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2019issue C0132-35

Seasonal depth versus tracking for futures position sizing

A seasonal overlay can stay off until a market shows historical seasonal consistency and the current year is highly correlated with that typical path. Only then is a short-horizon directional bias used to raise or lower contract count on an existing futures system, not to set a buy or sell date.

  • The overlay can stay off until a market shows historical seasonal consistency and the current year is highly correlated with that typical path.
  • seasonalDepth is inferred when 5-, 10-, 15-, and 20-year maps agree; seasonalAccuracy is how closely the live contract tracks those maps in the current year.
  • The seasonal outlook is not a fixed-date calendar. Agreement with an existing system can raise size and conflict can lower it.
  • Near-term shocks can knock a seasonal path off course. The overlay stays off unless current seasonalAccuracy remains high.
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Current trackSeasonality analysis65 readingsSeasonal analysis67 readingsSeasonal trading90 readings

What the overlay waits for

This archive case study describes a seasonal overlay on an existing systematic futures book. The overlay can stay off until a market shows historical seasonal consistency and the current year is highly correlated with that typical path. Only then is a short-horizon directional bias produced.

An imprecise directional roadmap

Seasonal maps are treated as an imprecise directional roadmap. The archive illustrates that idea with late-year crude softness after driving season, corn softness in the June to August growing window, sugar strength after the September to October harvest, and year-end equity strength tied to tax-related selling.

Long-horizon seasonalDepth

A weeks-ahead watch list of markets that may soon be in play comes first. Long-horizon seasonalDepth is then inferred when 5-, 10-, 15-, and 20-year seasonal maps are highly correlated. seasonalDepth is the stability of a market's typical path, judged by whether those several long-horizon maps agree with one another.

Current-year seasonalAccuracy and the projection

seasonalAccuracy is how closely the live contract is tracking those historical seasonal maps in the current year. Current-year tracking against the multi-year maps selects candidates for weighted 7-, 14-, and 21-day return projections. Those projections resolve to upside, downside, or mixed. That short-horizon result is the seasonalProjection. Only a definitive strong upside or downside result feeds the sizing algorithm.

Sizing on an existing system

The seasonal outlook is not used as a fixed-date buy or sell calendar. Agreement with an existing system can raise size and conflict can lower it. That use of seasonal agreement or conflict to raise or lower contract count is the sizingOverlay. Conservative application is defined as cutting the usual contract count when a long system signal faces a measured bearish seasonalProjection.

A slow depth list and a faster accuracy list

In a nightly ranking of 40 global futures by seasonalDepth, lean hogs, the S&P 500, and RBOB gasoline ranked among the most consistent names, while copper, wheat, and gold ranked among the most erratic.

A faster-rotating accuracy list can differ from the slower depth ranking. Energy contracts including crude oil, RBOB gasoline, and London gas oil then led current accuracy. Names with greater seasonal consistency can still move into and out of phase quickly.

Shocks and the regimeSwitch

Near-term shocks such as currency swings, drought, livestock disease, freeze, political unrest, tariffs, or earthquakes can knock a seasonal path off course. Lasting shocks take longer to be absorbed. The overlay stays off unless current seasonalAccuracy remains high. That on-or-off rule is the regimeSwitch: the seasonalProjection is applied only while seasonalDepth and current tracking remain acceptable.

Educational research material, not investment advice. Historical source context does not establish present-day performance.
35 of 41 in the Seasonality analysis track
201946-47 pp.Next on Seasonality analysisStacking cycle forecasts with seasonal regimesA dominant cycle is the most prominent oscillation from ordered price, volume, or breadth observations, and it belongs on the page as a forecast baseline.
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
Also on Seasonality analysis5 readings
1991A thirty-name price-weighted average as a seasonal regime classroom1997Stacking calendar regimes around election years2006Midterm-to-presidential seasonal holding window2008Retesting seasonal rules when regimes change2008Seasonal futures as a regime filter, not a calendar rule