# 📊 Stock Market Intelligence API
> 🚀 **Transform your applications with AI-powered stock market analysis and real-time financial intelligence**
Welcome to RL-MCP's comprehensive stock market API! Our platform combines cutting-edge vector search, real-time market data, sentiment analysis, and intelligent caching to deliver unparalleled financial intelligence capabilities. 📈✨
## 🌟 What Makes Our Stock API Special?
### 🧠 **AI-Powered Intelligence**
- **🔍 Vector Search**: Semantic search across news, analysis, and market data
- **📊 Sentiment Analysis**: Real-time sentiment scoring for news and market data
- **🤖 Smart Analysis**: AI-driven stock analysis with confidence scoring
- **🎯 Relevance Scoring**: Intelligent content ranking and filtering
### ⚡ **High-Performance Architecture**
- **🚀 Intelligent Caching**: Multi-layer caching for lightning-fast responses
- **📡 Real-time Data**: Live market data with minimal latency
- **🔄 Background Processing**: Async data ingestion and processing
- **📈 Scalable Design**: Built to handle high-volume trading applications
### 🛡️ **Enterprise-Ready**
- **🔐 Secure Authentication**: Token-based API security
- **📊 Performance Monitoring**: Built-in health checks and cache statistics
- **🗄️ Robust Storage**: PostgreSQL with optimized indexing
- **🐳 Container Ready**: Full Docker support for easy deployment
## 🎯 Core Capabilities
### 1. 🔍 **Vector Search & Semantic Analysis**
```bash
POST /v1/stock/search
```
- **Semantic Search**: Find relevant content using natural language queries
- **Multi-Source Search**: Search across news, analysis, and market data
- **Smart Filtering**: Filter by symbols, dates, content types, and similarity thresholds
- **Ranked Results**: AI-powered relevance and similarity scoring
**Example Query**: *"What are analysts saying about Tesla's battery technology?"*
### 2. 💹 **Real-Time Market Data**
```bash
GET /v1/stock/price/{symbol}
```
- **Live Pricing**: Current stock prices with change indicators
- **Market Metrics**: Volume, market cap, P/E ratios, and more
- **Historical Context**: Price changes and percentage movements
- **Multi-Symbol Support**: Batch processing for portfolio analysis
### 3. 📰 **News Intelligence & Sentiment**
```bash
GET /v1/stock/news
```
- **Real-Time News**: Latest financial news with sentiment analysis
- **Smart Filtering**: Filter by symbols, sources, and relevance
- **Sentiment Scoring**: AI-powered sentiment analysis (-1 to 1 scale)
- **Source Diversity**: Aggregated from multiple trusted financial sources
### 4. 🧠 **AI-Powered Stock Analysis**
```bash
GET /v1/stock/analysis/{symbol}
```
- **Comprehensive Analysis**: Technical, fundamental, and news-based insights
- **Confidence Scoring**: AI confidence levels for each analysis
- **Actionable Recommendations**: Buy/Hold/Sell recommendations with reasoning
- **Risk Assessment**: Intelligent risk level categorization
### 5. 🌍 **Market Overview & Trends**
```bash
GET /v1/stock/market/summary
```
- **Market Summary**: Daily market overview with key metrics
- **Top Movers**: Gainers and losers with performance data
- **Trending Analysis**: Most active and discussed stocks
- **Sentiment Overview**: Overall market sentiment indicators
## 🚀 Quick Start Examples
### 🔍 **Semantic Search Example**
```python
import requests
# Search for Tesla battery technology insights
search_query = {
"query": "Tesla battery technology innovations",
"symbols": ["TSLA"],
"include_news": True,
"include_analysis": True,
"similarity_threshold": 0.8,
"limit": 10
}
response = requests.post(
"http://localhost:8000/v1/stock/search",
json=search_query,
headers={"Authorization": "Bearer YOUR_TOKEN"}
)
results = response.json()
for result in results:
print(f"📊 {result['content_type']}: {result['similarity_score']:.2f}")
print(f"📝 {result['content'][:100]}...")
