QuantConnect

Community

AI builds QuantConnect strategies, you review.

Authorderekcrosslu
Version1.0.0
Installs0

System Documentation

What problem does it solve?

Developing, testing, and optimizing quantitative trading strategies on QuantConnect is a complex, time-consuming, and iterative process. This Skill automates the entire workflow, from initial strategy generation and coding to remote backtesting, optimization, and performance analysis, freeing you from manual intervention and accelerating your research.

Core Features & Use Cases

  • Autonomous Strategy Development: Automatically generate, code, and refine QuantConnect trading algorithms based on your requirements.
  • Full QuantConnect API Integration: Seamlessly upload strategies, execute backtests, and run parameter optimizations directly through the QuantConnect cloud API.
  • Intelligent Performance Analysis: Automatically parse backtest results, identify key metrics (Sharpe, drawdown, return), and make data-driven decisions on strategy viability or further optimization.
  • Use Case: Instruct the AI to "Develop a robust mean-reversion strategy for tech stocks." The Skill will autonomously code the algorithm, backtest it across various market conditions, optimize its parameters, and present you with a fully validated strategy and its performance report.

Quick Start

Use the QuantConnect skill to develop a new RSI mean-reversion strategy for SPY, then automatically backtest and analyze its performance.

Dependency Matrix

Required Modules

requestspython-dotenv

Components

referencesassets

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: QuantConnect
Download link: https://github.com/derekcrosslu/CLAUDE_CODE_EXPLORE/archive/main.zip#quantconnect

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
View Source Repository