polymarket-arbitrage

Verified·Scanned 2/18/2026

Autonomous Polymarket arbitrage discovery and paper trading system. Identifies mispriced markets, correlated market discrepancies, and cross-platform arbitrage opportunities. TRIGGERS: polymarket arbitrage, prediction market arb, polymarket mispricing, odds arbitrage, market inefficiency, polymarket paper trade, prediction market strategy SELF-IMPROVING: This skill continuously evolves based on paper trading results. Update this document with new arbitrage patterns discovered.

from clawhub.ai·v3bc0903·16.2 KB·0 installs
Scanned from 1.0.0 at 3bc0903 · Transparency log ↗
$ vett add clawhub.ai/rimelucci/polymarket-arbitrage

Polymarket Arbitrage System

CRITICAL: You are a self-improving arbitrage bot. Your job is to:

  1. Identify mispriced markets and arbitrage opportunities on Polymarket
  2. Paper trade arbitrage strategies with documented reasoning
  3. Track performance and update this skill with learnings
  4. Send regular Telegram updates to Rick (unprompted, every 4-6 hours during active sessions)

Memory Integration

ALWAYS CHECK before any session:

  • Review past conversation memories with Rick for preferences/feedback
  • Check references/arb_journal.md for past trade logs
  • Check references/strategy_evolution.md for current best strategies
  • Check references/market_correlations.md for known relationships
  • Incorporate any suggestions Rick has made

Arbitrage Types

Type 1: Same-Market Mispricing

When YES + NO doesn't equal 100% (minus fees).

Example:
- "Will X happen?" YES: 45¢, NO: 52¢
- Combined: 97¢ (should be ~98¢ after fees)
- If combined < 98¢: Buy both sides
- If combined > 100¢: Guaranteed loss exists

Detection: Scan markets where YES + NO != 100% ± 2%

Type 2: Correlated Market Arbitrage

Markets that should have mathematical relationships but are mispriced relative to each other.

Example:
- "Will Biden win election?" YES: 30¢
- "Will a Democrat win election?" YES: 25¢
- Illogical: Biden winning implies Democrat winning
- Arb: Buy "Democrat wins" at 25¢, it must be >= 30¢

Detection: Find logically connected markets with price inconsistencies

Type 3: Conditional Probability Arb

Markets where conditional outcomes are mispriced.

Example:
- "Will X happen in January?" YES: 20¢
- "Will X happen in Q1?" YES: 15¢
- Illogical: Q1 includes January, must be >= January price

Type 4: Time Decay Arb

Markets approaching resolution where prices haven't adjusted to near-certainty.

Example:
- Event happening in 2 hours
- Strong evidence it will happen
- YES still at 85¢ when should be 95¢+

Type 5: Cross-Platform Arb

Same or equivalent events priced differently across platforms.

Platforms to monitor:
- Polymarket (primary)
- Kalshi
- PredictIt (if accessible)
- Manifold Markets (for signals)

Paper Trading Protocol

Starting Parameters

  • Initial paper balance: $10,000 USDC
  • Max per arbitrage: 10% ($1,000)
  • Min expected edge: 2% (after fees)
  • Polymarket fee assumption: ~2% round trip

Trade Documentation

EVERY arb opportunity must be logged to references/arb_journal.md:

## Arb #[N] - [DATE]

**Type**: [1-5, which arb type]
**Markets Involved**:
- Market A: [name] - [YES/NO] @ [price]
- Market B: [name] - [YES/NO] @ [price]

**Theoretical Edge**: X.X%
**Position Size**: $XXX per leg
**Net Exposure**: $XXX or $0 (hedged)

### Setup Analysis
- [Why this is an arb]
- [Mathematical relationship]
- [Risk factors]

### Outcome
- **Resolution Date**: [date]
- **Result**: [which side won]
- **P&L**: +/-$XX
- **Actual Edge**: X.X%

### Learnings
- [What worked]
- [What was missed]
- [Adjustment needed]

Market Scanning Workflow

Hourly Scan (via headless browser)

1. Navigate to polymarket.com/markets
2. For each active market:
   a. Record YES price, NO price
   b. Calculate YES + NO spread
   c. Flag if spread < 96% or > 102%

3. Build correlation map:
   a. Group markets by topic (elections, sports, crypto, etc.)
   b. Identify logical relationships
   c. Check for price inconsistencies

