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analytics
Performance attribution, trade analytics, and strategy optimization
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Performance attribution, trade analytics, and strategy optimization
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
| name | analytics |
| description | Performance attribution, trade analytics, and strategy optimization |
| emoji | 📊 |
Analyze trading performance with attribution by edge source, time-of-day analysis, and optimization insights.
/analytics Performance summary
/analytics today Today's performance
/analytics week Weekly breakdown
/analytics month Monthly breakdown
/analytics attribution P&L by edge source
/analytics by-platform P&L by platform
/analytics by-category P&L by market category
/analytics by-strategy P&L by strategy
/analytics best-times Best trading hours
/analytics by-hour Hourly performance
/analytics by-day Day of week analysis
/analytics edge-decay How edge decays over time
/analytics edge-buckets Performance by edge size
/analytics liquidity Performance by liquidity
import { createAnalyticsService } from 'clodds/analytics';
const analytics = createAnalyticsService({
// Data source
tradesDb: './trades.db',
// Time zone
timezone: 'America/New_York',
});
const summary = await analytics.getSummary({
period: 'month',
// or: from: '2024-01-01', to: '2024-01-31'
});
console.log('=== Performance ===');
console.log(`Total P&L: $${summary.totalPnl}`);
console.log(`Win Rate: ${summary.winRate}%`);
console.log(`Profit Factor: ${summary.profitFactor}`);
console.log(`Sharpe Ratio: ${summary.sharpeRatio}`);
console.log(`Total Trades: ${summary.totalTrades}`);
console.log(`Avg Trade: $${summary.avgTrade}`);
console.log(`Best Trade: $${summary.bestTrade}`);
console.log(`Worst Trade: $${summary.worstTrade}`);
const attribution = await analytics.getAttribution('edgeSource');
for (const source of attribution) {
console.log(`${source.name}:`);
console.log(` P&L: $${source.pnl}`);
console.log(` Trades: ${source.trades}`);
console.log(` Win Rate: ${source.winRate}%`);
console.log(` Contribution: ${source.contribution}%`);
}
// Example sources:
// - price_lag (stale prices)
// - liquidity_gap (thin orderbooks)
// - information (news/events)
// - model_edge (external models)
// - combinatorial (arbitrage)
const hourly = await analytics.getHourlyPerformance();
console.log('Best Hours:');
for (const hour of hourly.slice(0, 3)) {
console.log(` ${hour.hour}:00 - Win: ${hour.winRate}%, Avg: $${hour.avgPnl}`);
}
console.log('Worst Hours:');
for (const hour of hourly.slice(-3)) {
console.log(` ${hour.hour}:00 - Win: ${hour.winRate}%, Avg: $${hour.avgPnl}`);
}
const daily = await analytics.getDayOfWeekPerformance();
for (const day of daily) {
console.log(`${day.name}: $${day.pnl} (${day.trades} trades, ${day.winRate}% win)`);
}
const decay = await analytics.getEdgeDecay();
console.log('Edge Decay (how fast edge disappears):');
for (const bucket of decay) {
console.log(` ${bucket.holdTime}: ${bucket.avgReturn}% return`);
}
// Shows optimal hold time before edge decays
const edgeBuckets = await analytics.getEdgeBuckets();
for (const bucket of edgeBuckets) {
console.log(`Edge ${bucket.min}-${bucket.max}%:`);
console.log(` Trades: ${bucket.trades}`);
console.log(` Win Rate: ${bucket.winRate}%`);
console.log(` Avg P&L: $${bucket.avgPnl}`);
console.log(` Realized Edge: ${bucket.realizedEdge}%`);
}
const liquidity = await analytics.getLiquidityAnalysis();
for (const bucket of liquidity) {
console.log(`${bucket.name} liquidity:`);
console.log(` Trades: ${bucket.trades}`);
console.log(` Avg Slippage: ${bucket.avgSlippage}%`);
console.log(` Fill Rate: ${bucket.fillRate}%`);
console.log(` Avg P&L: $${bucket.avgPnl}`);
}
const execution = await analytics.getExecutionQuality();
console.log('=== Execution Quality ===');
console.log(`Avg Slippage: ${execution.avgSlippage}%`);
console.log(`Fill Rate: ${execution.fillRate}%`);
console.log(`Avg Fill Time: ${execution.avgFillTimeMs}ms`);
console.log(`Partial Fills: ${execution.partialFillRate}%`);
console.log(`Rejected Orders: ${execution.rejectionRate}%`);
const platforms = await analytics.getPlatformComparison();
for (const platform of platforms) {
console.log(`${platform.name}:`);
console.log(` P&L: $${platform.pnl}`);
console.log(` Win Rate: ${platform.winRate}%`);
console.log(` Avg Slippage: ${platform.avgSlippage}%`);
console.log(` Best For: ${platform.strengths.join(', ')}`);
}
// Generate PDF report
await analytics.exportReport({
format: 'pdf',
period: 'month',
include: ['summary', 'attribution', 'charts'],
outputPath: './reports/january-2024.pdf',
});
// Export raw data
await analytics.exportData({
format: 'csv',
period: 'month',
outputPath: './data/january-trades.csv',
});
| Category | Description |
|---|---|
| Edge Source | Where the edge came from |
| Platform | Which platform traded on |
| Category | Market category (politics, crypto) |
| Strategy | Which strategy generated trade |
| Time | Hour/day of trade |
| Size | Trade size bucket |
| Metric | Good Value | Description |
|---|---|---|
| Win Rate | > 50% | Percent of winning trades |
| Profit Factor | > 1.5 | Gross profit / gross loss |
| Sharpe Ratio | > 1.0 | Risk-adjusted returns |
| Realized Edge | > 0 | Actual vs expected edge |
| Fill Rate | > 95% | Orders fully filled |
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