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Quantitative Trade

Quantitative trading self-learning environment with Marimo notebooks.

Aim

Learn quantitative trading concepts and techniques through hands-on practice, focusing on:

  • Understanding market data and price patterns
  • Building and visualizing technical indicators
  • Developing trading strategies with real Chinese A-share data

Objectives

  1. Data Acquisition: Fetch and process Chinese stock market data using akshare
  2. Data Analysis: Use polars + narwhals for efficient data manipulation
  3. Visualization: Create interactive K-line charts with plotly
  4. Strategy Development: Experiment with quantitative trading ideas

Tech Stack

Component Technology
Notebook marimo >= 0.19.4
Data Processing polars, narwhals
Data Source akshare (Chinese A-shares)
Visualization plotly, seaborn
Dev Tools ruff, mypy

Quick Start

# Install dependencies
uv sync

# Start Marimo notebook server
marimo run notesbooks/*
marimo edit --watch notesbooks/*

Requirements

  • uv
  • git
  • just

Caveat

To use BaoStock source in batch reading, please use in windows:

if __name__ == "__main__":
    multiprocessing.freeze_support()
	...

Due to the child processes re-importing and re-executing the entire module infinitely.

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Quant-Trade Self-Learning

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