vibe-trading - Finance research, backtesting, and market analysis toolkit
Provides finance research tools for market data, strategy backtesting, factor analysis, options pricing, trade journals, shadow accounts, and multi-agent research.
Tags
Updated: 2026-10-04What this skill does
- List finance skills
- Load skill documentation
- Create research goals
- Attach goal evidence
- Run strategy backtests
- Analyze quantitative factors
- Price options
- Detect chart patterns
- Fetch market data
- Analyze trade journals
- Extract shadow strategies
- Run shadow backtests
- Render shadow reports
- Scan shadow signals
- Run agent swarms
- Benchmark quantitative alphas
- Search financial information
- Read financial documents
- Write strategy files
- Read strategy files
Inputs
- Market symbols
- Historical market data
- Strategy configurations
- Strategy code
- Broker CSV exports
- Research queries
- Financial documents
- Research goal data
- Market data provider credentials
Outputs
- Backtest metrics
- Factor analysis results
- Options prices and Greeks
- Market data results
- Financial research results
- Trade behavior diagnostics
- Shadow strategy rules
- Shadow backtest results
- HTML or PDF reports
- Matching shadow signals
- Written configuration files
- Written strategy files
- Research goal updates
Requirements
- Python 3.11 or later
- vibe-trading-ai package
- MCP server runtime
- IBKR TWS or IB Gateway for IBKR tools
- OPENAI-compatible API key for run_swarm
- LLM model name for run_swarm