Testing Weekend Gap Fills with MQL5 Data and Survival Analysis
Summary
This article sets out a reproducible study of whether forex weekend gaps return to the preceding Friday close. It defines gap size in pips, identifies a fill when price reaches that close, and measures elapsed time from Monday’s open to the first fill. The protocol limits observation to a configured window, filters gaps by size, and excludes cases lacking the required minute-level history. An MQL5 Expert Advisor collects gap and fill data across selected symbols and exports CSV files; Python then cleans the data, summarizes fill rates by gap-size bucket and time limit, fits a logistic model, estimates time to fill with Kaplan–Meier analysis, and produces plots and a report.
The stated outputs are designed to test whether fill probability or speed varies with gap size and to assess observed cumulative fill rates over time. The article does not provide the study’s actual statistical findings, so it cannot establish that gaps tend to fill or that any interval is especially reliable. Even with reproducible data collection, fill statistics alone do not define an entry, exit, or position-sizing strategy, and results depend on data availability and the chosen measurement rules.
Key ideas
- A weekend gap is measured as the signed difference between Monday’s open and Friday’s close, expressed in pips.
- A fill occurs when price touches the Friday close in the direction that closes the gap.
- The study tracks first-fill time within a fixed observation window and excludes unavailable history from analysis.
- An MQL5 Expert Advisor collects data that Python uses for logistic regression and Kaplan–Meier analysis.
- Fill rates and time-to-fill estimates can inform further research, but do not constitute a complete trading strategy.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.