Measuring the Value of Scaling Out with Exit-Price Counterfactuals
Summary
The article describes an MQL5 analyzer that reconstructs positions from closing deals and evaluates trades exited in multiple parts. It computes each exit leg’s net result per lot, including commission and swap, then reprices the full position at the first, last, and best realized exit rates. These comparisons estimate the value added versus exiting everything at the last rate and the share of the best observed outcome captured by the actual scale-out.
The tool also aggregates value-add as a ratio of sums, reports excluded positions built from multiple entry deals, and proposes checks for dependence on a single trade before assigning a configurable grade and recommendations. The method uses only prices the trader actually received, but its counterfactuals are limited: they assume costs scale linearly with volume and implicitly borrow the chosen exit leg’s holding-time effects, especially for swap. The article explains the analyzer and its data flow, but the supplied excerpt gives no numerical performance results or evidence that scaling out improves future trading outcomes.
Key ideas
- Reconstruct positions by grouping closing deals that share a position identifier.
- Compare actual scale-out results with full-size outcomes repriced at realized exit rates.
- Include commission and swap in per-lot exit rates, while recognizing the linear-cost assumption.
- Aggregate value-add as a ratio of sums to avoid unstable per-position percentages.
- Exclude multi-entry positions and report the exclusion rather than blending their entries.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.