POLYMARKET · PREDICTION MARKET · ELON MUSK # TWEETS JUNE 16 - JUNE 23, 2026?
Will Elon Musk post 60-79 tweets from June 16 to June 23, 2026?
0.4¢
99.6¢
▸ Advanced metrics · M2M bundle
polymarket · elon-musk-of-tweets-june-16-june-23-60-79 · fresh · feed 0s old24h sparkline · 60 pts▲ 700.00%
realized vol (ann.)
6.78%
max drawdown
44.44%
sharpe
—
ulcer index
11.97%
RMS drawdown
pain index
5.49%
mean drawdown
mod. VaR 95%
0.00%
Cornish-Fisher
martin ratio
—
ret / ulcer
CDaR 95%
24.89%
cond. drawdown
gain/pain
1.75
Σgain / Σ|loss|
sterling
—
ret / CDaR
omega (θ=0)
1.75
upside/downside
roll spread
4.0 bps
implied (price-only)
bars used
2000
store
spread
—
24h Δ
700.00%
flow lean
—
carry
flat
signalNEUTRALconfidence 25%
- 24h change +700.00%
Same bundle via M2M API:
/api/m2m/pm-elon-musk-of-tweets-june-16-june-23-60-79/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
0.4¢
NO · live
99.6¢
25 ticks · last 0.40¢
Σ 100.00% · fair
Σ-sides total = 100.00% (tight rounding)
H(p) entropy = 0.038 / 1.00 bits (4%) · informative — one side favoured
YES0.4%0.4¢250.00×▬ +0.00pp
NO99.6%99.6¢1.00×▬ +0.00pp
Σ 100.00% · arb gap 0.00pp
Σ 75bp moved · peak 20bp · n=24 ticks
4ms
0.40¢ (0.40%)
99.60¢ (99.60%)
100.00%
0.000pp
$45.6k
$65.3k
25 ticks (live)
§1 · 24h price history (YES + NO tokens)
25 YES observations from clob.polymarket.com · last 0.40¢
25 NO observations from clob.polymarket.com · last 99.60¢
§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=-1.77)
FIVE-NUMBER SUMMARY · BOX PLOT
SKEWNESS · G₁0.052approximately symmetric
−3−10+1+3
EXCESS KURTOSIS · G₂-1.766platykurtic · 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: MEAN-REVERTING · ρ(1) -0.22 + ADF rejected
HURST EXPONENT [0, 1]
H = 0.810STRONGLY 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
0.40¢
99.60¢
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
YES250.00×(0¢)NO1.00×(100¢)
Kelly bet-size (% of bankroll) K* = 0.00%
Entropy H(p̂) = 0.038 bits (4% 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 · LOWresolves 2026-06-23 16:00 UTC
8days
22hrs
57min
YES →$1.00
NO →$0.00
current: $0.0040 · expected return per side: $1.00 on YES hit · $0.00 on NO hit
Theta progression · θ ∝ σ / √t_remainingθ_now = 0.774 pp/day
now8.96d left0.774 pp/day×1.00
−25%6.72d left0.894 pp/day×1.15
−50%4.48d left1.095 pp/day×1.41
−75%2.24d left1.548 pp/day×2.00
−90%21.50h left2.448 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 · 1 down · best 0.15% · worst -0.20% · typical |Δ| 0.031%
§10 · Equity curve & underwater drawdown
final equity 1.0035 (0.35%) · max DD -0.20% · time-under-water 4/25 bars
§11 · Rolling-window statistics (w = 6 bars)
latest 0.000 · range [-26.58, 60.42] · μ 31.690 · positive Sharpe = excess-return-per-risk earned by buying-and-holding through this window
latest 9.82% · range [0.00%, 9.82%] · μ 5.29% · σ̂ scaled to annualised (×√8760)
latest -0.273 · |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)
2 of 5 REJECT · mixed evidence2 reject·3 pass·1 n/a·α = 0.05
Jarque-Bera
REJECT H₀***H₀: Δp ~ Normal(μ, σ²)
STATISTIC
37.0476
p-VALUE (log scale)
< 0.0001
Ljung-Box(h=5)
FAIL TO REJECTnsH₀: No serial autocorrelation up to lag 5
STATISTIC
1.7632
p-VALUE (log scale)
0.8813
Dickey-Fuller (τ_μ)
FAIL TO REJECTnsH₀: p has a unit root (non-stationary)
STATISTIC
-1.0196
p-VALUE (log scale)
0.7446
Wald-Wolfowitz runs
N/An/aH₀: Sign sequence of Δ is random
STATISTIC
—
p-VALUE (log scale)
—
KPSS (μ stationarity)
REJECT H₀**H₀: p IS level-stationary
STATISTIC
0.8285
p-VALUE (log scale)
0.0061
Variance ratio q=3
FAIL TO REJECTnsH₀: Δp is a random walk · VR = 1