```
### 💹 **Market Analysis Example**
```python
# Get comprehensive market overview
market_summary = requests.get(
"http://localhost:8000/v1/stock/market/summary",
headers={"Authorization": "Bearer YOUR_TOKEN"}
).json()
print(f"📈 Market Sentiment: {market_summary['market_sentiment']:.2f}")
print(f"🔥 Top Gainer: {market_summary['top_gainers'][0]['symbol']}")
print(f"📉 Top Loser: {market_summary['top_losers'][0]['symbol']}")
```
### 📰 **News Intelligence Example**
```python
# Get latest news with sentiment for Apple
news = requests.get(
"http://localhost:8000/v1/stock/news?symbol=AAPL&limit=5",
headers={"Authorization": "Bearer YOUR_TOKEN"}
).json()
for article in news:
sentiment = "🟢" if article['sentiment_score'] > 0 else "🔴"
print(f"{sentiment} {article['title']}")
print(f"📊 Sentiment: {article['sentiment_score']:.2f}")
```
## 🎯 Use Cases & Applications
### 🤖 **AI Trading Assistants**
- **Portfolio Analysis**: Semantic search across holdings for insights
- **Risk Assessment**: AI-powered risk analysis and recommendations
- **Market Intelligence**: Real-time sentiment and trend analysis
- **Decision Support**: Data-driven buy/sell/hold recommendations
### 📊 **Financial Research Platforms**
- **Research Automation**: Automated collection and analysis of market data
- **Sentiment Tracking**: Track sentiment changes over time
- **Competitive Analysis**: Compare companies and sectors
- **Trend Identification**: Identify emerging market trends
### 📱 **Investment Apps & Tools**
- **Smart Notifications**: Alert users to relevant market changes
- **Personalized Insights**: Tailored analysis based on user portfolios
- **Educational Content**: Explain market movements and trends
- **Social Trading**: Share and discover investment insights
### 🏢 **Enterprise Financial Systems**
- **Risk Management**: Real-time risk assessment and monitoring
- **Compliance Monitoring**: Track regulatory and market changes
- **Client Reporting**: Automated insight generation for clients
- **Market Research**: Comprehensive market intelligence gathering
## 📈 Performance & Scalability
### ⚡ **Caching Strategy**
- **Multi-Layer Caching**: Memory, database, and application-level caching
- **Smart Invalidation**: Intelligent cache refresh based on data freshness
- **Performance Monitoring**: Real-time cache hit rates and performance metrics
- **Configurable TTL**: Customizable cache expiration policies
### 🔄 **Background Processing**
- **Async Data Ingestion**: Non-blocking news and data collection
- **Batch Processing**: Efficient handling of large data volumes
- **Queue Management**: Intelligent task prioritization and scheduling
- **Error Handling**: Robust error recovery and retry mechanisms
### 📊 **Monitoring & Analytics**
```bash
GET /v1/stock/cache/stats # Cache performance metrics
GET /v1/stock/health # System health and status
```
## 🛠️ **Integration Guide**
### 🔑 **Authentication**
All endpoints require Bearer token authentication:
```bash
curl -H "Authorization: Bearer YOUR_TOKEN" \
http://localhost:8000/v1/stock/price/AAPL
```
### 📝 **Response Formats**
All responses follow consistent JSON schemas with:
- **Standardized Fields**: Consistent naming and data types
- **Rich Metadata**: Timestamps, confidence scores, and source information
- **Error Handling**: Detailed error messages and status codes
- **Pagination Support**: Efficient handling of large result sets
### 🔄 **Rate Limiting & Best Practices**
- **Batch Requests**: Use batch endpoints for multiple symbols
- **Caching**: Leverage built-in caching for frequently accessed data
- **Filtering**: Use specific filters to reduce response sizes
- **Background Tasks**: Use async endpoints for heavy operations
## 🎉 **What's Next?**
Ready to dive deeper? Explore our detailed guides:
- 🔍 **[Vector Search Guide](vector-search.md)** - Master semantic search capabilities
- 📰 **[News & Analysis](news-analysis.md)** - Leverage market intelligence
- 💹 **[Market Data](market-data.md)** - Real-time pricing and metrics
- ⚡ **[Performance Guide](performance.md)** - Optimization strategies
- 🔗 **[API Reference](api-reference.md)** - Complete endpoint documentation
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**🚀 Ready to revolutionize your financial applications?**
*Our stock market API combines the power of AI, real-time data, and intelligent caching to deliver unparalleled financial intelligence. Start building the future of fintech today!* 📈✨
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