Opportunity Finder - Complete API Reference
Discover and execute cross-platform arbitrage opportunities across Polymarket, Kalshi, Betfair, Smarkets, Manifold, Metaculus, PredictIt, and Drift.
Based on arXiv:2508.03474 which found $40M+ in realized arbitrage on Polymarket.
Opportunity Types
| Type | Description | Example |
|---|---|---|
| Internal | YES + NO < $1 on same platform | Buy both for guaranteed profit |
| Cross-Platform | Same market priced differently | Buy low on A, sell high on B |
| Combinatorial | Logical violations (P(A) > P(B) when A implies B) | Trump > Republican |
| Edge | Market vs external model (538, polls) | Market 45%, model 52% |
Chat Commands
Scanning
/opportunities scan # Scan all platforms for opportunities /opportunities scan "trump" # Scan with keyword filter /opportunities scan --min-edge 2 # Min 2% edge /opportunities scan --min-liquidity 1000 # Min $1000 liquidity /opportunities active # View active opportunities /opportunities active --sort edge # Sort by edge size /opportunities active --sort liquidity # Sort by liquidity
Real-Time Monitoring
/opportunities realtime start # Start continuous scanning /opportunities realtime stop # Stop scanning /opportunities realtime status # Check monitoring status /opportunities realtime config --interval 30 # Set scan interval (seconds)
Market Linking
/opportunities link <market-a> <market-b> # Manually link equivalent markets /opportunities unlink <market-a> <market-b> # Remove link /opportunities links # View all linked markets /opportunities auto-match # Run auto-matching algorithm
Execution
/opportunities execute <id> # Execute an opportunity /opportunities execute <id> --size 100 # Execute with $100 size /opportunities mark-taken <id> # Mark as taken (manual) /opportunities record-outcome <id> <pnl> # Record P&L outcome
Analytics
/opportunities stats # Performance statistics /opportunities stats --period 7d # Last 7 days /opportunities history # Past opportunities /opportunities by-platform # Stats by platform pair /opportunities by-type # Stats by opportunity type
Risk Modeling
/opportunities risk <id> # Model execution risk /opportunities estimate <id> # Estimate execution costs /opportunities kelly <id> # Calculate Kelly fraction
TypeScript API Reference
Create Opportunity Finder
typescriptimport { createOpportunityFinder } from 'clodds/opportunity'; const finder = createOpportunityFinder({ platforms: ['polymarket', 'kalshi', 'betfair', 'manifold'], // Filtering minEdge: 0.5, // 0.5% minimum edge minLiquidity: 500, // $500 minimum liquidity minConfidence: 0.7, // 70% match confidence // Real-time enableRealtime: true, scanIntervalMs: 30000, // 30 second intervals // Credentials polymarket: { apiKey, apiSecret, passphrase, privateKey }, kalshi: { apiKey, privateKey }, });
Scan for Opportunities
typescript// One-time scan const opportunities = await finder.scan({ query: 'election', // Optional keyword minEdge: 1, // 1% minimum minLiquidity: 1000, // $1000 minimum platforms: ['polymarket', 'kalshi'], }); for (const opp of opportunities) { console.log(`${opp.type}: ${opp.description}`); console.log(` Edge: ${opp.edge.toFixed(2)}%`); console.log(` Liquidity: $${opp.liquidity.toLocaleString()}`); console.log(` Confidence: ${(opp.confidence * 100).toFixed(0)}%`); console.log(` Score: ${opp.score}/100`); console.log(` Platforms: ${opp.platforms.join(' ↔ ')}`); }
Real-Time Monitoring
typescript// Start real-time scanning await finder.startRealtime(); // Event handlers finder.on('opportunity', (opp) => { console.log(`🎯 New opportunity: ${opp.description}`); console.log(` Edge: ${opp.edge.toFixed(2)}%`); }); finder.on('opportunityExpired', (opp) => { console.log(`❌ Opportunity expired: ${opp.id}`); }); finder.on('opportunityUpdated', (opp) => { console.log(`📊 Updated: ${opp.id} - Edge now ${opp.edge.toFixed(2)}%`); }); // Get active opportunities const active = await finder.getActive(); // Stop monitoring await finder.stopRealtime();
