> ## Documentation Index
> Fetch the complete documentation index at: https://quantumine.net/learn/llms.txt
> Use this file to discover all available pages before exploring further.

> ## Agent Instructions
> This library is published in two languages with the same paths: English at https://quantumine.net/learn/<path> and Vietnamese at https://quantumine.net/learn/vi/<path>. Add .md to either address for the Markdown version.
> llms.txt and llms-full.txt list the English pages only. When the reader writes in Vietnamese, read and cite the Vietnamese page.
> To search the library, connect to the MCP server at https://quantumine.net/learn/mcp. Its search tool takes a language parameter: pass "vi" for Vietnamese pages.

# Overview

Quantumine Learn is a free library on financial markets and quantitative trading, built by [Quantumine](https://quantumine.net).

## 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:

<CardGroup cols={2}>
  <Card title="Core concepts" icon="book-open" href="/learn/learn/core-concepts">
    The concepts every other article builds on: orders, the order book, trading costs, leverage, returns and volatility.
  </Card>

  <Card title="Indicators" icon="chart-line" href="/learn/learn/indicators">
    How each indicator is calculated, what its settings change, and where it misleads.
  </Card>

  <Card title="Backtesting" icon="flask" href="/learn/learn/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.
  </Card>

  <Card title="Strategies" icon="lightbulb" href="/learn/learn/strategies">
    The hypothesis behind each strategy, what its rules are, and when it fails.
  </Card>

  <Card title="Risk management" icon="shield-halved" href="/learn/learn/risk-management">
    How to size positions, limit losses, and keep an account alive through losing streaks.
  </Card>

  <Card title="Automation" icon="robot" href="/learn/learn/automation">
    How to turn a strategy into a program that places its own orders: architecture, exchange connectivity, test runs and operation.
  </Card>
</CardGroup>

## What you will be able to do

The library is built so that you can do each of these yourself:

<AccordionGroup>
  <Accordion title="Understand how markets work" icon="building-columns">
    How orders get matched, where prices come from, and how much of your profit fees, spread and slippage take.
  </Accordion>

  <Accordion title="Read and calculate indicators" icon="chart-line">
    Know each indicator's formula, what its settings change, and where it misleads, instead of treating it as a black box.
  </Accordion>

  <Accordion title="Turn an idea into a strategy" icon="lightbulb">
    Write a trading idea as clear rules: when to enter, when to exit, and how large each trade should be.
  </Accordion>

  <Accordion title="Test a strategy on historical data" icon="flask">
    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.
  </Accordion>

  <Accordion title="Manage risk" icon="shield-halved">
    Work out the size of each position and set loss limits, so that a run of losing trades does not wipe out the account.
  </Accordion>

  <Accordion title="Write an automated trading bot" icon="robot">
    Code a strategy as a program that places its own orders, connect it to an exchange or broker, then run and monitor it.
  </Accordion>
</AccordionGroup>

## Next steps

* [Quickstart](/learn/learn/getting-started/quickstart): how to read the library and connect your AI agent.
* [Core concepts](/learn/learn/core-concepts): where to start if you are new to the subject.
* [Changelog](/learn/learn/getting-started/changelog): what has newly been published.


This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.