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Agent skill

Quant Analyst

by majiayu000 in majiayu000/claude-skill-registry

Expert in quantitative finance, algorithmic trading, and financial data analysis using Python (Pandas/NumPy), statistical modeling, and machine learning.

MITAuto-check passedData & Analytics

Install Quant Analyst

skills CLI
$ npx skills add majiayu000/claude-skill-registry --skill quant-analyst -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install majiayu000/claude-skill-registry quant-analyst --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/analysis/quant-analyst-skill .claude/skills/quant-analyst && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
quant-analyst
GitHub stars
666
Used in
1 other repo
Token cost
~964 tokens
SKILL.md length
387 words
Files
2
Skills in repo
971
Repo updated
First seen
Licence
MIT

At a glance

Expert in quantitative finance, algorithmic trading, and financial data analysis using Python (Pandas/NumPy), statistical modeling, and machine learning.

  • Works in 3 steps: Algorithmic Trading Strategy Development → Risk Model Implementation → Portfolio Optimization
  • Tasks that involve Trading and backtesting
  • SKILL.md covers Purpose, When to Use, Quick Start and Decision Framework, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Quant Analyst is an agent skill from majiayu000/claude-skill-registry. Expert in quantitative finance, algorithmic trading, and financial data analysis using Python (Pandas/NumPy), statistical modeling, and machine learning.

Its SKILL.md is about 960 tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `metadata.json`).

It sits in Data & Analytics, covering Trading and backtesting and DataFrames. It works with Python, pandas and NumPy. The repository describes itself as: Searchable Claude Code skills catalog with source-linked guides and generated registry artifacts. The licence is MIT.

When your agent uses it

  • Tasks that involve Trading and backtesting
  • Tasks that involve DataFrames

Example prompts

  • “/quant-analyst”

Requirements

  • Python 3

Workflow steps

3 steps, taken from the step headings in SKILL.md.

  1. Algorithmic Trading Strategy Development
  2. Risk Model Implementation
  3. Portfolio Optimization

What it can do on your machine

Read from SKILL.md and the folder at commit 000116a. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Quant Analyst loads about 964 tokens when it runs. Until then it costs about 42 tokens; SKILL.md has 387 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~42
When it runs · the whole SKILL.md, loaded when a task matches
~964

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from majiayu000/claude-skill-registry at commit 000116a, republished under its MIT licence (© majiayu000). 387 words, ~964 tokens.

Download SKILL.mdSave it as .claude/skills/quant-analyst/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
quant-analyst
description
Expert in quantitative finance, algorithmic trading, and financial data analysis using Python (Pandas/NumPy), statistical modeling, and machine learning.

Quantitative Analyst

Purpose

Provides expertise in quantitative finance, algorithmic trading strategies, and financial data analysis. Specializes in statistical modeling, risk analytics, and building data-driven trading systems using Python scientific computing stack.

When to Use

  • Building algorithmic trading strategies or backtesting frameworks
  • Performing statistical analysis on financial time series data
  • Implementing risk models (VaR, CVaR, Greeks calculations)
  • Creating portfolio optimization algorithms
  • Developing quantitative pricing models for derivatives
  • Analyzing market microstructure and order book dynamics
  • Building factor models for asset returns
  • Implementing Monte Carlo simulations for financial instruments

Quick Start

Invoke this skill when:

  • Building algorithmic trading strategies or backtesting frameworks
  • Performing statistical analysis on financial time series data
  • Implementing risk models (VaR, CVaR, Greeks calculations)
  • Creating portfolio optimization algorithms
  • Developing quantitative pricing models for derivatives

Do NOT invoke when:

  • Building general web applications → use fullstack-developer
  • Creating data visualizations without financial context → use data-analyst
  • Implementing payment processing → use payment-integration
  • Building generic ML models → use ml-engineer

Decision Framework

Financial Analysis Task?
├── Trading Strategy → Backtesting framework + signal generation
├── Risk Management → VaR/CVaR models + stress testing
├── Portfolio Optimization → Mean-variance, Black-Litterman, risk parity
├── Derivatives Pricing → Monte Carlo, finite difference, analytical
└── Time Series Analysis → ARIMA, GARCH, cointegration tests

Core Workflows

1. Algorithmic Trading Strategy Development
  1. Define trading hypothesis and signal generation logic
  2. Implement strategy using vectorized Pandas operations
  3. Build backtesting engine with realistic execution simulation
  4. Calculate performance metrics (Sharpe, Sortino, max drawdown)
  5. Perform walk-forward optimization to avoid overfitting
  6. Implement live trading hooks with proper risk controls
2. Risk Model Implementation
  1. Gather historical price/returns data
  2. Select appropriate risk metric (VaR, CVaR, Greeks)
  3. Implement calculation using parametric, historical, or Monte Carlo methods
  4. Validate model with backtesting and stress scenarios
  5. Build monitoring dashboard for real-time risk exposure
Show full SKILL.md (135 more words)Show less
3. Portfolio Optimization
  1. Define investment universe and constraints
  2. Calculate expected returns and covariance matrix
  3. Implement optimization (scipy.optimize or cvxpy)
  4. Apply regularization to prevent concentration
  5. Rebalance periodically with transaction cost consideration

