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2019issue C0920-23

Hit-rate gates for seasonal regime evaluation

A yearly-average seasonal map can rank a month as the seasonal high when a few standout years dominate. Positive-return frequency, a rolling four-year window, and a consistency gate turn that map into a regime overlay that can stay flat.

  • A yearly-average seasonal map can rank a month as the seasonal high when a few standout years dominate, even if that month is ordinary in most other years.
  • Positive-return frequency counts only whether a month was above zero, and that count is used to judge whether a seasonal peak or trough is consistent.
  • A rolling four-year window and a consistency gate allow seasonal abstention when the map is too muted to show one reliably strong month and one reliably weak month.
  • Because the frequency rules do not follow trend or momentum logic, they are framed as a diversification sleeve rather than a substitute for those approaches.
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Current trackSeasonality analysis65 readingsSeasonal trading90 readingsMechanical trading system172 readings

What a yearly-average seasonal map measures

A yearly-average seasonal map is built by scaling each month’s price to that year’s mean, subtracting one, and then averaging those scaled values across years by calendar month. The map is a calendar profile of how each month sits relative to that year’s average price.

A month can rank as the seasonal high on average returns because a few standout years dominate, even when that month is ordinary in most other years. Average size and year-to-year regularity are different questions.

Positive-return frequency

Counting how often a month’s return is merely positive, regardless of size, is used to judge whether a seasonal peak or trough is consistent. That share is the positive-return frequency.

In the corn frequency illustration, February, March, and April each show an 80 percent chance of a positive monthly return, versus 10 percent in October. The airline-equity frequency illustration, using 13 years beginning in 2006, stays inside a 40-to-60 percent band and therefore shows less calendar conviction than the futures example.

Corn monthly positive-return frequency

Share of years in which corn’s yearly-average-adjusted monthly return was positive, 2009–2018. February, March and April each print 80 percent; October prints 10 percent. Values are the last row of the corn adjusted-returns table, not a yearly-average seasonal map.
Share of years in which corn’s yearly-average-adjusted monthly return was positive, 2009–2018. February, March and April each print 80 percent; October prints 10 percent. Values are the last row of the corn adjusted-returns table, not a yearly-average seasonal map.Corn futures · monthly · 2009-01-01T00:00:00.000Z to 2018-12-31T00:00:00.000Z

Each month’s price is divided by that year’s average, then 1 is subtracted. Frequency counts only the sign of that residual, not its size. The 2009–2018 window is the decade shown in the table.

A rolling four-year window and a consistency gate

The mechanical overlay averages each month’s positive-return frequency over the prior four years. That rolling four-year window recomputes monthly hit rates so the seasonal map can change as recent years replace older ones.

When two months tie at an extreme, the overlay uses the latest calendar month. It requires a high of at least 75 percent and a low of at most 25 percent before any trade is allowed. That pair of hit-rate thresholds is the consistency gate.

If the rolling frequency map is too muted to meet the consistency gate, the stance is seasonal abstention: stay flat.

Month-end calendar order

If the high-frequency month occurs first, the rule shorts at that month-end and covers at the low-frequency month-end. If the low-frequency month occurs first, it buys at that month-end and exits at the high-frequency month-end. Direction and holding span follow month-end calendar order: which extreme month arrives first in the year.

Movable equity calendars

Equity seasonality is treated as movable because shopping calendars, off-season travel discounts, and year-round retail can shift when monthly highs and lows appear. The same rule set is examined on commodity futures and on a narrow equity group of airlines, home builders, and large hotel chains.

A broad-market fund is used to show that a persistent upward drift can look like a seasonal edge if individual trades are not inspected.

A diversification sleeve

Because the frequency rules do not follow trend or momentum logic, they are framed as a diversification sleeve rather than a substitute for those approaches. In that framing the hit-rate map is a regime overlay: market-state context rather than a forecast of return size.

Educational research material, not investment advice. Historical source context does not establish present-day performance.
37 of 41 in the Seasonality analysis track
201948-49 pp.Next on Seasonality analysisJuly to October as a seasonal window, not a reason to own the nameThe archive case defined the seasonal window as one calendar entry and exit: buy on 14 July and sell on 3 October.
All readings on this track · 41 readings
  1. 1989Evaluating venue volume as a speculation-breadth signal
  2. 1991A thirty-name price-weighted average as a seasonal regime classroom
  3. 1991Ranked half-year rate changes as an equity signal filter
  4. 1991Demographic wave as a market-regime overlay
  5. 1994Seasonal range regimes as a futures context overlay
  6. 1996Evaluating presidential party terms as equity regimes
  7. 1996A dominant cycle is a baseline, not a reprint
  8. 1996Seasonality and presidential election cycle regimes
  9. 1997Stacking calendar regimes around election years
  10. 1997Calendar seasonality as a testable trading procedure
  11. 1997Lunar phase delay as a testable seasonal regime
  12. 1998Seasonal system construction without curve-fitting
  13. 1999Crowd life cycle as a market regime map
  14. 2001Regime-dependent cycle timing after four-year and seasonal lows
  15. 2002A 2002 case study in regime-first seasonal selection
  16. 2002Seasonal windows and dominant-cycle rules
  17. 2002Fifty-four-year wholesale cycle as an inflation-deflation regime map
  18. 2004The championship conference rule as a yearly regime case study
  19. 2004Election-year seasonality as trade regime context
  20. 2006Two-ten inversion as an intermarket regime filter
  21. 2006Midterm-to-presidential seasonal holding window
  22. 2008Two-layer equity regimes from seasonality and price history
  23. 2008Seasonal futures as a regime filter, not a calendar rule
  24. 2008Retesting seasonal rules when regimes change
  25. 2010Corn and wheat staggered calendars as dollar-neutral seasonal spreads
  26. 2011Name the S&P 500 trend regime before using weekly and monthly seasonality
  27. 2012Seasonal windows that wait for confirmation
  28. 2013Pair-sleeve rotation as a two-state sector regime-switch
  29. 2013Lunar phase as a seasonal overlay on implied volatility
  30. 2013Soybean seasonal highs in a five-year carryover regime
  31. 2014Year-end tax-loss selling as a seasonal regime
  32. 2017Calendar-window overlays that mute mechanical signals without rewriting the system
  33. 2017A four-year cycle and volume case study of a secular bear
  34. 2017Treat the valuation climate as climate and implied-volatility extremes as weather
  35. 2019Seasonal depth versus tracking for futures position sizing
  36. 2019Stacking cycle forecasts with seasonal regimes
  37. 2019Hit-rate gates for seasonal regime evaluation
  38. 2019July to October as a seasonal window, not a reason to own the name
  39. 2020A recession-regime checklist from valuation stretch and the yield curve
  40. 2020Treat a seasonal idea as a stay-or-sit holding procedure
  41. 2020A single position as a sleeve on a seasonal regime map
By fieldSeasonality and regimes131 readingsBy year201992 readings
All 65 readings tagged Seasonality analysis
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