PolymarketIntel

PolymarketIntel — System Architecture

An autonomous whale-following trading bot that monitors Polymarket blockchain transactions in real time, scores insider-signal probability, sizes positions via Kelly Criterion, and manages risk across multiple kill-switch layers.

4
Scoring Weights
4
Kill Switches
57+
Insider Keywords
2
Venues

Real-Time Signal Detection

Monitors Polymarket blockchain transactions in real time with a resilient RPC layer and automatic failover.

5-block lag
Chain Safety
Circuit breaker
RPC Failover
300s
Watchdog Timeout
3
Background Jobs
  • Price capture, wallet monitoring, batch grading
  • Auto-reconnect with exponential back-off
  • Watchdog supervisor restarts stalled processes

🎯Composite Scoring Engine

4-weight scoring system that evaluates every whale trade for insider-signal probability. Score ≥ 0.6 triggers an alert.

30%
Trade Size
25%
Wallet Novelty
25%
Market Sensitivity
20%
Conviction
  • 57+ insider-prone keywords (assassination, arrest, hack, merger …)
  • Tiered alerts: Tier 1-4 based on composite score
  • Anti-spam: wallet cooldown 180s, market cooldown 60s

📐Kelly Criterion Position Sizing

Optimal bet sizing via the Kelly formula with fractional scaling, confidence throttling, and hard guardrails.

f* = (p·b − q) / b
0.25–0.5×
Fractional Kelly
0.5–1.5×
Score Boost
0.7–1.3×
Wallet Boost
10%
Max Per Trade
  • Confidence throttle: linear or logistic curve
  • Portfolio heat limit + per-market concentration cap
  • Tier fallback: T1=15%, T2=10%, T3=6%, T4=3%

🛡️Multi-Layered Risk Management

4 independent kill switches, a risk governor, and graduated escalation with full audit trails.

>25%
Portfolio DD
>10%
Intraday DD
>3σ
Vol Anomaly
Feed check
Data Integrity
  • Rolling drawdown window with daily loss limits
  • Graduated escalation levels (warn → throttle → halt)
  • State persistence across restarts
  • Every decision logged with audit trail

🧪Backtesting & Validation

Historical trade replay against ground-truth outcomes with per-tier accuracy metrics and regression detection.

Win rate + P&L
Metrics
p25–p99
Percentiles
Frozen schemas
Baselines
Auto-detect
Regression
  • Score distribution: p25, p50, p75, p90, p95, p99
  • Compare-to-baseline with configurable thresholds
  • Per-tier accuracy breakdown (win rate, expected value)

🔄Cross-Venue Arbitrage

Detects pricing discrepancies between Polymarket and Kalshi with a two-step evaluate → execute pipeline.

$3K total
Capital Limit
$1K
Per Pair
$2K
Per Venue
Paper
Mode
  • Slippage model: venue floors + depth impact + latency penalty
  • Shadow P&L tracking vs paper execution comparison
  • Two-step pipeline: evaluate() then execute()

🔍Deterministic Replay & Drift Detection

Decision fingerprinting with SHA-256, parity checking every 60 s, and multi-sigma drift alerting.

SHA-256
Fingerprint
Last 5 / 60s
Replay
3+ mismatches
Halt
100 points
Window
  • Drift thresholds: 1.5σ info, 2.0σ warn, 3.0σ kill recommend
  • Rolling 100-point statistical windows
  • Config versioning — every decision stores config_id

🧬Alpha Tuning & Convergence

4 Quick-Win filters, multi-whale convergence detection, automated calibration grid search, and a single-source-of-truth config.

4 active
Quick Wins
2+ wallets
Convergence
100 combos
Grid Search
PARAMS.yaml
Config
  • Gambling filter: $5K+ on long-shots
  • Hot wallet boost: +0.15 for 80%+ recent win rate
  • Category limit: max 2 positions per category
  • Context floor: market score ≥ 60 OR wallet score ≥ 45