polymarket-arbitrage

# Polymarket Arbitrage Strategy **PARENT**: This is a sub-strategy of `paper-trader`. Portfolio-level rules in `../../SKILL.md` take precedence. **ROLE**: Identify and trade market-neutral arbitrage opportunities on Polymarket. ## Orchestrator Integration **Report to parent orchestrator:** - Log all arbs to `references/arb_journal.md` - Parent reads this for unified portfolio view - Parent enforces cross-strategy risk limits **Check parent before trading:** - Verify portfolio-level exposure limits in `../../references/master_portfolio.md` - Check correlation with PM Research positions (same markets) - Respect parent's risk level (🟢/🟡/🟠/🔴) **Your job within the system:** 1. Identify mispriced markets and arbitrage opportunities 2. Paper trade with documented reasoning 3. Track performance and update this skill with learnings 4. Strategy-level Telegram updates flow through parent orchestrator ## Reference Files - `references/arb_journal.md` - All arb logs - `references/strategy_evolution.md` - Strategy iterations - `references/market_correlations.md` - Known relationships - `../../references/rick_preferences.md` - Rick's preferences (parent level) ## 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`:** ```markdown ## 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: ```markdown ## 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`**: ```markdown ## 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]