POLYMARKET · PREDICTION MARKET · ELON MUSK # TWEETS JUNE 16 - JUNE 23, 2026?
Will Elon Musk post 160-179 tweets from June 16 to June 23, 2026?
21.5¢
78.5¢
▸ Advanced metrics · M2M bundle
polymarket · elon-musk-of-tweets-june-16-june-23-160-179 · fresh · feed 4s old24h sparkline · 60 pts▼ —
realized vol (ann.)
207.25%
max drawdown
12.20%
sharpe
—
ulcer index
3.87%
RMS drawdown
pain index
1.63%
mean drawdown
mod. VaR 95%
0.00%
Cornish-Fisher
martin ratio
—
ret / ulcer
CDaR 95%
10.46%
cond. drawdown
gain/pain
2.56
Σgain / Σ|loss|
sterling
—
ret / CDaR
omega (θ=0)
2.56
upside/downside
roll spread
7.2 bps
implied (price-only)
bars used
999
store
spread
—
24h Δ
—
flow lean
—
carry
flat
signalNEUTRALconfidence 20%
Same bundle via M2M API:
/api/m2m/pm-elon-musk-of-tweets-june-16-june-23-160-179/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
21.5¢
NO · live
78.5¢
25 ticks · last 21.50¢
Σ 100.00% · fair
Σ-sides total = 100.00% (tight rounding)
H(p) entropy = 0.751 / 1.00 bits (75%) · moderate uncertainty
YES21.5%21.5¢4.65×▬ +0.00pp
NO78.5%78.5¢1.27×▬ +0.00pp
Σ 100.00% · arb gap 0.00pp
Σ 2300bp moved · peak 400bp · n=24 ticks
3.5s
21.50¢ (21.50%)
78.50¢ (78.50%)
100.00%
0.000pp
$39.9k
$35.1k
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=25RIGHT-SKEWED (G₁=0.80)
FIVE-NUMBER SUMMARY · BOX PLOT
SKEWNESS · G₁0.803right-skewed
−3−10+1+3
EXCESS KURTOSIS · G₂-1.087platykurtic · 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 = 0.902STRONGLY 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
21.50¢
78.50¢
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
YES4.65×(22¢)NO1.27×(79¢)
Kelly bet-size (% of bankroll) K* = 0.00%
Entropy H(p̂) = 0.751 bits (75% 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 · LOWresolves 2026-06-23 16:00 UTC
3days
03hrs
44min
YES →$1.00
NO →$0.00
current: $0.2150 · expected return per side: $0.79 on YES hit · $0.21 on NO hit
Theta progression · θ ∝ σ / √t_remainingθ_now = 27.745 pp/day
now3.16d left27.745 pp/day×1.00
−25%2.37d left32.037 pp/day×1.15
−50%1.58d left39.237 pp/day×1.41
−75%18.94h left55.489 pp/day×2.00
−90%7.57h left87.736 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
7 up bars · 4 down · best 4.00% · worst -2.00% · typical |Δ| 0.958%
§10 · Equity curve & underwater drawdown
final equity 1.1353 (13.53%) · max DD -2.97% · time-under-water 11/25 bars
§11 · Rolling-window statistics (w = 6 bars)
latest 31.732 · range [-73.99, 84.06] · μ 30.164 · positive Sharpe = excess-return-per-risk earned by buying-and-holding through this window
latest 184.04% · range [57.31%, 234.92%] · μ 126.62% · σ̂ scaled to annualised (×√8760)
latest -0.782 · |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
4.6490
p-VALUE (log scale)
0.0978
Ljung-Box(h=5)
FAIL TO REJECTnsH₀: No serial autocorrelation up to lag 5
STATISTIC
3.5745
p-VALUE (log scale)
0.6146
Dickey-Fuller (τ_μ)
FAIL TO REJECTnsH₀: p has a unit root (non-stationary)
STATISTIC
0.5138
p-VALUE (log scale)
0.9865
Wald-Wolfowitz runs
FAIL TO REJECTnsH₀: Sign sequence of Δ is random
STATISTIC
-1.4489
p-VALUE (log scale)
0.1474
KPSS (μ stationarity)
REJECT H₀*H₀: p IS level-stationary
STATISTIC
0.7327
p-VALUE (log scale)
0.0106
Variance ratio q=3
FAIL TO REJECTnsH₀: Δp is a random walk · VR = 1
STATISTIC
0.5677
p-VALUE (log scale)
0.5702
