POLYMARKET · PREDICTION MARKET · POLITICS
Will Shimelis Abdisa be the next Prime Minister of Ethiopia?
2.1¢
98.0¢
▸ Advanced metrics · M2M bundle
polymarket · will-shimelis-abdisa-be-the-next-prime-minister-of-ethiopia · fresh · feed 0s old24h sparkline · 60 pts▼ —
realized vol (ann.)
103.59%
max drawdown
33.87%
sharpe
—
ulcer index
23.07%
RMS drawdown
pain index
15.72%
mean drawdown
mod. VaR 95%
0.00%
Cornish-Fisher
martin ratio
—
ret / ulcer
CDaR 95%
33.87%
cond. drawdown
gain/pain
0.00
Σgain / Σ|loss|
sterling
—
ret / CDaR
omega (θ=0)
0.00
upside/downside
roll spread
45.0 bps
implied (price-only)
bars used
181
store
spread
—
24h Δ
—
flow lean
—
carry
flat
signalNEUTRALconfidence 20%
Same bundle via M2M API:
/api/m2m/pm-will-shimelis-abdisa-be-the-next-prime-minister-of-ethiopia/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
2.1¢
NO · live
98.0¢
25 ticks · last 2.05¢
Σ 100.00% · fair
Σ-sides total = 100.00% (tight rounding)
H(p) entropy = 0.144 / 1.00 bits (14%) · informative — one side favoured
YES2.1%2.1¢48.78×▬ +0.00pp
NO98.0%98.0¢1.02×▬ +0.00pp
Σ 100.00% · arb gap 0.00pp
Σ 3670bp moved · peak 1900bp · n=24 ticks
27ms
2.05¢ (2.05%)
97.95¢ (97.95%)
100.00%
0.000pp
$148.4k
$13.3k
25 ticks (live)
§1 · 24h price history (YES + NO tokens)
25 YES observations from clob.polymarket.com · last 2.05¢
25 NO observations from clob.polymarket.com · last 97.95¢
§2 · Distribution of Δp
n=24
reference line = identity (perfect normality). Heavy upper-right tail = fat positive tail.
§3 · Sample moments
SAMPLE MOMENTS · N=25LEPTOKURTIC · FAT TAILS (G₂=2.74)
FIVE-NUMBER SUMMARY · BOX PLOT
SKEWNESS · G₁2.121right-skewed
−3−10+1+3
EXCESS KURTOSIS · G₂2.735leptokurtic · fat 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: MARTINGALE · UNPREDICTABLE
HURST EXPONENT [0, 1]
H = 0.811STRONGLY 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
2.05¢
97.95¢
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
YES48.78×(2¢)NO1.02×(98¢)
Kelly bet-size (% of bankroll) K* = 0.00%
Entropy H(p̂) = 0.144 bits (14% 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.
§9 · Hourly return heatmap
2 up bars · 8 down · best 19.00% · worst -15.15% · typical |Δ| 1.529%
§10 · Equity curve & underwater drawdown
final equity 0.9852 (-1.48%) · max DD -16.92% · time-under-water 20/25 bars
§11 · Rolling-window statistics (w = 6 bars)
latest 2.509 · range [-38.21, 37.73] · μ -5.278 · positive Sharpe = excess-return-per-risk earned by buying-and-holding through this window
latest 1018.30% · range [0.00%, 1018.30%] · μ 278.11% · σ̂ scaled to annualised (×√8760)
latest 0.030 · |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
REJECT H₀***H₀: Δp ~ Normal(μ, σ²)
STATISTIC
151.5238
p-VALUE (log scale)
< 0.0001
Ljung-Box(h=5)
FAIL TO REJECTnsH₀: No serial autocorrelation up to lag 5
STATISTIC
7.1439
p-VALUE (log scale)
0.2090
Dickey-Fuller (τ_μ)
FAIL TO REJECTnsH₀: p has a unit root (non-stationary)
STATISTIC
-2.0985
p-VALUE (log scale)
0.2548
Wald-Wolfowitz runs
FAIL TO REJECTnsH₀: Sign sequence of Δ is random
STATISTIC
0.9045
p-VALUE (log scale)
0.3657
KPSS (μ stationarity)
FAIL TO REJECTnsH₀: p IS level-stationary
STATISTIC
0.3530
p-VALUE (log scale)
0.0974
Variance ratio q=3
FAIL TO REJECTnsH₀: Δp is a random walk · VR = 1
STATISTIC
0.4402
p-VALUE (log scale)
