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quant-analyst · wshobson — Claude Code subagent: what it does, how to install

Builds financial models, tests trading strategies against historical data, and calculates risk metrics. Built for algorithmic trading workflows.

Install into Claude Code · Plugin marketplace All methods and platforms ↓ 
/plugin marketplace add wshobson/agents
/plugin install quantitative-trading@claude-code-workflows
Open on GitHub

What quant-analyst does

The subagent develops algorithmic trading strategies and runs backtests on historical market data. It factors in execution realities, including transaction costs and price slippage. You also get risk metric calculations such as VaR and maximum drawdown, alongside portfolio optimization via Markowitz or Black-Litterman models.

Calculations rely on pandas, numpy, and scipy. All code uses vectorized operations to keep execution fast. Research scripts remain cleanly separated from production code, while out-of-sample testing prevents strategy overfitting.

If your workflow involves options pricing, Greeks, or statistical arbitrage, install this subagent. For trivial scripts without realistic market microstructure assumptions, it is unnecessary.

What it helps with

  • Backtest trading strategies with transaction costs and slippage
  • Calculate portfolio risk metrics including VaR and maximum drawdown
  • Ingest and validate market data into a clean pipeline
  • Optimize asset allocations using Markowitz or Black-Litterman models

Example prompts for the agent

  • Backtest a pairs trading strategy in pandas with slippage and transaction costs included
  • Calculate VaR and maximum drawdown for this portfolio using historical returns
  • Optimize portfolio weights using the Black-Litterman model

How to install quant-analyst

1Plugin marketplace

/plugin marketplace add wshobson/agents
/plugin install quantitative-trading@claude-code-workflows

2Manually: put the files in place

.claude/agents/quant-analyst.md

For all projects use ~/.claude/agents/. Claude delegates by the description field or an @-mention

From the same set213

The whole set →
typescript-advanced-types Seth Hobson Guides an agent through advanced TypeScript types, from generics to conditional and mapped types. Use it for typed libraries, API clients, or strict configuration objects. Claude Code CX Codex Cursor 92,169installs tailwind-design-system Seth Hobson Helps build design systems with Tailwind CSS v4, from theme tokens to component variants. Use it when a project needs shared UI patterns. Claude Code CX Codex Cursor 70,180installs brand-landingpage Travis D. Elliott This skill interviews you about the product and its visual direction, then builds a landing page through Stitch. Use it when there’s no established design yet. Claude Code CX Codex Cursor 39,476installs python-testing-patterns Seth Hobson This skill guides Python testing with pytest, fixtures and mocks. Use it when building a test suite or tracking down failing checks. Claude Code CX Codex Cursor 36,943installs python-performance-optimization Seth Hobson This skill profiles Python code to locate CPU and memory bottlenecks. Use it when an application responds slowly or consumes too many resources. Claude Code CX Codex Cursor 35,675installs nextjs-app-router-patterns Seth Hobson This skill covers Next.js App Router patterns for rendering, routing, and data fetching. Use it when starting an App Router project or moving from Pages Router. Claude Code CX Codex Cursor 32,529installs api-design-principles Seth Hobson Use this skill to plan or review REST and GraphQL APIs. It helps when writing a specification or setting API conventions for a team. Claude Code CX Codex Cursor 30,348installs code-review-excellence Seth Hobson This skill guides pull request reviews, catches logic and security issues, and helps teams give specific feedback. Use it for review standards or developer mentoring. Claude Code CX Codex Cursor 30,193installs

Other versions of quant-analyst

quant-analyst VoltAgent Community A subagent for quantitative trading strategies, financial models, and portfolio risk analysis. Use it for backtests, derivatives pricing, and statistical arbitrage. Claude Code 1,366installs

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Questions about quant-analyst

How to install quant-analyst in Claude Code?

Run /plugin marketplace add wshobson/agents and /plugin install quantitative-trading@claude-code-workflows in Claude Code. Alternatively, add the definition file to .claude/agents/quant-analyst.md.

What does the quant-analyst subagent do?

It implements trading strategies, calculates risk metrics, and optimizes portfolios. The subagent generates vectorized Python code, backtest performance reports, and sensitivity analysis.

What Python libraries are required for quant-analyst?

The subagent writes code using pandas, numpy, and scipy. It focuses on vectorized calculations and out-of-sample validation to prevent overfitting.

Source text

quant-analyst.md · MIT 
---
name: quant-analyst
description: Build financial models, backtest trading strategies, and analyze market data. Implements risk metrics, portfolio optimization, and statistical arbitrage. Use PROACTIVELY for quantitative finance, trading algorithms, or risk analysis.
model: inherit
---

You are a quantitative analyst specializing in algorithmic trading and financial modeling.

## Focus Areas

- Trading strategy development and backtesting
- Risk metrics (VaR, Sharpe ratio, max drawdown)
- Portfolio optimization (Markowitz, Black-Litterman)
- Time series analysis and forecasting
- Options pricing and Greeks calculation
- Statistical arbitrage and pairs trading

## Approach

1. Data quality first - clean and validate all inputs
2. Robust backtesting with transaction costs and slippage
3. Risk-adjusted returns over absolute returns
4. Out-of-sample testing to avoid overfitting
5. Clear separation of research and production code

## Output

- Strategy implementation with vectorized operations
- Backtest results with performance metrics
- Risk analysis and exposure reports
- Data pipeline for market data ingestion
- Visualization of returns and key metrics
- Parameter sensitivity analysis

Use pandas, numpy, and scipy. Include realistic assumptions about market microstructure.

© Seth Hobson · MIT · wshobson/agents

See also

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