Measuring Monthly Market Seasonality with Average Returns and Reliability

Summary

This indicator measures historical seasonality by grouping monthly price changes by calendar month, using data from a chosen starting year and month through the present. For each month, it reports the average open-to-close return, a normalized rank relative to the strongest and weakest monthly averages, and a reliability percentage based on how often that month rose or fell. The author suggests comparing shorter and longer lookback periods to judge whether observed patterns persist, and describes using the rank to vary position size or reliability to screen directional exposure.

The document provides indicator code but no market-specific output or evidence that the seasonal patterns predict future returns. Its reliability measure is simply the share of historical observations moving in the favored direction; it is not a probability guarantee. The calculation also depends on available history and chosen dates, and monthly average returns omit trading costs, within-month risk, and changing market regimes. Seasonal signals therefore need separate out-of-sample testing before they inform a strategy.

Key ideas

• The indicator groups monthly price changes by calendar month over a user-selected history.
• It reports average monthly return, relative rank, and the share of observations in the favored direction.
• Comparing different lookback windows can help assess whether a seasonal pattern is stable.
• Historical directional frequency is descriptive and does not guarantee future outcomes.
• The indicator does not account for costs or intramonth risk and needs separate validation.

Tags

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