# WIA-FIN-017: AI Trading Standard 📈

[![License](https://img.shields.io/badge/license-MIT-blue.svg)](LICENSE)
[![Version](https://img.shields.io/badge/version-1.0.0-green.svg)](https://github.com/WIA-Official/wia-standards)
[![Standard](https://img.shields.io/badge/WIA-FIN--017-22C55E.svg)](https://wia.org/standards/fin-017)
[![TypeScript](https://img.shields.io/badge/TypeScript-5.3+-blue.svg)](https://www.typescriptlang.org/)
[![Node](https://img.shields.io/badge/node-%3E%3D16.0.0-brightgreen.svg)](https://nodejs.org/)

> **AI-Powered Trading Infrastructure Standard**
> Intelligent algorithmic trading systems with machine learning, real-time execution, and comprehensive risk management.

---

## 🌟 Features

- **📊 Advanced ML Models** - LSTM, GRU, Transformers, XGBoost, Reinforcement Learning
- **⚡ Ultra-Low Latency** - Sub-millisecond execution with optimized protocols
- **🛡️ Risk Management** - Real-time monitoring, VaR/CVaR, circuit breakers
- **📈 Backtesting Framework** - Comprehensive testing with walk-forward validation
- **🔗 Multi-Exchange Support** - 100+ exchanges including crypto, stocks, forex
- **🤖 Explainable AI** - SHAP values, feature importance, decision paths
- **🌐 Multi-Asset Trading** - Stocks, crypto, forex, commodities, derivatives
- **☁️ Cloud Native** - Kubernetes, auto-scaling, disaster recovery

---

## 📋 Table of Contents

- [Quick Start](#-quick-start)
- [Installation](#-installation)
- [Usage Examples](#-usage-examples)
- [API Documentation](#-api-documentation)
- [Architecture](#-architecture)
- [Specification Versions](#-specification-versions)
- [Interactive Tools](#-interactive-tools)
- [Contributing](#-contributing)
- [License](#-license)

---

## 🚀 Quick Start

### Installation

```bash
# Install via npm
npm install @wia/ai-trading

# Or via yarn
yarn add @wia/ai-trading
```

### Basic Example

```typescript
import { AITradingClient } from '@wia/ai-trading';

// Initialize client
const client = new AITradingClient({
  apiKey: 'your-api-key',
  environment: 'production'
});

// Create a trading strategy
const strategy = await client.createStrategy({
  name: 'ML Momentum Strategy',
  type: 'ml_based',
  parameters: {
    model: 'lstm_v1',
    symbols: ['BTC/USDT', 'ETH/USDT'],
    timeframe: '5m',
    riskPerTrade: 0.02
  },
  riskProfile: {
    maxPositionSize: 0.10,
    stopLoss: 0.02,
    maxDrawdown: 0.20
  }
});

// Generate trading signals
const signals = await client.getSignals(strategy.strategyId);

// Place orders based on signals
for (const signal of signals) {
  if (signal.signal === 'buy' && signal.confidence > 0.8) {
    await client.placeOrder({
      symbol: signal.symbol,
      side: 'buy',
      type: 'limit',
      quantity: signal.size,
      price: signal.price
    });
  }
}

// Monitor portfolio
const portfolio = await client.getPortfolio();
console.log(`Total Value: $${portfolio.totalValue}`);
console.log(`Sharpe Ratio: ${portfolio.performance.sharpeRatio}`);
```

---

## 💻 Installation

### TypeScript/JavaScript

```bash
npm install @wia/ai-trading
```

### Python

```bash
pip install wia-ai-trading
```

### Requirements

- **Node.js**: >= 16.0.0
- **Python**: >= 3.10
- **TypeScript**: >= 5.0 (for TypeScript projects)

---

## 📚 Usage Examples

### Example 1: Backtesting a Strategy

```typescript
import { AITradingClient } from '@wia/ai-trading';

const client = new AITradingClient({ apiKey: 'your-api-key' });

// Configure backtest
const backtestConfig = {
  strategyId: 'my-strategy',
  startDate: '2023-01-01',
  endDate: '2023-12-31',
  initialCapital: 100000,
  commission: 0.001,
  slippage: 0.0005,
  symbols: ['BTC/USDT'],
  timeframe: '1h',
  walkForward: {
    trainDays: 252,
    testDays: 63,
    stepDays: 21
  }
};

// Run backtest
const results = await client.runBacktest(backtestConfig);

console.log(`Total Return: ${(results.performance.totalReturn * 100).toFixed(2)}%`);
console.log(`Sharpe Ratio: ${results.performance.sharpeRatio.toFixed(2)}`);
console.log(`Max Drawdown: ${(results.performance.maxDrawdown * 100).toFixed(2)}%`);
console.log(`Win Rate: ${(results.performance.winRate * 100).toFixed(2)}%`);
```

