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7 Steps to Start with Algorithmic Trading

A sequential beginner roadmap for algorithmic trading in Python

From the Xiry library · Updated 11 October 2026

This list outlines an ordered learning path for getting started with algorithmic trading using the Python data ecosystem. It moves from core programming and editor setup to data analysis, portfolio optimization, and backtesting. It serves as a focused roadmap for beginners to avoid getting overwhelmed by tooling choices.

The list

  1. Start with Python
  2. Learn to use VSCode
  3. Take a pandas tutorial
  4. Then a plotly tutorial
  5. Make a portfolio with riskfolio
  6. Make a backtest with vectorbt
  7. Analyze performance with vectorbt

What it's for

  • Plan a self-directed curriculum for learning quantitative finance
  • Select an initial Python tech stack for financial data analysis
  • Build and backtest quantitative trading strategies using vectorbt

Key points

  • Foundational setup using Python and VS Code
  • Data manipulation fundamentals using pandas
  • Financial data visualization using Plotly
  • Portfolio construction and optimization using Riskfolio-Lib
  • Strategy backtesting and performance analytics using vectorbt

Pricing

Free

Details

Type
List
Category
Learning
Topic
Algorithmic Trading
Platforms
other
For
Beginner quantitative analysts and developers learning algorithmic trading
Tags
trading, python, datascience, finance, roadmap

Why it was saved

  • @quantscience_, 21 February 2025: A concrete ordered toolchain: the exact libraries and tools to learn in sequence, ending with vectorbt backtesting and performance analysis.

Related

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