Best Practices

  • Use vectorized NumPy/Pandas operations for performance on large datasets
  • Always account for transaction costs, slippage, and market impact in backtests
  • Implement proper cross-validation (walk-forward) to prevent lookahead bias
  • Use log returns for statistical properties, simple returns for aggregation
  • Store financial data with timezone-aware timestamps (UTC preferred)
  • Validate models with out-of-sample testing before deployment

Anti-Patterns

  • Overfitting to historical data → Use walk-forward validation and regularization
  • Ignoring transaction costs → Include realistic costs in all backtests
  • Using future data in signals → Ensure strict point-in-time correctness
  • Assuming normal distributions → Use fat-tailed distributions for risk models
  • Hardcoding market assumptions → Parameterize and stress test assumptions

© majiayu000, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in skills/analysis/quant-analyst-skill of majiayu000/claude-skill-registry.

  • SKILL.md
  • metadata.json

Open the folder on GitHubat commit 000116a

Used in 1 other repository

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in majiayu000/claude-skill-registry, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Quant Analyst next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Quant Analyst compared with similar skills
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Quant Analyst this skillmajiayu000/claude-skill-registry6661 repos~964Automated safety check: PassMIT
Candlestick Pattern SignalsHKUDS/Vibe-Trading35k—~468Automated safety check: PassMIT
Machine Learning Trading StrategyHKUDS/Vibe-Trading35k—~3.2kAutomated safety check: PassMIT
Python Executorcortega26/chile-hub1132 repos~1.5kAutomated safety check: PassMIT
Vaex Out-of-Core DataFramesdavila7/claude-code-templates32k12 repos~1.6kAutomated safety check: PassMIT
DaskK-Dense-AI/scientific-agent-skills48k1 repos~4.4kAutomated safety check: NotesBSD-3-Clause

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Works with

Categories

Questions about Quant Analyst

What does Quant Analyst do?

Expert in quantitative finance, algorithmic trading, and financial data analysis using Python (Pandas/NumPy), statistical modeling, and machine learning. Quant Analyst is an agent skill from majiayu000/claude-skill-registry. Expert in quantitative finance, algorithmic trading, and financial data analysis using Python (Pandas/NumPy), statistical modeling, and machine learning.

When should I use Quant Analyst?

Quant Analyst fits situations like: tasks that involve Trading and backtesting; tasks that involve DataFrames.

How do I install Quant Analyst in Claude Code?

Run `npx skills add majiayu000/claude-skill-registry --skill quant-analyst -a claude-code`. Or copy the skill folder (skills/analysis/quant-analyst-skill in majiayu000/claude-skill-registry) into .claude/skills/quant-analyst in your project. Claude Code loads it when a task matches its description.

How do I install Quant Analyst in Codex?

Run `npx skills add majiayu000/claude-skill-registry --skill quant-analyst -a codex`. Or copy the skill folder (skills/analysis/quant-analyst-skill in majiayu000/claude-skill-registry) into .agents/skills/quant-analyst in your project. Codex loads it when a task matches its description.

Can I use Quant Analyst in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add majiayu000/claude-skill-registry --skill quant-analyst -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/quant-analyst, .gemini/skills/quant-analyst, .github/skills/quant-analyst and .opencode/skills/quant-analyst in your project.

What does Quant Analyst need to run?

SKILL.md names no scripts, command-line tools or credentials: Quant Analyst is instructions for the agent only. Our summary lists: Python 3.

Does Quant Analyst access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Quant Analyst safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Quant Analyst use?

Quant Analyst is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Quant Analyst use?

About 964 tokens (SKILL.md is roughly 3.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Quant Analyst?

Skills that share tags, products or a category with Quant Analyst: Candlestick Pattern Signals (HKUDS/Vibe-Trading, 35k stars), Machine Learning Trading Strategy (HKUDS/Vibe-Trading, 35k stars), Python Executor (cortega26/chile-hub, 113 stars) and Vaex Out-of-Core DataFrames (davila7/claude-code-templates, 32k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Quant Analyst?

majiayu000 (a GitHub user) maintains it in majiayu000/claude-skill-registry, which has 666 GitHub stars. The repository holds 971 skills in this directory. The repository was last updated on October 7, 2026.

Source: majiayu000/claude-skill-registry on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.