matplotlib / matplotlib/mplfinance

Feature Request: Point and Figure (PnF) Traditional Box Scaling

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enhancement
Dominant language
Python
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Description

First, thank you for the great work on mplfinance!

I would like to request the addition of Traditional Box Scaling for Point and Figure (P&F) charts.

Currently, mplfinance supports fixed box scaling and dynamic ATR scaling. While these approaches are helpful, they both have important limitations in practice:

- Fixed box scaling fails to stay consistent across price levels. For example, a $1 move represents a 10% change when a stock is priced at $10, but only a 1% change when the same stock is priced at $100.
- Dynamic ATR or percent scaling solves this inconsistency but often produces non-round box values, which can be visually and psychologically unintuitive for market participants.

Image

Source: StockCharts.com

The Traditional Box Scaling, originally established by ChartCraft in the 1930s, resolves both these issues. It has long been the standard reference for Point and Figure charting and preserves both visual clarity and percentage consistency across price ranges.

This way, Point and Figure charts are actually very very helpful.

Sources: [https://chartschool.stockcharts.com/table-of-contents/chart-analysis/point-and-figure-charts/point-and-figure-basics/point-and-figure-scaling-and-timeframes](url)

Thank you for your time and for considering this enhancement.

![Image](https://github.com/user-attachments/assets/7e47fb9a-c400-42a3-862b-954848b446d6)

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by locating mplfinance's Point and Figure chart implementation and the existing fixed box scaling and dynamic ATR scaling paths. Read the linked StockCharts reference to define the traditional scaling rules, then determine the expected behavior and validation needed for charts using the new scaling mode.

Written by the indexing model from the issue text.

Assessment

Tech stack
matplotlib, python
Domain
data-visualization
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
30/100

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