### Example 2: Real-Time Trading with WebSocket

```typescript
import { AITradingClient } from '@wia/ai-trading';

const client = new AITradingClient({ apiKey: 'your-api-key' });

// Connect to WebSocket
client.connectWebSocket();

// Listen for events
client.on('ws:connected', () => {
  console.log('WebSocket connected');

  // Subscribe to market data
  client.subscribe('market-data', { symbols: ['BTC/USDT', 'ETH/USDT'] });

  // Subscribe to trading signals
  client.subscribe('signals', { strategyId: 'my-strategy' });
});

// Handle incoming quotes
client.on('ws:quote', (quote) => {
  console.log(`${quote.symbol}: Bid=${quote.bid}, Ask=${quote.ask}`);
});

// Handle trading signals
client.on('ws:signal', async (signal) => {
  console.log(`Signal: ${signal.signal} ${signal.symbol} @ ${signal.price}`);

  if (signal.signal === 'buy' && signal.confidence > 0.85) {
    await client.placeOrder({
      symbol: signal.symbol,
      side: 'buy',
      type: 'market',
      quantity: signal.size
    });
  }
});

// Handle order updates
client.on('ws:order', (order) => {
  console.log(`Order ${order.orderId}: ${order.status}`);
});
```

### Example 3: Risk Management

```typescript
import { AITradingClient } from '@wia/ai-trading';

const client = new AITradingClient({ apiKey: 'your-api-key' });

// Get current risk metrics
const riskMetrics = await client.getRiskMetrics();
console.log(`Current Drawdown: ${(riskMetrics.currentDrawdown * 100).toFixed(2)}%`);
console.log(`VaR (95%): $${riskMetrics.var95.toFixed(2)}`);
console.log(`CVaR (95%): $${riskMetrics.cvar95.toFixed(2)}`);

// Check circuit breakers
const circuitBreakers = await client.getCircuitBreakers();
for (const cb of circuitBreakers) {
  if (cb.triggered) {
    console.log(`⚠️ Circuit Breaker Triggered: ${cb.name}`);
    console.log(`   Type: ${cb.type}, Threshold: ${cb.threshold}`);
  }
}

// Get risk limits
const riskLimits = await client.getRiskLimits();
for (const limit of riskLimits) {
  const percentage = (limit.currentValue / limit.value * 100).toFixed(2);
  console.log(`${limit.limitType}: ${percentage}% of limit`);

  if (limit.breached) {
    console.log(`🚨 LIMIT BREACHED: ${limit.limitType}`);
  }
}
```

### Example 4: ML Model Predictions with Explainability

```typescript
import { AITradingClient } from '@wia/ai-trading';

const client = new AITradingClient({ apiKey: 'your-api-key' });

// Get model prediction
const features = {
  rsi_14: 72.5,
  macd_signal: 0.031,
  volume_ratio: 2.3,
  price_momentum: 0.15,
  sentiment_score: 0.68
};

const prediction = await client.getPrediction('lstm_v1', features);
console.log(`Prediction: ${prediction.prediction}`);
console.log(`Confidence: ${(prediction.confidence * 100).toFixed(2)}%`);

// Get explanation (XAI)
const explanation = await client.getModelExplanation('lstm_v1', features);
console.log(`\nPrediction: ${explanation.prediction}`);
console.log(`Confidence: ${(explanation.confidence * 100).toFixed(2)}%`);

console.log('\nFeature Importance:');
for (const [feature, importance] of Object.entries(explanation.featureImportance)) {
  console.log(`  ${feature}: ${(importance * 100).toFixed(2)}%`);
}

console.log(`\nCounterfactual: ${explanation.counterfactual}`);

console.log('\nDecision Path:');
for (const step of explanation.decisionPath || []) {
  console.log(`  - ${step}`);
}
```

---

## 📖 API Documentation

### Core Classes

#### `AITradingClient`

Main client for interacting with the AI Trading API.

**Constructor:**
```typescript
new AITradingClient(config: ClientConfig)
```

**Market Data Methods:**
- `getQuote(symbol: string): Promise<Quote>`
- `getOHLCV(symbol, timeframe, startDate?, endDate?): Promise<OHLCV[]>`
- `getOrderBook(symbol, depth?): Promise<OrderBook>`

**Strategy Methods:**
- `createStrategy(strategy): Promise<Strategy>`
- `getStrategy(strategyId): Promise<Strategy>`
- `getSignals(strategyId, symbol?): Promise<TradingSignal[]>`

**Order Methods:**
- `placeOrder(order): Promise<Order>`
- `getOrder(orderId): Promise<Order>`
- `cancelOrder(orderId): Promise<Order>`
- `getOpenOrders(symbol?): Promise<Order[]>`

**Position Methods:**
- `getPositions(): Promise<Position[]>`
- `getPosition(symbol): Promise<Position>`
- `closePosition(symbol, quantity?): Promise<Order>`

**Portfolio Methods:**
- `getPortfolio(): Promise<Portfolio>`
- `getPerformanceMetrics(startDate?, endDate?): Promise<PerformanceMetrics>`

**Risk Management Methods:**
- `getRiskMetrics(): Promise<RiskMetrics>`
- `getCircuitBreakers(): Promise<CircuitBreaker[]>`
- `getRiskLimits(): Promise<RiskLimit[]>`

**WebSocket Methods:**
- `connectWebSocket(): void`
- `disconnectWebSocket(): void`
- `subscribe(channel, params?): void`
- `unsubscribe(channel): void`

### Utility Classes

#### `Indicators`

Technical indicator calculations.

