Using Signal Groups to Match Entries with Their Own Exit Rules

Summary

This tutorial explains how to group trading instructions so positions opened by one setup are closed according to that setup’s exit conditions. It distinguishes filtered models, where groups pair distinct entry and exit signals, from unfiltered models, where groups can separate initial entries, add-on entries, and their respective stops. Examples use moving-average crosses, KDJ signals, breakouts, and price-based stops, with group identifiers and position-volume references in the platform’s strategy language.

The article also describes sequencing rules: filtered models apply group filtering before signal filtering, while unfiltered models constrain subsequent signals according to the active group and whether its position remains open. Worked examples show how to assign different exits to trend and swing entries, and different exits to staged positions. These are implementation examples, not performance evidence; the document does not report backtests or live results, and its rules are specific to the described platform syntax.

Key ideas

• Groups associate an entry signal with the exit conditions intended to close that position.
• Filtered models separate entry and exit setups, while unfiltered models can distinguish initial entries from add-ons.
• The platform applies signal-order and group-position rules that constrain which subsequent signals are valid.
• Examples combine moving averages, KDJ, breakouts, and price-based stops across separate groups.
• The tutorial explains implementation mechanics but provides no evidence of strategy profitability.

Tags

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