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 ≈ 24.00h (freq 0.042) · concentrates 23.7% of total energy · Σ|X̂|²/n = 2.898e-3
▸ Depth section using sovereign-store price series (999 bars · effective 1752616 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 3.2 d · σ/bar 0.157pp · expected |Δp| over horizon 1.36ppterminal variance p(1−p) = 0.1688 · n = 999✓ n = 999
μ per bar
+0.007pp
average Δp · drift
σ per bar
0.157pp
one-bar volatility · logit-free
Per-day movedaily
0.77pp
σ × √24
Per-horizon move3d
1.36pp
σ × √75.74018416666667
Terminal variancebinary
0.1688
p(1−p) at resolution
Current pricep
21.5¢
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 0.25pp · ES₉₅ 0.32pp · method parametric · drift-correcteddrift +0.007pp/bar · quantised: yes · median step 1.00pp · unique ratio 0.01✓ n = 999
VaR 95%
0.25pp
1.645·σ (parametric) of Δp
ES 95%
0.32pp
mean of the tail
Max drawdown
12.2pp
peak 20.5¢ → trough 18.0¢
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
21.5%
= price
Decimal oddsEU
4.651
total return per $1
AmericanUS
+365
$100 wins $365
FractionalUK
3.65 / 1
profit per $1 risked
Profit per $100stake
+$365.12
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)
0.751 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.751 bit
Δ +0.000 bit vs market
Surprise · YES−log₂ p
2.22 bit
self-information
Surprise · NO−log₂(1−p)
0.35 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
1130541205933882688360185425371991767475416734436685663838593295067233583535- NO token ID
38880446123235159437018881085394937434582261054784538202184279445551840485959- Snapshot fetched
- 2026-06-20 12:15:31 UTC
- Snapshot age
- 3.5s
- History points
- 25 CLOB mids
- Page rendered
- 2026-06-20 12:15:35 UTC
- Storage policy
- no persistence — fetched on every request
- SHA-256 attestation
67a6c60627b2a61beebf611d971d60d71b7b0a22d1668004915318932569145f· deterministic hash of source snapshot- Open data licence
- CC0 / public domain
§∞-2 · Related markets · explore more
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Also see: /arb opportunities · RSS feed · more in Elon Musk # tweets June 16 - June 23, 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
0.215000
(best bid + best ask) / 2
Spread
465.1bp
(bestAsk − bestBid) / mid
Imbalance (whole book)
-0.181
ask-heavy
Imbalance (top-5)
-0.493
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-16-june-23-160-179/slippage?size=10000&side=buy
| Side | Notional | Avg fill | Slippage | Worst fill | Levels | Status |
|---|---|---|---|---|---|---|
| BUY | $1.00K | 0.237813 | 1061.07bp | 0.250000 | 4 | FILLED |
| BUY | $10.00K | 0.357268 | 6617.12bp | 0.530000 | 28 | FILLED |
| BUY | $100.00K | 0.767940 | 25718.13bp | 0.930000 | 50 | FILLED |
| SELL | $1.00K | 0.157822 | 2659.44bp | 0.130000 | 9 | FILLED |
| SELL | $10.00K | 0.040560 | 8113.49bp | 0.010000 | 21 | PARTIAL |
| SELL | $100.00K | 0.040560 | 8113.49bp | 0.010000 | 21 | PARTIAL |
Risk metrics
▸ sovereign store · 999 barsperiods/year ≈ 1.75MRealized vol (annualised)
1128.84%
σ per bar = 0.008527
Mean return (annualised)
69174.64%
μ per bar = 0.000395
Sharpe (rf=0)
61.28
annualised; risk-free assumed zero
Max drawdown
12.20%
peak 0.20 → trough 0.18 over 184 bars
/api/asset/pm-elon-musk-of-tweets-june-16-june-23-160-179/risk · same metrics, JSON