0.6598
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 15.4% of total energy · Σ|X̂|²/n = 3.208e-2
▸ Depth section using sovereign-store price series (181 bars · effective 1753200 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 0.078pp · expected |Δp| over horizon 0.19ppterminal variance p(1−p) = 0.0201 · n = 181✓ n = 181
μ per bar
-0.006pp
average Δp · drift
σ per bar
0.078pp
one-bar volatility · logit-free
Per-day movedaily
0.38pp
σ × √24
Per-horizon move0d
0.19pp
σ × √6
Terminal variancebinary
0.0201
p(1−p) at resolution
Current pricep
2.1¢
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 0.13pp · ES₉₅ 0.17pp · method parametric · drift-correcteddrift -0.006pp/bar · quantised: yes · median step 1.05pp · unique ratio 0.01⚠ low confidence · n < 200
VaR 95%
0.13pp
1.645·σ (parametric) of Δp
ES 95%
0.17pp
mean of the tail
Max drawdown
33.9pp
peak 3.1¢ → trough 2.1¢
Median step
1.05pp
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
2.1%
= price
Decimal oddsEU
48.780
total return per $1
AmericanUS
+4778
$100 wins $4778
FractionalUK
47.78 / 1
profit per $1 risked
Profit per $100stake
+$4778.05
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)
0.144 bit
max 1.0 at p = 0.5
Your entropyH(q)
0.144 bit
Δ +0.000 bit vs market
Surprise · YES−log₂ p
5.61 bit
self-information
Surprise · NO−log₂(1−p)
0.03 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
4489049127093187435445530909063903861654656526363504166478270583011546818111- NO token ID
25722831118938263747933513466544465949348258789327262382514030421129575874093- Snapshot fetched
- 2026-06-14 20:42:15 UTC
- Snapshot age
- 27ms
- History points
- 25 CLOB mids
- Page rendered
- 2026-06-14 20:42:15 UTC
- Storage policy
- no persistence — fetched on every request
- SHA-256 attestation
cebee2612e90c22ba9dd4d12d09e6f53e43c80c38981299e6f26f6bc4b2f1a64· deterministic hash of source snapshot- Open data licence
- CC0 / public domain
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Also see: /arb opportunities · RSS feed · more in Politics
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
0.020500
(best bid + best ask) / 2
Spread
18048.8bp
(bestAsk − bestBid) / mid
Imbalance (whole book)
-0.537
ask-heavy
Imbalance (top-5)
+0.246
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-will-shimelis-abdisa-be-the-next-prime-minister-of-ethiopia/slippage?size=10000&side=buy
| Side | Notional | Avg fill | Slippage | Worst fill | Levels | Status |
|---|---|---|---|---|---|---|
| BUY | $1.00K | 0.203649 | 89340.77bp | 0.439000 | 12 | FILLED |
| BUY | $10.00K | 0.613235 | 289138.91bp | 0.899000 | 29 | FILLED |
| BUY | $100.00K | 0.711498 | 337072.37bp | 0.999000 | 37 | PARTIAL |
| SELL | $1.00K | 0.001306 | 9362.97bp | 0.001000 | 2 | PARTIAL |
| SELL | $10.00K | 0.001306 | 9362.97bp | 0.001000 | 2 | PARTIAL |
| SELL | $100.00K | 0.001306 | 9362.97bp | 0.001000 | 2 | PARTIAL |
Risk metrics
▸ sovereign store · 181 barsperiods/year ≈ 1.75MRealized vol (annualised)
4081.51%
σ per bar = 0.030825
Mean return (annualised)
-402809.70%
μ per bar = -0.002298
Sharpe (rf=0)
-98.69
annualised; risk-free assumed zero
Max drawdown
33.87%
peak 0.03 → trough 0.02 over 97 bars
/api/asset/pm-will-shimelis-abdisa-be-the-next-prime-minister-of-ethiopia/risk · same metrics, JSON