quant-practice

Generate Jupyter notebooks with quantitative finance practice questions and solutions.

Updated Dec 20, 2025
One-click install
npx skills add https://github.com/jwplatta/ml_gym --skill quant-practice
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: quant-practice
Source: https://github.com/jwplatta/ml_gym/tree/main/.claude/skills/quant-practice
Command: npx skills add https://github.com/jwplatta/ml_gym --skill quant-practice

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires nbformat, yfinance, numpy, pandas, scikit-learn, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill automates the creation of personalized quantitative finance practice problems and their corresponding solutions, streamlining the learning process for complex financial concepts.

Core Features & Use Cases

  • Notebook Generation: Creates Jupyter notebooks pre-populated with practice questions.
  • Customizable Topics: Allows users to specify desired topics (e.g., returns, portfolio, signals).
  • Novel Question Generation: Generates unique questions based on templates, varying parameters like tickers and values.
  • Use Case: A student preparing for a finance exam can use this Skill to generate a set of 10 practice problems focused on portfolio optimization, complete with step-by-step solutions.

Quick Start

Use the quant-practice skill to generate 5 practice questions on the topic of returns.

Frequently Asked Questions about quant-practice

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate Jupyter notebooks with quantitative finance practice questions?

You can generate Jupyter notebooks with quantitative finance practice questions by using a template-driven script that modifies parameters like tickers, numbers, and date ranges to create novel problems and solutions.

Can I customize the topics and number of practice questions in a generated quant notebook?

Yes, you can customize both the topics and the number of practice questions. The notebook generation supports user-defined counts and specific quant topics like returns, portfolio optimization, and signals.

Do I need yfinance and pandas to run quantitative finance practice notebooks?

Yes, you need yfinance and pandas, along with numpy, scikit-learn, and nbformat. These dependencies support the financial data retrieval, numerical analysis, and notebook formatting required for the practice problems.

What's the best way to create unique quantitative finance exam problems from templates?

The best way to create unique quantitative finance exam problems is by running a Python script that selects from example templates and varies parameters like tickers and date ranges to generate novel questions with step-by-step solutions.

Does this quant practice generator support portfolio optimization and trading signals topics?

Yes, this quant practice generator supports portfolio optimization and trading signals topics. It populates Jupyter notebooks with customizable practice questions and solutions covering these specific quantitative finance areas.

Why use Jupyter notebooks for quantitative finance practice instead of plain Python scripts?

Jupyter notebooks are used for quantitative finance practice because the nbformat dependency structures the practice questions and solutions into an interactive document, allowing students to execute and modify financial analysis code directly.