POLYMARKET · PREDICTION MARKET · ELON MUSK # TWEETS JUNE 18 - JUNE 20, 2026?
Will Elon Musk post 40-64 tweets from June 18 to June 20, 2026?
93.5¢
6.5¢
▸ Advanced metrics · M2M bundle
polymarket · elon-musk-of-tweets-june-18-june-20-40-64 · fresh · feed 10s old24h sparkline · 60 pts▼ —
realized vol (ann.)
612.92%
max drawdown
5.29%
sharpe
—
ulcer index
1.72%
RMS drawdown
pain index
1.12%
mean drawdown
mod. VaR 95%
0.00%
Cornish-Fisher
martin ratio
—
ret / ulcer
CDaR 95%
4.78%
cond. drawdown
gain/pain
2.24
Σgain / Σ|loss|
sterling
—
ret / CDaR
omega (θ=0)
2.24
upside/downside
roll spread
4.9 bps
implied (price-only)
bars used
553
store
spread
—
24h Δ
—
flow lean
—
carry
flat
signalNEUTRALconfidence 20%
Same bundle via M2M API:
/api/m2m/pm-elon-musk-of-tweets-june-18-june-20-40-64/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
93.5¢
NO · live
6.5¢
24 ticks · last 93.50¢
Σ 100.00% · fair
Σ-sides total = 100.00% (tight rounding)
H(p) entropy = 0.347 / 1.00 bits (35%) · informative — one side favoured
YES93.5%93.5¢1.07×▬ +0.00pp
NO6.5%6.5¢15.38×▬ +0.00pp
Σ 100.00% · arb gap 0.00pp
Σ 7950bp moved · peak 1200bp · n=23 ticks
9.9s
93.50¢ (93.50%)
6.50¢ (6.50%)
100.00%
0.000pp
$83.6k
$11.9k
24 ticks (live)
§1 · 24h price history (YES + NO tokens)
24 YES observations from clob.polymarket.com · last 93.50¢
25 NO observations from clob.polymarket.com · last 10.50¢
§2 · Distribution of Δp
n=23
reference line = identity (perfect normality). Heavy upper-right tail = fat positive tail.
§3 · Sample moments
SAMPLE MOMENTS · N=24RIGHT-SKEWED (G₁=0.67)
FIVE-NUMBER SUMMARY · BOX PLOT
SKEWNESS · G₁0.667right-skewed
−3−10+1+3
EXCESS KURTOSIS · G₂-0.639mesokurtic · 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) -0.27 + ADF rejected
HURST EXPONENT [0, 1]
H = 0.781STRONGLY 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
93.50¢
6.50¢
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
YES1.07×(94¢)NO15.38×(7¢)
Kelly bet-size (% of bankroll) K* = 0.00%
Entropy H(p̂) = 0.347 bits (35% 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 · HIGHresolves 2026-06-20 16:00 UTC
0days
06hrs
19min
YES →$1.00
NO →$0.00
current: $0.9350 · expected return per side: $0.06 on YES hit · $0.94 on NO hit
Theta progression · θ ∝ σ / √t_remainingθ_now = 67.600 pp/day
now6.32h left67.600 pp/day×1.00
−25%4.74h left78.058 pp/day×1.15
−50%3.16h left95.601 pp/day×1.41
−75%1.58h left135.201 pp/day×2.00
−90%0.63h left213.771 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
17 up bars · 3 down · best 12.00% · worst -9.00% · typical |Δ| 3.457%
§10 · Equity curve & underwater drawdown
final equity 1.5023 (50.23%) · max DD -9.00% · time-under-water 4/24 bars
§11 · Rolling-window statistics (w = 5 bars)
latest 67.321 · range [-7.52, 178.59] · μ 43.459 · positive Sharpe = excess-return-per-risk earned by buying-and-holding through this window
latest 468.44% · range [122.03%, 814.33%] · μ 449.29% · σ̂ scaled to annualised (×√8760)
latest -0.116 · |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
1.4646
p-VALUE (log scale)
0.4808
Ljung-Box(h=5)
FAIL TO REJECTnsH₀: No serial autocorrelation up to lag 5
STATISTIC
4.9948
p-VALUE (log scale)
0.4172
Dickey-Fuller (τ_μ)
FAIL TO REJECTnsH₀: p has a unit root (non-stationary)
STATISTIC
0.0704
p-VALUE (log scale)
0.9617
Wald-Wolfowitz runs
FAIL TO REJECTnsH₀: Sign sequence of Δ is random
STATISTIC
0.8579
p-VALUE (log scale)
0.3909
KPSS (μ stationarity)
REJECT H₀**H₀: p IS level-stationary
STATISTIC
0.8356
p-VALUE (log scale)
0.0058
Variance ratio q=2
FAIL TO REJECTnsH₀: Δp is a random walk · VR = 1
STATISTIC
-1.1344
