POLYMARKET · PREDICTION MARKET · ELON MUSK # TWEETS JUNE 13 - JUNE 15, 2026?
Will Elon Musk post 40-64 tweets from June 13 to June 15, 2026?
28.5¢
71.5¢
▸ Advanced metrics · M2M bundle
polymarket · elon-musk-of-tweets-june-13-june-15-40-64 · 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-elon-musk-of-tweets-june-13-june-15-40-64/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
28.5¢
NO · live
71.5¢
25 ticks · last 28.50¢
Σ 100.00% · fair
Σ-sides total = 100.00% (tight rounding)
H(p) entropy = 0.862 / 1.00 bits (86%) · high uncertainty
YES28.5%28.5¢3.51×▬ +0.00pp
NO71.5%71.5¢1.40×▬ +0.00pp
Σ 100.00% · arb gap 0.00pp
Σ 6800bp moved · peak 900bp · n=24 ticks
4ms
28.50¢ (28.50%)
71.50¢ (71.50%)
100.00%
0.000pp
$50.7k
$13.7k
25 ticks (live)
§1 · 24h price history (YES + NO tokens)
25 YES observations from clob.polymarket.com · last 28.50¢
25 NO observations from clob.polymarket.com · last 71.50¢
§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=0.72)
FIVE-NUMBER SUMMARY · BOX PLOT
SKEWNESS · G₁0.718right-skewed
−3−10+1+3
EXCESS KURTOSIS · G₂-1.030platykurtic · 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 = 0.937STRONGLY 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
28.50¢
71.50¢
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
YES3.51×(28¢)NO1.40×(72¢)
Kelly bet-size (% of bankroll) K* = 0.00%
Entropy H(p̂) = 0.862 bits (86% of max) · high 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 · HIGHresolves 2026-06-15 16:00 UTC
0days
20hrs
46min
YES →$1.00
NO →$0.00
current: $0.2850 · expected return per side: $0.72 on YES hit · $0.28 on NO hit
Theta progression · θ ∝ σ / √t_remainingθ_now = 46.941 pp/day
now20.78h left46.941 pp/day×1.00
−25%15.58h left54.203 pp/day×1.15
−50%10.39h left66.385 pp/day×1.41
−75%5.19h left93.882 pp/day×2.00
−90%2.08h left148.441 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
5 up bars · 14 down · best 8.00% · worst -9.00% · typical |Δ| 2.833%
§10 · Equity curve & underwater drawdown
final equity 0.7723 (-22.77%) · max DD -27.67% · time-under-water 23/25 bars
§11 · Rolling-window statistics (w = 6 bars)
latest 3.431 · range [-89.24, 22.09] · μ -34.348 · positive Sharpe = excess-return-per-risk earned by buying-and-holding through this window
latest 425.49% · range [98.16%, 494.08%] · μ 350.11% · σ̂ scaled to annualised (×√8760)
latest -0.232 · |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
2.3551
p-VALUE (log scale)
0.3080
Ljung-Box(h=5)
FAIL TO REJECTnsH₀: No serial autocorrelation up to lag 5
STATISTIC
0.3870
p-VALUE (log scale)
0.9940
Dickey-Fuller (τ_μ)
FAIL TO REJECTnsH₀: p has a unit root (non-stationary)
STATISTIC
-1.7295
p-VALUE (log scale)
0.4240
Wald-Wolfowitz runs
FAIL TO REJECTnsH₀: Sign sequence of Δ is random
STATISTIC
-0.2282
p-VALUE (log scale)
0.8195
KPSS (μ stationarity)
REJECT H₀*H₀: p IS level-stationary
STATISTIC
0.6867
p-VALUE (log scale)
0.0148
Variance ratio q=3
FAIL TO REJECTnsH₀: Δp is a random walk · VR = 1
STATISTIC
-0.0617
p-VALUE (log scale)
0.9508
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 ≈ 4.00h (freq 0.250) · concentrates 24.8% of total energy · Σ|X̂|²/n = 1.700e-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 0.9 d · σ/bar 3.845pp · expected |Δp| over horizon 17.53ppterminal variance p(1−p) = 0.2038 · n = 25⚠ low confidence · n < 100
μ per bar
-1.000pp
average Δp · drift
σ per bar
3.845pp
one-bar volatility · logit-free
Per-day movedaily
18.84pp
σ × √24
Per-horizon move1d
17.53pp
σ × √20.77711027777778
Terminal variancebinary
0.2038
p(1−p) at resolution
Current pricep
28.5¢
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 7.32pp · ES₉₅ 8.93pp · method parametric · drift-correcteddrift -1.000pp/bar · quantised: yes · median step 1.00pp · unique ratio 0.72⊘ disabled · n < 30
VaR 95%
7.32pp
1.645·σ (parametric) of Δp
ES 95%
8.93pp
mean of the tail
Max drawdown
56.9pp
peak 54.5¢ → trough 23.5¢
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
28.5%
= price
Decimal oddsEU
3.509
total return per $1
AmericanUS
+251
$100 wins $251
FractionalUK
2.51 / 1
profit per $1 risked
Profit per $100stake
+$250.88
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)
0.862 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.862 bit
Δ +0.000 bit vs market
Surprise · YES−log₂ p
1.81 bit
self-information
Surprise · NO−log₂(1−p)
0.48 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
105577993048948109580713045276679542431413340762946402420115963849346865805857- NO token ID
39577234398414241613289748679241795149829793792284485248363350884887923488707- Snapshot fetched
- 2026-06-14 19:13:22 UTC
- Snapshot age
- 4ms
- History points
- 25 CLOB mids
- Page rendered
- 2026-06-14 19:13:22 UTC
- Storage policy
- no persistence — fetched on every request
- SHA-256 attestation
87a3c395fa77aa188b905d197b93f7afa6975e36f850ae024f7c0d29d4fccfdf· 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 13 - June 15, 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
0.285000
(best bid + best ask) / 2
Spread
350.9bp
(bestAsk − bestBid) / mid
Imbalance (whole book)
-0.570
ask-heavy
Imbalance (top-5)
+0.060
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-13-june-15-40-64/slippage?size=10000&side=buy
| Side | Notional | Avg fill | Slippage | Worst fill | Levels | Status |
|---|---|---|---|---|---|---|
| BUY | $1.00K | 0.329863 | 1574.15bp | 0.370000 | 9 | FILLED |
| BUY | $10.00K | 0.572575 | 10090.37bp | 0.890000 | 36 | FILLED |
| BUY | $100.00K | 0.911800 | 21993.00bp | 0.990000 | 43 | FILLED |
| SELL | $1.00K | 0.231210 | 1887.38bp | 0.210000 | 8 | FILLED |
| SELL | $10.00K | 0.091215 | 6799.47bp | 0.010000 | 26 | PARTIAL |
| SELL | $100.00K | 0.091215 | 6799.47bp | 0.010000 | 26 | PARTIAL |
Risk metrics
▸ upstream candles · 25 barsRealized vol (annualised)
—
σ per bar = 0.122729
Mean return (annualised)
—
μ per bar = -0.025455
Sharpe (rf=0)
—
annualised; risk-free assumed zero
Max drawdown
56.88%
peak 0.55 → trough 0.23 over 19 bars
/api/asset/pm-elon-musk-of-tweets-june-13-june-15-40-64/risk · same metrics, JSON