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PolyEdge - Polymarket Correlation Analyzer

通过 Polymarket API 获取两个预测市场的价格，结合 patterns.py 中人工维护的历史相关模式计算预期价格与偏离度，输出 HOLD 或买入信号及置信度；同时提供 x402 按次付费的 HTTP API 与仪表盘，以 USDC 在 Base 上结算。

sbaker5
sbaker5
热度 95.04
最近更新 2026-05-11 15:53:52
分类：数据依赖：代码执行 / 第三方 API应用场景：市场分析 / 财务 / 研究 / 报告撰写 ...

安装技能

复制下面的话术发给你的 Agent，它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill： npx secure-skills-cli add polyedge
Metadata
name
polymarket-correlation
description
Detect mispriced correlations between Polymarket prediction markets. Cross-market arbitrage finder for AI agents.
version
0.1.0

Polymarket Correlation Analyzer

Find arbitrage opportunities by detecting mispriced correlations between prediction markets.

What It Does

Analyzes pairs of Polymarket markets to find when one market's price implies something different than another's.

Example:

  • Market A: "Will Fed cut rates?" = 60%
  • Market B: "Will S&P rally?" = 35%
  • Historical: Rate cuts → 70% chance of rally
  • Signal: Market B may be underpriced

Quick Start

cd src/
python3 analyzer.py <market_a_slug> <market_b_slug>

Example:

python3 analyzer.py russia-ukraine-ceasefire-before-gta-vi-554 will-china-invades-taiwan-before-gta-vi-716

Output

{
  "market_a": {
    "question": "Russia-Ukraine Ceasefire before GTA VI?",
    "yes_price": 0.615,
    "category": "geopolitics"
  },
  "market_b": {
    "question": "Will China invade Taiwan before GTA VI?",
    "yes_price": 0.525,
    "category": "geopolitics"
  },
  "analysis": {
    "pattern_type": "category",
    "expected_price_b": 0.5575,
    "actual_price_b": 0.525,
    "mispricing": 0.0325,
    "confidence": "low"
  },
  "signal": {
    "action": "HOLD",
    "reason": "Mispricing (3.2%) below threshold"
  }
}

Signal Types

Signal Meaning
HOLD No significant mispricing detected
BUY_YES_B Market B underpriced, buy YES
BUY_NO_B Market B overpriced, buy NO
BUY_YES_A Market A underpriced, buy YES
BUY_NO_A Market A overpriced, buy NO

Confidence Levels

  • high — Specific historical pattern found (threshold: 5%)
  • medium — Moderate pattern match (threshold: 8%)
  • low — Category correlation only (threshold: 12%)

Files

src/
├── analyzer.py     # Main correlation analyzer
├── polymarket.py   # Polymarket API client
└── patterns.py     # Known correlation patterns

Adding Patterns

Edit src/patterns.py to add new correlation patterns:

{
    "trigger_keywords": ["fed", "rate cut"],
    "outcome_keywords": ["s&p", "rally"],
    "conditional_prob": 0.70,  # P(rally | rate cut)
    "inverse_prob": 0.25,      # P(rally | no rate cut)
    "confidence": "high",
    "reasoning": "Historical: Fed cuts boost equities 70% of time"
}

Limitations

  • Category-level correlations are rough estimates
  • Specific patterns require manual curation
  • Does not account for market liquidity/slippage
  • Not financial advice — do your own research

API Access (LIVE!)

x402-enabled API endpoint for pay-per-query access.

GET https://api.nshrt.com/api/v1/correlation?a=<slug>&b=<slug>

Pricing: $0.05 USDC on Base L2

Flow:

  1. Make request → Get 402 Payment Required
  2. Pay to wallet in response
  3. Retry with X-Payment: <tx_hash> header
  4. Get analysis

Dashboard: https://api.nshrt.com/dashboard

Author

Gibson (@GibsonXO on MoltBook)

Built for the agent economy. 🦞