A robust AI-driven trading system relies on diverse and high-quality data. In the world of financial markets, data primarily falls into two categories:
Market Data:
- Price Quotes: Real-time bid, ask, and last-trade prices.
- Order Book Data: Level II or depth-of-market data showing the quantity of buy and sell orders at various price levels.
- Historical Time Series: Daily, hourly, minute, or tick-level data for backtesting and analysis.
Alternative Data:
- News and Social Media: Articles, tweets, blog posts, or any textual source that could influence market sentiment.
- Macroeconomic Indicators: GDP, unemployment rates, inflation figures, etc.
- Web Scraped Data: For instance, e-commerce product pricing or shipping data that might hint at economic trends.
- Sensor Data: Weather data for commodities, satellite imagery for shipping or agriculture, etc.
Major providers offer real-time feeds that can be accessed via APIs or specialized data terminals. When building an AI-driven…
