Using Excel to Analyze Gold Day-of-Week Seasonality

Summary

The article demonstrates a spreadsheet workflow for exploring a claimed weekday pattern in gold-related prices. Using GLD price history, it derives log returns and calendar fields, groups returns by weekday in a pivot table, and charts the sums. It reports higher Friday returns and negative Monday returns, with Monday the only weekday showing a negative sum. A second grouped view suggests the combined Friday-long and Monday-short effect appeared in all but four years in the dataset.

To inspect its evolution, the author defines a daily metric that takes Friday returns, reverses Monday returns, and assigns zero to other days, then plots its cumulative sum over time. The author explicitly distinguishes this frictionless descriptive curve from a backtest of implementable rules. The analysis offers no causal explanation, and the apparent pattern may be a random artifact or disappear. The suggested Friday trade is to be tested with realistic costs and sized conservatively; the Monday short is considered too small relative to costs.

Key ideas

• Pivot tables can group summed log returns by weekday to inspect seasonal patterns.
• The article reports stronger Friday returns and negative Monday returns in its GLD sample.
• A yearly aggregation and cumulative metric help examine whether the pattern persists over time.
• A cumulative return plot without costs is descriptive analysis, not a realistic strategy backtest.
• The author sees no plausible cause for the effect and recommends caution, realistic costs, and small sizing.

Tags

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