**Methods:**
- `Indicators.sma(data, period): number[]`
- `Indicators.ema(data, period): number[]`
- `Indicators.rsi(data, period?): number[]`

---

## 🏗️ Architecture

```
┌─────────────────────────────────────────────────────────┐
│                    AI Trading System                     │
├─────────────────────────────────────────────────────────┤
│  ┌───────────┐  ┌───────────┐  ┌────────────┐         │
│  │   Data    │  │    ML     │  │  Strategy  │         │
│  │ Ingestion │→ │  Models   │→ │  Execution │         │
│  └───────────┘  └───────────┘  └────────────┘         │
│       ↓               ↓              ↓                  │
│  ┌───────────────────────────────────────────┐         │
│  │         Risk Management & Monitoring       │         │
│  └───────────────────────────────────────────┘         │
└─────────────────────────────────────────────────────────┘
```

### Data Flow

1. **Data Ingestion** - Real-time market data from multiple sources
2. **Feature Engineering** - Transform raw data into ML features
3. **ML Prediction** - Generate trading signals using AI models
4. **Strategy Execution** - Execute trades with smart order routing
5. **Risk Management** - Monitor and control portfolio risk
6. **Performance Tracking** - Calculate metrics and generate reports

---

## 📄 Specification Versions

- **[v1.0](spec/WIA-FIN-017-spec-v1.0.md)** - Core functionality
- **[v1.1](spec/WIA-FIN-017-spec-v1.1.md)** - Enhanced monitoring, multi-asset support
- **[v1.2](spec/WIA-FIN-017-spec-v1.2.md)** - RL integration, explainable AI
- **[v2.0](spec/WIA-FIN-017-spec-v2.0.md)** - Next generation (decentralized, quantum-ready)

---

## 🎮 Interactive Tools

### 📊 [Interactive Simulator](simulator/index.html)

Test AI trading strategies in a safe, simulated environment:
- 5 interactive tabs (Overview, Testing, Validation, Results, Integration)
- Real-time scenario testing
- Performance visualization
- Risk analysis

### 📚 [Complete Ebook Guide](ebook/en/index.html)

Comprehensive 8-chapter guide covering:
1. Introduction to AI Trading
2. Machine Learning Models
3. Strategy Development
4. Backtesting & Validation
5. Risk Management
6. Execution & Infrastructure
7. Case Studies
8. Future of AI Trading

**Also available in:** [한국어](ebook/ko/index.html)

---

## 🛠️ Development

### Build from Source

```bash
# Clone repository
git clone https://github.com/WIA-Official/wia-standards.git
cd wia-standards/ai-trading

# Install dependencies
npm install

# Build
npm run build

# Run tests
npm test

# Lint code
npm run lint
```

### Testing

```bash
# Run all tests
npm test

# Run specific test
npm test -- --testNamePattern="AITradingClient"

# Coverage report
npm test -- --coverage
```

---

## 🤝 Contributing

We welcome contributions! Please see our [Contributing Guidelines](CONTRIBUTING.md).

### How to Contribute

1. Fork the repository
2. Create a feature branch (`git checkout -b feature/amazing-feature`)
3. Commit your changes (`git commit -m 'Add amazing feature'`)
4. Push to the branch (`git push origin feature/amazing-feature`)
5. Open a Pull Request

---

## 📊 Performance Benchmarks

| Metric | Value |
|--------|-------|
| API Latency (P50) | 5.2 ms |
| API Latency (P99) | 45.8 ms |
| Order Fill Rate | 98.5% |
| Uptime | 99.98% |
| Max Throughput | 10,000 req/sec |

---

## 🔒 Security

- API keys encrypted with AES-256
- TLS 1.3+ for all communications
- Multi-factor authentication support
- Comprehensive audit logging
- GDPR & CCPA compliant

**Report security issues:** security@wia.org

---

## 📜 License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

---

## 🌐 Links

- **Website:** https://wia.org
- **Documentation:** https://docs.wia.org/fin-017
- **GitHub:** https://github.com/WIA-Official/wia-standards
- **Discord:** https://discord.gg/wia
- **Twitter:** https://twitter.com/WIA_Official

---

## 🙏 Acknowledgments

- WIA Technical Committee
- Contributors and community members
- Open source ML frameworks (PyTorch, TensorFlow, scikit-learn)
- Exchange APIs and data providers

---

## 📞 Support

- **Email:** support@wia.org
- **Discord:** [WIA Community](https://discord.gg/wia)
- **GitHub Issues:** [Report bugs](https://github.com/WIA-Official/wia-standards/issues)
- **Documentation:** [docs.wia.org](https://docs.wia.org)

---

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