p-VALUE (log scale)
0.2566
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 ≈ 3.29h (freq 0.304) · concentrates 24.5% of total energy · Σ|X̂|²/n = 2.490e-2
▸ Depth section using sovereign-store price series (553 bars · effective 1752518 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 0.3 d · σ/bar 0.463pp · expected |Δp| over horizon 1.16ppterminal variance p(1−p) = 0.0608 · n = 553✓ n = 553
μ per bar
+0.024pp
average Δp · drift
σ per bar
0.463pp
one-bar volatility · logit-free
Per-day movedaily
2.27pp
σ × √24
Per-horizon move0d
1.16pp
σ × √6.319945
Terminal variancebinary
0.0608
p(1−p) at resolution
Current pricep
93.5¢
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 0.74pp · ES₉₅ 0.93pp · method parametric · drift-correcteddrift +0.024pp/bar · quantised: yes · median step 1.00pp · unique ratio 0.02✓ n = 553
VaR 95%
0.74pp
1.645·σ (parametric) of Δp
ES 95%
0.93pp
mean of the tail
Max drawdown
5.3pp
peak 94.5¢ → trough 89.5¢
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
93.5%
= price
Decimal oddsEU
1.070
total return per $1
AmericanUS
-1438
risk $1438 to win $100
FractionalUK
0.07 / 1
profit per $1 risked
Profit per $100stake
+$6.95
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)
0.347 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.347 bit
Δ +0.000 bit vs market
Surprise · YES−log₂ p
0.10 bit
self-information
Surprise · NO−log₂(1−p)
3.94 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
17008133912366416395222778286066139436932650416761805770025243200411535263210- NO token ID
22017366524511205107638154808394564746643180461954582310220600628260584857655- Snapshot fetched
- 2026-06-20 09:40:38 UTC
- Snapshot age
- 9.9s
- History points
- 24 CLOB mids
- Page rendered
- 2026-06-20 09:40:48 UTC
- Storage policy
- no persistence — fetched on every request
- SHA-256 attestation
eacfbe1d4b1ebc2b19e0ff39bc9c67c28757462c71c7472047d8e70ddbbf7688· deterministic hash of source snapshot- Open data licence
- CC0 / public domain
§∞-2 · Related markets · explore more
HL PREDSpain88.4¢HL PREDEcuador86.3¢HL PREDBelgium67.7¢POLYMARKETWill USA win the 2026 FIFA World Cup?3¢POLYMARKET Iran agrees to end enrichment of uranium by June 30?6¢POLYMARKETWill Egypt win the 2026 FIFA World Cup?0¢HL PERPBTC-USD perpetual$63,620HL PERPHYPE-USD perpetual$70.71HL PERPETH-USD perpetual$1,728
Also see: /arb opportunities · RSS feed · more in Elon Musk # tweets June 18 - June 20, 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
0.905000
(best bid + best ask) / 2
Spread
110.5bp
(bestAsk − bestBid) / mid
Imbalance (whole book)
+0.296
bid-heavy
Imbalance (top-5)
-0.487
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-elon-musk-of-tweets-june-18-june-20-40-64/slippage?size=10000&side=buy
| Side | Notional | Avg fill | Slippage | Worst fill | Levels | Status |
|---|---|---|---|---|---|---|
| BUY | $1.00K | 0.911162 | 68.09bp | 0.920000 | 2 | FILLED |
| BUY | $10.00K | 0.964201 | 654.15bp | 0.990000 | 9 | FILLED |
| BUY | $100.00K | 0.973729 | 759.43bp | 0.990000 | 9 | PARTIAL |
| SELL | $1.00K | 0.872560 | 358.45bp | 0.840000 | 6 | FILLED |
| SELL | $10.00K | 0.569283 | 3709.58bp | 0.310000 | 38 | FILLED |
| SELL | $100.00K | 0.373612 | 5871.69bp | 0.010000 | 59 | PARTIAL |
Risk metrics
▸ sovereign store · 553 barsperiods/year ≈ 1.75MRealized vol (annualised)
683.26%
σ per bar = 0.005161
Mean return (annualised)
47528.89%
μ per bar = 0.000271
Sharpe (rf=0)
69.56
annualised; risk-free assumed zero
Max drawdown
5.29%
peak 0.94 → trough 0.90 over 17 bars
/api/asset/pm-elon-musk-of-tweets-june-18-june-20-40-64/risk · same metrics, JSON