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