vibe-trading - Research markets, strategies, factors, and trading behavior
Provides finance research tools for market data, backtesting, factor analysis, options, multi-agent research, trade journals, and shadow accounts.
Tags
Updated: 2026-10-04Capabilities
Typical Inputs
Typical Outputs
What this skill does
- Run quantitative backtests
- Analyze investment factors
- Price options and Greeks
- Fetch multi-market data
- Detect chart patterns
- Search financial information
- Read financial documents
- Analyze trade journals
- Extract shadow strategies
- Render shadow reports
- Run multi-agent research
- Manage research goals
- Benchmark quantitative alphas
- Create strategy files
Inputs
- Market symbols
- Historical market data
- Strategy configurations
- Strategy source files
- Broker trade CSV files
- Research questions
- Financial URLs
- Financial documents
- Research goal evidence
Outputs
- Backtest metrics
- Factor analysis results
- Options prices and Greeks
- Market data results
- Pattern detection results
- Research findings
- Extracted document text
- Trade behavior diagnostics
- Shadow strategy rules
- HTML or PDF reports
- Research goal states
- Written configuration files
Requirements
- Python 3.11 or newer
- vibe-trading-ai package
- vibe-trading-mcp command
- API keys for selected providers
- OpenAI-compatible key for run_swarm
- LLM model name for run_swarm
- Local TWS or IB Gateway for IBKR tools