e87ce35· deterministic hash of source snapshot- Open data licence
- CC0 / public domain
§∞-2 · Related markets · explore more
HL PREDGermany100.0¢HL PREDSpain89.5¢HL PREDUruguay66.9¢POLYMARKETWill Curaçao win on 2026-06-14?0¢POLYMARKETWill Australia win the 2026 FIFA World Cup?0¢POLYMARKETWill Scotland win the 2026 FIFA World Cup?0¢HL PERPBTC-USD perpetual$63,752.5HL PERPETH-USD perpetual$1,661.95HL PERPHYPE-USD perpetual$60.32
Also see: /arb opportunities · RSS feed · more in Who will Trump speak to in 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
0.410000
(best bid + best ask) / 2
Spread
487.8bp
(bestAsk − bestBid) / mid
Imbalance (whole book)
+0.749
bid-heavy
Imbalance (top-5)
-0.003
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-will-trump-speak-to-ahmed-al-sharaa-in-june/slippage?size=10000&side=buy
| Side | Notional | Avg fill | Slippage | Worst fill | Levels | Status |
|---|---|---|---|---|---|---|
| BUY | $1.00K | 0.590366 | 4399.18bp | 0.730000 | 14 | FILLED |
| BUY | $10.00K | 0.801132 | 9539.81bp | 0.870000 | 22 | FILLED |
| BUY | $100.00K | 0.888157 | 11662.38bp | 0.990000 | 30 | PARTIAL |
| SELL | $1.00K | 0.303979 | 2585.87bp | 0.240000 | 14 | FILLED |
| SELL | $10.00K | 0.108483 | 7354.07bp | 0.040000 | 31 | FILLED |
| SELL | $100.00K | 0.062667 | 8471.55bp | 0.010000 | 34 | PARTIAL |
Risk metrics
▸ upstream candles · 25 barsRealized vol (annualised)
—
σ per bar = 0.138385
Mean return (annualised)
—
μ per bar = -0.001497
Sharpe (rf=0)
—
annualised; risk-free assumed zero
Max drawdown
49.26%
peak 0.68 → trough 0.34 over 9 bars
/api/asset/pm-will-trump-speak-to-ahmed-al-sharaa-in-june/risk · same metrics, JSON