Measuring Bitcoin’s Average Monthly Returns and Seasonal Win Rates
Summary
This indicator groups Bitcoin price changes by calendar month over a configurable historical lookback. It records each completed month’s return as either a percentage or a price change, then calculates the average return and the share of observations with positive returns for each month. A chart can display monthly averages as bars or a line, either as standalone monthly values or cumulatively across the calendar year. A table reports the average, win rate, and observation count, with visual emphasis on the historically strongest and weakest average months.
The output is descriptive seasonality analysis, not a trading system or evidence that a seasonal pattern will persist. The sample is limited by the selected lookback and available chart history, so monthly observations may be few and regime-dependent. A positive historical win rate does not capture return magnitude, volatility, costs, or risk-adjusted performance. The document provides no actual monthly readings or out-of-sample evaluation, and the displayed summaries should be treated as exploratory rather than predictive.
Key ideas
- Monthly price changes are grouped by calendar month over a configurable lookback period.
- For each month, the indicator calculates the average return and the proportion of positive observations.
- Returns can be displayed as percentages or price differences, with an optional cumulative view.
- The table includes a sample count to show how many observations contribute to each monthly statistic.
- Historical averages and win rates are descriptive and do not establish a persistent or profitable seasonal effect.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.