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Quantumine Learn is a free library on financial markets and quantitative trading, built by Quantumine.

Who it is for

  • People learning quantitative trading. Each article explains one concept, from how markets work to how a strategy gets automated.
  • AI agents. Every page has a Markdown version that an AI assistant can look up and cite.

What is in it

The library is divided into six categories:

Core concepts

The concepts every other article builds on: orders, the order book, trading costs, leverage, returns and volatility.

Indicators

How each indicator is calculated, what its settings change, and where it misleads.

Backtesting

How to test a strategy on historical data, read the performance metrics, and spot the mistakes that make results look better than they really are.

Strategies

The hypothesis behind each strategy, what its rules are, and when it fails.

Risk management

How to size positions, limit losses, and keep an account alive through losing streaks.

Automation

How to turn a strategy into a program that places its own orders: architecture, exchange connectivity, test runs and operation.

What you will be able to do

The library is built so that you can do each of these yourself:
How orders get matched, where prices come from, and how much of your profit fees, spread and slippage take.
Know each indicator’s formula, what its settings change, and where it misleads, instead of treating it as a black box.
Write a trading idea as clear rules: when to enter, when to exit, and how large each trade should be.
Backtest a strategy, read the results through the Sharpe ratio and drawdown, and spot the mistakes that make results look better than they really are, such as overfitting and look-ahead bias.
Work out the size of each position and set loss limits, so that a run of losing trades does not wipe out the account.
Code a strategy as a program that places its own orders, connect it to an exchange or broker, then run and monitor it.

Next steps

  • Quickstart: how to read the library and connect your AI agent.
  • Core concepts: where to start if you are new to the subject.
  • Changelog: what has newly been published.