Discussing the article: "Price movement discretization methods in Python"

MetaQuotes 2025.10.02 13:19

Check out the new article: Price movement discretization methods in Python.

We will look at price discretization methods using Python + MQL5. In this article, I will share my practical experience developing a Python library that implements a wide range of approaches to bar formation — from classic Volume and Range bars to more exotic methods like Renko and Kagi. We will consider three-line breakout candles and range bars analyzing their statistics and trying to define how else the prices can be represented discretely.

Let's think about what really determines price movement. Time? No. Trading volume? Probably. Activity of major players? Definitely. In fact, all of these factors are important, but at different moments one or the other plays the main role.

Let's imagine a typical trading day. In the morning, low activity, rare deals. We can safely use H1 here. When London session starts, there is an explosion of volumes. Volume discretization is needed. During news events, there are sharp movements; range bars work better. And in calm and trendy periods, Renko or Kagi perform well.

That is why I decided to create a universal tool, a kind of Swiss army knife for working with market data. A script is a Python module that can: