AI-Powered Analytics

Analytics & Intelligence

Performance metrics, risk analysis, and data-driven insights

What You Can Do (Logged In)

  • Calculate real-time P&L with performance attribution
  • View Sharpe ratio and maximum drawdown metrics
  • Analyze trading volume patterns and fee impact
  • Generate performance reports by strategy or time period
  • Export analytics data to CSV/JSON format
  • Compare your performance against market benchmarks
📈 Performance Analytics

How Analytics & Intelligence Works

Flow Demo
📊 Loading P&L Data from all trades...
📱 Mobile Flow

Analytics & Intelligence · 6 Steps

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How It Works

Our analytics engine processes every trade, order, and position change to generate comprehensive performance metrics. Using time-series databases and pandas/numpy processing, you get instant insights into what's working and what isn't.

P&L Calculation
Engine

Sharpe Ratio
& Drawdown

CSV/JSON
Export

H13 Analytics Machine - How It Works

Educational Purpose: This machine demonstrates how real-world crypto trading platforms aggregate data from multiple sources to provide analytics, P&L tracking, and market intelligence.

What This Machine Does

Real-World Analogy

Just like CoinGecko, TradingView, or Bloomberg Terminal aggregate crypto data, this machine:

  • 📊 Collects trading volume from all platform users
  • 💰 Tracks P&L (Profit & Loss) in real-time
  • 📈 Caches market prices to reduce API calls
  • 🔗 Communicates with other machines via APIs (no direct access)
Security Isolation

Why this matters for learning: In real trading systems, analytics engines NEVER directly access trading databases. They use APIs.

  • ✅ Reads user data via API only
  • ✅ Never modifies other machines
  • ✅ Self-contained database
  • ✅ Rate-limited endpoints

Try These API Calls (Educational)

GET /api/analytics/status
Check machine health
GET /api/analytics/trading-volume?period=24h
View last 24h volume
GET /api/analytics/pnl-summary
View profit/loss summary

Real-World vs H13 Educational Platform

FeatureReal Trading PlatformH13 Educational Platform
Data StorageEnterprise PostgreSQL/ClickHouseSQLite (self-contained)
Analytics EngineSeparate microservice with cachingAnalytics Machine (port 5006)
Update FrequencyReal-time WebSocket streams30-second polling + manual refresh
API IsolationInternal API gatewayHTTP channels with API keys
P&L TrackingRealized + Unrealized with tax implicationsEducational P&L for learning concepts

How Machines Communicate

    ┌──────────────┐     ┌──────────────┐     ┌──────────────┐
    │    Control   │────▶│   Analytics  │◀────│   Platform   │
    │   (Port 5000)│     │   (Port 5006)│     │   (Port 5003)│
    └──────────────┘     └──────────────┘     └──────────────┘
           │                    │                     │
           │                    │                     │
           ▼                    ▼                     ▼
    ┌──────────────┐     ┌──────────────┐     ┌──────────────┐
    │   Trading    │────▶│    Market    │◀────│     Order    │
    │   (Port 5001)│     │   (Port 5004)│     │   (Port 5002)│
    └──────────────┘     └──────────────┘     └──────────────┘
Each machine is self-contained. Communication via HTTP APIs ONLY.
Educational Note: In a production trading platform, analytics systems would use:
  • 📊 Time-series databases (InfluxDB, TimescaleDB) for trade history
  • 🔄 Message queues (RabbitMQ, Kafka) for real-time trade ingestion
  • 📈 Redis caching for sub-millisecond market data access
  • 🔐 JWT tokens + API Gateway for secure inter-service communication
H13 Crypto implements simplified versions of these concepts for educational clarity.

Technical Features

  • FastAPI/Express backend server
  • TimescaleDB for time-series data
  • Redis cache for real-time metrics
  • Python with pandas/numpy processing
  • Performance attribution system
  • Fee impact analyzer
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