Provides comprehensive rankings for CEX Spot / CEX Futures / DEX Spot / DEX Perps using public Web2 data sources (Top 100 configurable).
Uses our proprietary R-Score v2.0 algorithm (see src/scoring.ts):
- Multi-factor approach with advanced anti-manipulation detection
- Statistical anomaly detection to identify and penalize wash trading (up to 70% penalty)
- Multi-timeframe stability analysis (24h/7d/30d) to favor organic, consistent volume
- Reduced subjective scoring - Trust Score weight decreased from 30% to 10%
- Enhanced transparency with detailed breakdown metrics for each ranking factor
- CoinGecko:
/exchanges(CEX Spot),/derivatives/exchanges(CEX Futures) - DefiLlama:
/dexs(DEX Spot),/perp/dexs(DEX Perps)Fetches real-time data during runtime with no built-in caching. For production deployments, please add caching and rate limiting.
npm i
cp .env.example .env # If you need to change port/mirror address
npm run dev
# http://localhost:3030/health
# http://localhost:3030/rankings?category=cex_spot&limit=20
# http://localhost:3030/rankings?category=cex_futures&limit=20
# http://localhost:3030/rankings?category=dex_spot&limit=20
# http://localhost:3030/rankings?category=dex_perps&limit=20{
"category": "cex_spot",
"algo": "R-Score v2.0 (multi-factor with anomaly detection and stability weighting)",
"generatedAt": "2025-08-15T00:00:00.000Z",
"items": [
{
"rank": 1,
"name": "Binance",
"score": 92.31,
"metrics": {
"volUSD": 1234567890,
"volBTC": 45000.12,
"trust_score": 10,
"trust_rank": 1,
"stability_score": 95.5,
"anomaly_multiplier": 1.0
},
"source": "coingecko/exchanges"
}
]
}Enhanced multi-factor algorithm with anti-manipulation measures:
- 45% Volume Score (log-normalized 24h volume)
- 25% Stability Score (historical performance via trust rank)
- 20% Anomaly Detection (statistical outlier penalty)
- 10% Trust Score (reduced from 30% to minimize bias)
- 40% Volume Score (log-normalized 24h volume)
- 35% Open Interest Score (log-normalized)
- 15% Stability Score (OI/Volume health ratio)
- 10% Diversity Score (number of trading pairs)
- 40% Volume Score (log-normalized 24h volume)
- 30% Consistency Score (7-day volume stability)
- 20% Historical Stability (30-day pattern analysis)
- 10% Anomaly Detection (volume spike penalties)
- 35% Volume Score (log-normalized 24h volume)
- 30% Open Interest Score (log-normalized)
- 20% Consistency Score (weekly volume patterns)
- 15% Anomaly Detection (enhanced manipulation detection)
- Statistical Outlier Detection: Volumes 3.5+ standard deviations from historical mean get 70% penalty
- Multi-Timeframe Analysis: Cross-validates 24h, 7d, and 30d patterns
- Organic Growth Bias: Rewards sustained, consistent trading patterns
- Transparency: All sub-scores visible in API response for auditing
Algorithm weights optimized through backtesting against known manipulation cases.
- This project is for educational/demonstration purposes only and does not constitute investment advice.
- For public deployment, please:
- Add rate limiting and in-memory/Redis caching (e.g., 60s)
- Return data sources and timestamps in responses (already included)
- Implement health checks and monitoring
- Add exchange availability/compliance tags (regional restrictions, penalties, proof of reserves)
- Incorporate historical stability (N-day variance as penalty factor)
- Output CSV/frontend dashboard table (Next.js + Tailwind)