Building a Chart-Based Workflow for Labeling Trend Time Series
Summary
The document describes a manual workflow for creating labeled time-series datasets from market charts. Instead of splitting a price series into separate files by trend direction, it adds a trend-group field to each observation so that the original chronological series remains intact. A further trend-index field records each observation's position within its labeled trend segment, supporting analyses that distinguish stages of trend development.
An MQL5 chart tool is used to navigate bars, mark segments, and write market fields and labels to a CSV file. The workflow also describes resuming from an existing file by locating its last annotated time and returning the chart to that point. The examples show the proposed data format and operation logic, not evidence that labels improve a forecasting model. Trend definitions and segment boundaries are chosen by the annotator, so consistency and potential subjectivity are important limitations; the article also says its demonstration code may need further refinement before practical use.
Key ideas
- Trend labels can be stored alongside each bar to preserve the full chronological series.
- A trend-group field identifies the assigned direction, while a trend index records position within a segment.
- The MQL5 workflow supports chart navigation, manual annotation, and CSV output.
- Existing annotation files can be used to resume labeling from the last recorded time.
- Labels depend on human-defined trend boundaries and require consistent annotation rules.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.