소스 정보
- 저장소
- alsk1992/CloddsBot
- 최근 소스 활동
- 2026년 2월 10일 15:14
- 감지된 SKILL.md 언어
- 영어
- 스타
- 2,972
- 포크
- 359
설치 방법
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
소스 파일 검토
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
파일 탐색기
2 개 파일SKILL.md 표시 중
SKILL.md
소스 지침 · 읽기 전용 미리보기- name
- analytics
- description
- Performance attribution, trade analytics, and strategy optimization
- emoji
- 📊
# Analytics - Complete API Reference
Analyze trading performance with attribution by edge source, time-of-day analysis, and optimization insights.
---
## Chat Commands
### Performance Overview
```
/analytics Performance summary
/analytics today Today's performance
/analytics week Weekly breakdown
/analytics month Monthly breakdown
```
### Attribution
```
/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
```
### Time Analysis
```
/analytics best-times Best trading hours
/analytics by-hour Hourly performance
/analytics by-day Day of week analysis
```
### Edge Analysis
```
/analytics edge-decay How edge decays over time
/analytics edge-buckets Performance by edge size
/analytics liquidity Performance by liquidity
```
---
## TypeScript API Reference
### Create Analytics Service
```typescript
import { createAnalyticsService } from 'clodds/analytics';
const analytics = createAnalyticsService({
// Data source
tradesDb: './trades.db',
// Time zone
timezone: 'America/New_York',
});
```
### Performance Summary
```typescript
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}`);
```
### Attribution by Edge Source
```typescript
const attribution = await analytics.getAttribution('edgeSource');
for (const source of attribution) {
console.log(`${source.name}:`);
console.log(` P&L: $${source.pnl}`);
console.log(` Trades: ${source.trades}`);
console.log(` Win Rate: ${source.winRate}%`);
console.log(` Contribution: ${source.contribution}%`);
}
// Example sources:
// - price_lag (stale prices)
// - liquidity_gap (thin orderbooks)
// - information (news/events)
// - model_edge (external models)
// - combinatorial (arbitrage)
```
### Time-of-Day Analysis
```typescript
const hourly = await analytics.getHourlyPerformance();
console.log('Best Hours:');
for (const hour of hourly.slice(0, 3)) {
console.log(` ${hour.hour}:00 - Win: ${hour.winRate}%, Avg: $${hour.avgPnl}`);
}
console.log('Worst Hours:');
for (const hour of hourly.slice(-3)) {
console.log(` ${hour.hour}:00 - Win: ${hour.winRate}%, Avg: $${hour.avgPnl}`);
}
```
### Day-of-Week Analysis
```typescript
const daily = await analytics.getDayOfWeekPerformance();
for (const day of daily) {
console.log(`${day.name}: $${day.pnl} (${day.trades} trades, ${day.winRate}% win)`);
}
```
### Edge Decay Analysis
```typescript
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
```
### Edge Size Buckets
```typescript
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: $${bucket.avgPnl}`);
console.log(` Realized Edge: ${bucket.realizedEdge}%`);
}
```
### Liquidity Analysis
```typescript
const liquidity = await analytics.getLiquidityAnalysis();
for (const bucket of liquidity) {
console.log(`${bucket.name} liquidity:`);
console.log(` Trades: ${bucket.trades}`);
console.log(` Avg Slippage: ${bucket.avgSlippage}%`);
console.log(` Fill Rate: ${bucket.fillRate}%`);
console.log(` Avg P&L: $${bucket.avgPnl}`);
}
```
### Execution Quality
```typescript
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: ${execution.rejectionRate}%`);
```
### Platform Comparison
```typescript
const platforms = await analytics.getPlatformComparison();
for (const platform of platforms) {
console.log(`${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(', ')}`);
}
```
### Export Report
```typescript
// 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',
});
```
---
## Attribution Categories
| 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 |
---
## Key Metrics
| 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 |
---
## Best Practices
1. **Review weekly** — Catch problems early
2. **Track attribution** — Know where profits come from
3. **Optimize timing** — Trade your best hours
4. **Monitor edge decay** — Don't hold too long
5. **Check execution** — Slippage kills edge
GitHub에서 보기