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πŸ“ˆ Claude Finance Subagents

The definitive collection of finance-focused Claude Code subagents β€” specialized AI assistants for technical analysis, trading strategies, risk management, fundamental analysis, quantitative methods, and AI-driven market intelligence.

Subagent Count License

Installation

Option 1: Manual Installation

  1. Clone this repository
  2. Copy desired agent files to:
    • ~/.claude/agents/ for global access
    • .claude/agents/ for project-specific use
  3. Customize based on your project requirements

Option 2: Selective Install

# Install specific category
cp categories/01-technical-indicators/*.md ~/.claude/agents/

# Install specific agent
cp categories/01-technical-indicators/rsi-analyst.md ~/.claude/agents/

πŸ“š Categories

Subagents specialized in technical indicator calculation, interpretation, and strategy development.

Subagents for chart pattern recognition, support/resistance, and geometric analysis.

Subagents for position sizing, portfolio risk, and drawdown control.

Subagents for financial statement analysis, valuation, and macroeconomic assessment.

Subagents for backtesting, algorithmic trading, and quantitative strategy development.

Subagents for machine learning, deep learning, and AI-driven financial analysis.

Subagents for market data engineering, order book analysis, and alternative data.

πŸ€– Understanding Finance Subagents

Finance subagents are specialized AI assistants that enhance Claude Code's capabilities by providing deep financial domain expertise. They act as dedicated helpers for specific areas of financial analysis and trading.

What Makes Finance Subagents Special?

Domain-Specific Intelligence Each subagent is equipped with carefully crafted instructions specific to its financial domain β€” from technical indicator formulas to risk model mathematics.

Independent Context Windows Every subagent operates within its own isolated context, preventing cross-contamination between different analytical tasks.

Inter-Agent Collaboration Subagents can reference and work with each other. For example, backtesting-engineer can invoke rsi-analyst for indicator calculation within a strategy backtest.

Getting Started

> Have the rsi-analyst analyze AAPL's daily chart for divergences
> Ask the backtesting-engineer to backtest a MACD crossover strategy
> Use the reinforcement-learning-trader to optimize a trading policy

πŸ“– Subagent Structure

Each subagent follows a standardized template:

---
name: subagent-name
description: When this agent should be invoked
tools: Read, Write, Edit, Bash, Glob, Grep
model: opus
---

You are a [role description and expertise areas]...

[Agent-specific checklists, patterns, and guidelines]...

## Communication Protocol
Inter-agent communication specifications...

## Development Workflow
Structured implementation phases...

⚠️ Disclaimer

These subagents are educational tools and should not be considered financial advice. Trading and investing involve substantial risk of loss. Always do your own research and consult with qualified financial professionals before making investment decisions.

🀝 Contributing

We welcome contributions! See CONTRIBUTING.md for guidelines.

  • Submit new subagents via PR
  • Improve existing definitions
  • Report issues and bugs

πŸ“„ License

MIT License β€” see LICENSE

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A curated collection of 41+ finance-focused Claude Code subagents for technical analysis, risk management, quantitative strategies, and AI-driven market intelligence.

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