L1 Trend Filtering to Extract Piecewise-Linear Market Trends

Summary

The document introduces an L1 trend filter as a way to extract piecewise-linear trends from noisy price data while retaining major market structure. It describes a demonstration implemented in MQL5 for both float and double vectors, applied to simulated random-walk data.

The text explains the filter’s purpose and points readers toward a separate article for trading applications. It offers no performance results, parameter guidance, or detailed evaluation of how the method behaves on real market data. The example therefore illustrates implementation and concept rather than establishing that the filter improves trading decisions.

Key ideas

• L1 trend filtering can represent a price series as piecewise-linear segments.
• The method aims to reduce noise while preserving essential market structure.
• The demonstration applies the filter to random-walk data using MQL5 vector types.
• The document does not report trading results or validate performance on live markets.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.