STATISTIC
-1.0198
p-VALUE (log scale)
0.3078
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 ≈ 2.00h (freq 0.500) · concentrates 24.0% of total energy · Σ|X̂|²/n = 5.250e-6
▸ Depth section using sovereign-store price series (3979 bars · effective 1752908 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 9.0 d · σ/bar 0.004pp · expected |Δp| over horizon 0.06ppterminal variance p(1−p) = 0.0040 · n = 3979✓ n = 3979
μ per bar
+0.000pp
average Δp · drift
σ per bar
0.004pp
one-bar volatility · logit-free
Per-day movedaily
0.02pp
σ × √24
Per-horizon move9d
0.06pp
σ × √214.963585
Terminal variancebinary
0.0040
p(1−p) at resolution
Current pricep
0.4¢
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 0.01pp · ES₉₅ 0.01pp · method parametric · drift-correcteddrift +0.000pp/bar · quantised: yes · median step 0.10pp · unique ratio 0.00✓ n = 3979
VaR 95%
0.01pp
1.645·σ (parametric) of Δp
ES 95%
0.01pp
mean of the tail
Max drawdown
44.4pp
peak 0.4¢ → trough 0.3¢
Median step
0.10pp
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
0.4%
= price
Decimal oddsEU
250.000
total return per $1
AmericanUS
+24900
$100 wins $24900
FractionalUK
249.00 / 1
profit per $1 risked
Profit per $100stake
+$24900.00
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)
0.038 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.038 bit
Δ +0.000 bit vs market
Surprise · YES−log₂ p
7.97 bit
self-information
Surprise · NO−log₂(1−p)
0.01 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
86708258490710537956203309257867059198968962301448519716731833687948973051995- NO token ID
86944547605161640751531128403289010308599113284447515461743566947481896093281- Snapshot fetched
- 2026-06-14 17:02:11 UTC
- Snapshot age
- 4ms
- History points
- 25 CLOB mids
- Page rendered
- 2026-06-14 17:02:11 UTC
- Storage policy
- no persistence — fetched on every request
- SHA-256 attestation
8a961e21c44e17b975a504c5ed72cb3c84e09442366886f864e053f07eeff9bb· deterministic hash of source snapshot- Open data licence
- CC0 / public domain
§∞-2 · Related markets · explore more
HL PREDGermany93.5¢HL PREDSpain89.5¢HL PREDUruguay66.9¢POLYMARKETWill Australia win the 2026 FIFA World Cup?0¢POLYMARKETWill Scotland win the 2026 FIFA World Cup?0¢POLYMARKETWill Curaçao win on 2026-06-14?2¢HL PERPBTC-USD perpetual$63,928HL PERPETH-USD perpetual$1,661.6HL PERPHYPE-USD perpetual$60.08
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
0.004000
(best bid + best ask) / 2
Spread
5000.0bp
(bestAsk − bestBid) / mid
Imbalance (whole book)
-0.834
ask-heavy
Imbalance (top-5)
+0.266
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-elon-musk-of-tweets-june-16-june-23-60-79/slippage?size=10000&side=buy
| Side | Notional | Avg fill | Slippage | Worst fill | Levels | Status |
|---|---|---|---|---|---|---|
| BUY | $1.00K | 0.027609 | 59021.30bp | 0.095000 | 30 | FILLED |
| BUY | $10.00K | 0.159019 | 387547.79bp | 0.500000 | 81 | FILLED |
| BUY | $100.00K | 0.607790 | 1509474.24bp | 0.930000 | 93 | FILLED |
| SELL | $1.00K | 0.001223 | 6941.95bp | 0.001000 | 3 | PARTIAL |
| SELL | $10.00K | 0.001223 | 6941.95bp | 0.001000 | 3 | PARTIAL |
| SELL | $100.00K | 0.001223 | 6941.95bp | 0.001000 | 3 | PARTIAL |
Risk metrics
▸ sovereign store · 3,979 barsperiods/year ≈ 1.75MRealized vol (annualised)
2952.33%
σ per bar = 0.022299
Mean return (annualised)
91630.70%
μ per bar = 0.000523
Sharpe (rf=0)
31.04
annualised; risk-free assumed zero
Max drawdown
44.44%
peak 0.00 → trough 0.00 over 464 bars
/api/asset/pm-elon-musk-of-tweets-june-16-june-23-60-79/risk · same metrics, JSON