Strategy #0000000082 · Calendar effects and seasonality
Calendar-month return seasonality
Enter same-month history, off-season comparison return and costs for a simplified scenario spread.
Seasonality strategies compare a stock’s historical returns in the same calendar month with other months. Heston and Sadka document persistent calendar-month patterns; explanations include cash flows, investor behaviour and seasonal risk. Multiple testing, data mining, month selection and trading costs can inflate in-sample results.
Seasonality varies across samples and markets; selecting the best-performing month creates data-mining bias.
Three ways in
Understand the story. Then inspect the risk.
Start with a familiar situation, check the payoff, then test how the numbers change.
The idea · in two minutes
What assumed return spread separates a recurring calendar month from off-season periods?
Seasonality strategies compare a stock’s historical returns in the same calendar month with other months. Heston and Sadka document persistent calendar-month patterns; explanations include cash flows, investor behaviour and seasonal risk. Multiple testing, data mining, month selection and trading costs can inflate in-sample results.
Enter same-month history, off-season comparison return and costs for a simplified scenario spread.
Seasonality varies across samples and markets; selecting the best-performing month creates data-mining bias.
- Signal metricEnter same-month history, off-season comparison return and costs for a simplified scenario spread.
- Return scenarioSeasonality varies across samples and markets; selecting the best-performing month creates data-mining bias.
Illustrative research examples only. They are not live signals or a recommendation.
The mechanics · payoff and exposure
R_{season}=R_{same\ month}-R_{off\ season}-C
Same month means the same calendar month across years; off-season is the comparison window, using a consistent horizon.
Greeks: the directional intuition
- 資料時點
- Measures sensitivity to implied volatility.
- 模型風險
- Measures sensitivity to implied volatility.
- 執行成本
- Measures sensitivity to implied volatility.
R_{season}=R_{same\ month}-R_{off\ season}-C
Practical context · published observations
Calendar-month return seasonality: read the record with its caveats.
The chart uses the published figures or explicitly labelled study inputs below. A historical index or model replay is not the same as an investor’s realised account return.
Seasonality varies across samples and markets; selecting the best-performing month creates data-mining bias. Source ↗ · Methodology ↗
Change assumptions and inspect the scenario
Inputs illustrate the strategy mechanics; they are not live quotes, forecasts or investment advice.
Variants · same family, different risk levers
Related approaches use different horizons and data.
Compare ranking rules, holding periods and cost assumptions.
| Related strategy | Relationship | What changes | New cost or risk |
|---|---|---|---|
| Core version | Signal sort | Seasonality strategies compare a stock’s historical returns in the same calendar month with other months. Heston and Sadka document persistent calendar-month patterns; explanations include cash flows, investor behaviour and seasonal risk. Multiple testing, data mining, month selection and trading costs can inflate in-sample results. | Seasonality varies across samples and markets; selecting the best-performing month creates data-mining bias. |
| Industry-neutral version | Relative ranking | Compare firms within similar industries. | Classification and small samples affect signals. |
| Multi-signal version | Factor combination | Combine with quality or liquidity signals. | Adds weight, collinearity and data-mining risk. |
Seasonality varies across samples and markets; selecting the best-performing month creates data-mining bias.
Read beyond the summary
References
Primary sources and research used to describe the strategy and its limits.