Day Trading Agents provides a comprehensive suite of AI-powered modules that automate the entire day trading workflow. The platform continuously ingests tick-level market data and applies machine learning models to identify entry and exit points. It features backtesting utilities that simulate performance over historical timeframes, risk management engines for dynamic position sizing and drawdown control, and live execution adapters that connect to brokerage APIs such as Interactive Brokers and Alpaca. Custom strategy components can be written in Python, allowing traders to incorporate technical, fundamental, or sentiment-based indicators. With a modular architecture, users can mix and match data preprocessors, predictive models, and execution strategies to fine-tune performance and minimize latency. The system also logs detailed trade metrics for performance analysis and iterative improvement.

Investidor IA harnesses Python libraries like Pandas and Yahoo Finance to fetch and preprocess stock market data, while leveraging OpenAI’s GPT models to interpret complex financial metrics and generate actionable insights. It performs fundamental analysis—examining P/E ratios, revenue growth, and dividend yield—and technical analysis using moving averages and RSI. The agent also scrapes and analyzes news headlines for sentiment trends to gauge market mood. With a CLI interface, users define watchlists and risk preferences, receive CSV reports and visual plots, and get natural language summaries of portfolio health. Scheduled tasks automate daily updates and alerts via email or messaging. Its modular architecture allows integration with brokerage APIs for automated order execution, enhancing both research and trading workflows.