# AI-Trader Roadmap This document outlines planned features and improvements for the AI-Trader project. ## Release Planning ### v0.4.0 - Enhanced Simulation Management (Planned) **Focus:** Improved simulation control, resume capabilities, and performance analysis #### Simulation Resume & Continuation - **Resume from Last Completed Date** - API to continue simulations without re-running completed dates - `POST /simulate/resume` - Resume last incomplete job or start from last completed date - `POST /simulate/continue` - Extend existing simulation with new date range - Query parameters to specify which model(s) to continue - Automatic detection of last completed date per model - Validation to prevent overlapping simulations - Support for extending date ranges forward in time - Use cases: - Daily simulation updates (add today's date to existing run) - Recovering from failed jobs (resume from interruption point) - Incremental backtesting (extend historical analysis) #### Position History & Analysis - **Position History Tracking** - Track position changes over time - Query endpoint: `GET /positions/history?model=&start_date=&end_date=` - Timeline view of all trades and position changes - Calculate holding periods and turnover rates - Support for position snapshots at specific dates #### Performance Metrics - **Advanced Performance Analytics** - Calculate standard trading metrics - Sharpe ratio, Sortino ratio, maximum drawdown - Win rate, average win/loss, profit factor - Volatility and beta calculations - Risk-adjusted returns - Comparison across models #### Data Management - **Price Data Management API** - Endpoints for price data operations - `GET /data/coverage` - Check date ranges available per symbol - `POST /data/download` - Trigger manual price data downloads - `GET /data/status` - Check download progress and rate limits - `DELETE /data/range` - Remove price data for specific date ranges ### v0.5.0 - Real-Time Trading Support (Planned) **Focus:** Live market data integration and real-time decision making #### Real-Time Market Data - **Live Price Feeds** - Integration with real-time market data providers - WebSocket connections for streaming prices - Support for multiple data providers (Alpha Vantage, IEX Cloud, Polygon.io) - Fallback mechanisms for data provider failures - Rate limiting and connection management #### Live Trading Mode - **Real-Time Simulation** - Run AI agents with live market data - Separate mode from historical backtesting - Configurable update intervals (1min, 5min, 15min, 1hour) - Paper trading support (simulated execution) - Real broker integration (planned for later) #### Scheduling & Automation - **Scheduled Simulations** - Cron-like scheduling for automated runs - Daily market close simulations - Intraday update schedules - Configurable time zones and trading hours - Integration with external schedulers (Airflow, Prefect, n8n) ### v0.6.0 - Multi-Strategy & Portfolio Management (Planned) **Focus:** Strategy composition and portfolio-level optimization #### Strategy Composition - **Multi-Strategy Models** - Support for combining multiple AI strategies - Portfolio allocation across different AI models - Risk parity and factor-based allocation - Dynamic rebalancing based on performance - Strategy correlation analysis #### Risk Management - **Advanced Risk Controls** - Position limits and risk constraints - Maximum position size per symbol - Sector exposure limits - Portfolio-level stop losses - Volatility-based position sizing #### Model Ensembles - **Ensemble Methods** - Combine predictions from multiple models - Voting mechanisms (majority, weighted, rank-based) - Confidence-weighted predictions - Model performance tracking for weight adjustment ### v0.7.0 - Alternative Data & Advanced Features (Planned) **Focus:** Enhanced data sources and sophisticated analysis #### Alternative Data Sources - **News & Sentiment Analysis** - Integrate news and social media data - News API integration (NewsAPI, Benzinga, Bloomberg) - Sentiment scoring for individual stocks - Event detection (earnings, M&A, regulatory) - Social media sentiment (Reddit, Twitter/X) #### Market Regime Detection - **Adaptive Strategies** - Detect market conditions and adapt - Bull/bear/sideways market classification - Volatility regime detection - Sector rotation analysis - Economic indicator integration (GDP, unemployment, inflation) #### Custom Indicators - **User-Defined Indicators** - Plugin system for custom technical indicators - Python API for indicator development - Automatic caching and calculation - Vectorized computation support - Backtesting with custom indicators ## Future Enhancements ### Infrastructure & DevOps - **Kubernetes Deployment** - Production-ready orchestration - Helm charts for easy deployment - Horizontal scaling for parallel simulations - Service mesh integration (Istio, Linkerd) - Observability stack (Prometheus, Grafana, Jaeger) - **Cloud Provider Support** - Managed deployments - AWS (ECS, EKS, Lambda) - Google Cloud (Cloud Run, GKE) - Azure (AKS, Container Instances) - Terraform modules for infrastructure as code ### Data & Storage - **Alternative Databases** - Support for different storage backends - PostgreSQL for production workloads - TimescaleDB for time-series optimization - Redis for caching and real-time data - Object storage (S3, GCS, Azure Blob) for large datasets - **Data Pipeline** - Robust data ingestion and processing - Apache Airflow for workflow orchestration - Delta Lake for data versioning - Data quality checks and validation - Automated data backups and recovery ### Web UI & Visualization - **Dashboard Interface** - Web-based monitoring and control - React/Vue.js frontend - Real-time charts and graphs (Plotly, D3.js) - Job management and configuration - Performance comparison visualizations - Portfolio allocation charts - **Jupyter Integration** - Notebook-based analysis - Pre-built analysis notebooks - Interactive strategy development - Backtest result exploration - Custom metric calculation ### AI & ML Enhancements - **Model Training & Evaluation** - Train custom AI models - Training data preparation from historical results - Hyperparameter optimization (Optuna, Ray Tune) - Cross-validation and backtesting - Model versioning and registry (MLflow) - **Reinforcement Learning** - RL-based trading agents - Gym/Gymnasium environment for trading - PPO, SAC, TD3 agent implementations - Reward shaping and curriculum learning - Multi-agent competitive scenarios ### Integration & Extensibility - **Webhook Support** - Event-driven notifications - Job completion notifications - Trade execution alerts - Error and failure notifications - Custom webhook endpoints - **Plugin System** - Extensible architecture - Custom data sources - Alternative AI models (local LLMs, custom APIs) - Trading signal generators - Risk management rules ### Testing & Quality - **Performance Testing** - Load and stress testing - Locust/JMeter test scenarios - Database performance benchmarks - API latency measurements - Scalability testing - **Chaos Engineering** - Resilience testing - Network failure simulations - Database connection failures - API provider outages - Recovery time measurements ## Contributing We welcome contributions to any of these planned features! Please see [CONTRIBUTING.md](CONTRIBUTING.md) for guidelines. To propose a new feature: 1. Open an issue with the `feature-request` label 2. Describe the use case and expected behavior 3. Discuss implementation approach with maintainers 4. Submit a PR with tests and documentation ## Version History - **v0.1.0** - Initial release with batch execution - **v0.2.0** - Docker deployment support - **v0.3.0** - REST API, on-demand downloads, database storage (current) - **v0.4.0** - Enhanced simulation management (planned) - **v0.5.0** - Real-time trading support (planned) - **v0.6.0** - Multi-strategy & portfolio management (planned) - **v0.7.0** - Alternative data & advanced features (planned) --- Last updated: 2025-10-31