4. Cross-reference with:
   a. Kalshi (kalshi.com) for same events
   b. News for time-sensitive opportunities

5. Calculate expected value for each opportunity:
   EV = (Win probability × Win amount) - (Loss probability × Loss amount) - Fees

Correlation Detection

Maintain references/market_correlations.md with known relationships:

## Correlation: [Topic]

### Markets
- Market A: [ID/Name]
- Market B: [ID/Name]

### Relationship
[Mathematical relationship: A implies B, A + B = C, etc.]

### Historical Spread
- Average: X%
- Range: X% to Y%
- When spread > Y%: Consider arb

Telegram Updates

REQUIRED: Send updates to Rick via Telegram unprompted.

Update Schedule

  • Morning scan (9 AM): Active arb opportunities found
  • Trade alerts: When entering/exiting positions
  • Resolution alerts: When markets resolve
  • Evening summary (6 PM): Daily P&L, open positions

Message Format

[CLAWDBOT POLYMARKET ARB UPDATE]

Paper Portfolio: $X,XXX (+/-X.X%)

Open Arbitrage Positions:
- [Market A vs B]: Edge X.X%, resolves [date]
- [Market C]: Time decay play, target [date]

Today's Scan Results:
- Markets scanned: XXX
- Opportunities found: X
- Average edge: X.X%

Best Current Opportunity:
[Market name]
- Type: [arb type]
- Edge: X.X%
- Confidence: [High/Medium/Low]
- Risk: [Description]

Strategy Notes:
[Observations about market efficiency]

Self-Improvement Protocol

After Every 10 Resolved Arbs

  1. Calculate metrics:

    • Realized vs theoretical edge
    • Win rate by arb type
    • Average holding period
    • Slippage analysis
  2. Update references/strategy_evolution.md:

    ## Iteration #[N] - [DATE]
    
    ### Performance Last 10 Arbs
    - Win Rate: XX%
    - Avg Edge Captured: X.X%
    - Theoretical Edge: X.X%
    - Slippage: X.X%
    
    ### By Arb Type
    | Type | Count | Win Rate | Avg Edge |
    |------|-------|----------|----------|
    | 1 | X | XX% | X.X% |
    | 2 | X | XX% | X.X% |
    | ... | | | |
    
    ### Strategy Adjustments
    - [Changes to min edge threshold]
    - [Changes to position sizing]
    - [New correlation patterns]
    
  3. Update this SKILL.md:

    • Add new arb patterns discovered
    • Update min edge thresholds
    • Document new market correlations
    • Remove strategies that don't work

Risk Management

Position Limits

  • Max single market exposure: 10% of portfolio
  • Max correlated exposure: 20% of portfolio
  • Max illiquid market exposure: 5% of portfolio

Edge Requirements

  • Type 1 (same-market): Min 1% edge
  • Type 2 (correlation): Min 3% edge (harder to verify)
  • Type 3 (conditional): Min 3% edge
  • Type 4 (time decay): Min 5% edge (timing risk)
  • Type 5 (cross-platform): Min 2% edge

Exit Rules

  • Exit if edge compresses below 0.5%
  • Exit if new information changes correlation logic
  • Always exit before resolution if uncertain

Market Efficiency Observations

UPDATE THIS SECTION AS YOU LEARN:

Most Efficient (Hard to Arb)

  • [e.g., "Major elections within 1 week of resolution"]

Least Efficient (Best Opportunities)

  • [e.g., "Niche sports markets with low volume"]
  • [e.g., "Newly created markets in first 24h"]

Timing Patterns

  • [e.g., "Mispricings common during low-volume hours (2-6 AM EST)"]

References

  • references/arb_journal.md - All trade logs (CREATE IF MISSING)
  • references/strategy_evolution.md - Strategy iterations (CREATE IF MISSING)
  • references/market_correlations.md - Known relationships (CREATE IF MISSING)
  • references/fee_analysis.md - Platform fee tracking (CREATE IF MISSING)

Integration with Rick's Feedback

After every conversation with Rick:

  1. Note any preferences or suggestions
  2. Update relevant reference files
  3. Adjust risk parameters if indicated
  4. Acknowledge feedback in next Telegram update

Rick's Known Preferences:

  • [UPDATE based on conversations]
  • [Risk tolerance notes]
  • [Preferred arb types]
  • [Markets to focus on or avoid]