Market Linking
typescript// Manually link equivalent markets await finder.linkMarkets( { platform: 'polymarket', id: 'market-123' }, { platform: 'kalshi', id: 'TRUMP-WIN' } ); // Auto-match using semantic similarity const matches = await finder.autoMatchMarkets({ minSimilarity: 0.85, platforms: ['polymarket', 'kalshi'], }); console.log(`Found ${matches.length} potential matches`); for (const match of matches) { console.log(`${match.marketA.question}`); console.log(` ↔ ${match.marketB.question}`); console.log(` Similarity: ${(match.similarity * 100).toFixed(0)}%`); } // Get all links const links = await finder.getLinks();
Execute Opportunity
typescript// Execute an opportunity const result = await finder.execute(opportunityId, { size: 100, // $100 position maxSlippage: 0.5, // 0.5% max slippage useProtectedOrders: true, }); console.log(`Executed: ${result.status}`); console.log(` Filled: $${result.filledSize}`); console.log(` Avg price: ${result.avgPrice}`); console.log(` Fees: $${result.fees}`); // Mark as taken manually await finder.markTaken(opportunityId); // Record outcome await finder.recordOutcome(opportunityId, { pnl: 25.50, exitPrice: 0.55, exitTimestamp: Date.now(), });
Analytics
typescript// Get statistics const stats = await finder.getAnalytics({ period: '30d', }); console.log(`Total opportunities: ${stats.total}`); console.log(`Taken: ${stats.taken}`); console.log(`Win rate: ${(stats.winRate * 100).toFixed(1)}%`); console.log(`Total P&L: $${stats.totalPnl.toLocaleString()}`); console.log(`Avg edge: ${stats.avgEdge.toFixed(2)}%`); console.log(`By platform pair:`); for (const [pair, data] of Object.entries(stats.byPlatformPair)) { console.log(` ${pair}: ${data.count} opps, $${data.pnl} P&L`); }
Risk Modeling
typescript// Model execution risk const risk = await finder.modelRisk(opportunityId); console.log(`Execution risk:`); console.log(` Fill probability: ${(risk.fillProbability * 100).toFixed(0)}%`); console.log(` Expected slippage: ${risk.expectedSlippage.toFixed(2)}%`); console.log(` Time to fill: ${risk.estimatedTimeToFill}s`); console.log(` Counterparty risk: ${risk.counterpartyRisk}`); // Estimate execution const estimate = await finder.estimateExecution(opportunityId, { size: 500, }); console.log(`Execution estimate for $500:`); console.log(` Expected fill: $${estimate.expectedFill}`); console.log(` Expected cost: $${estimate.expectedCost}`); console.log(` Net edge after costs: ${estimate.netEdge.toFixed(2)}%`);
Opportunity Scoring
Opportunities are scored 0-100 based on:
| Factor | Weight | Description |
|---|---|---|
| Edge % | 35% | Raw arbitrage spread |
| Liquidity | 25% | Available volume |
| Confidence | 25% | Match quality |
| Execution | 15% | Platform reliability |
Penalties
- Low liquidity (<$1000): -5 points
- Cross-platform complexity: -3 per platform
- High slippage (>2%): -5 points
- Low confidence (<70%): -5 points
- Near expiry (<24h): -3 points
Semantic Matching
Markets are matched using:
- Exact slug match - Platform-specific IDs
- Text similarity - Jaccard coefficient
- Vector embeddings - Semantic similarity
- Manual links - User-defined
typescript// Configure matching finder.setMatchingConfig({ minTextSimilarity: 0.8, minEmbeddingSimilarity: 0.85, useManualLinksFirst: true, });
Best Practices
- Start with high-confidence matches - 85%+ similarity
- Check liquidity - Ensure enough volume to execute
- Account for fees - Factor in platform fees
- Use protected orders - Avoid slippage
- Monitor in real-time - Opportunities disappear fast
- Track outcomes - Build performance history


