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1994issue C121-5

Seasonal range regimes as a futures context overlay

Archive notes summarized domestic futures as one monthly barometer of aggregate trading-range change. Editorial reading: treat that seasonal-range-map as a regime-overlay around a live book, not as a switch that starts or stops the program.

  • Domestic futures were summarized as one monthly barometer of aggregate range change, and range-expansion was treated as a prerequisite for trends of significant degree.
  • The seasonal-range-map placed range-contraction in a spring tax-period lull, July and August vacation months, and a late-year holiday stretch, with expansion windows in the intervals between.
  • Seasonal maps were not treated as a reason to halt trading. Exceptions were cited as the case for staying in the program and adding a sideways-safeguard.
  • Expanding ranges were associated with fewer trades and larger vertical opportunity; contracting ranges with more trades and smaller opportunity.
Entries in this reading3 entries
Market regime classification52 readingsCurrent trackSeasonality analysis65 readingsSeasonal analysis67 readings

A monthly barometer of the complex

Domestic futures markets were summarized as one monthly barometer of aggregate trading-range change rather than a weekly or daily measure. Range-expansion was treated as a prerequisite for trends of significant degree. Without that widening of aggregate ranges, those trends were described as absent.

Expanding ranges were associated with fewer trades and larger vertical opportunity. Range-contraction was associated with more trades and smaller opportunity.

Where the seasonal-range-map placed quiet and active months

Recurring contraction windows were tied to a spring tax-period lull, July and August vacation months, and a late-year holiday stretch from late November through year-end. Expansion windows were placed in the intervals between those contraction stretches, when vertical price movement becomes more available to trend-seeking methods across time frames.

On that seasonal-range-map, January, July, and August were classified as contraction months. February and March were classified as expansion months.

Monthly seasonal range of U.S. futures

Aggregate trading-range level by calendar month for the domestic futures complex. Purple months are expansion/trend windows; yellow months are the consolidation windows Angle flagged (April, July–August, November–December). Values are read from the printed Figure 1 bars, not from a table.
Aggregate trading-range level by calendar month for the domestic futures complex. Purple months are expansion/trend windows; yellow months are the consolidation windows Angle flagged (April, July–August, November–December). Values are read from the printed Figure 1 bars, not from a table.U.S. futures complex (aggregate) · month

Y-axis ticks on the 1994 3-D original run from about 420 at the top rail down to 800; bars hang from that upper rail. Heights are approximate digitizations of a rotated column chart, so treat them as the shape of the seasonal map rather than exact index prints. Angle used this as a monthly barometer of all major U.S. futures, not a single contract.

Composite-alignment and the two exceptions

A month-to-month comparison used eight years of relative range-change data against six years of an industry managed-futures composite. In that composite-alignment, ten of twelve calendar months aligned in direction of change. April and September were the two exceptions.

Context around the book, not a halt rule

Seasonal maps were not treated as a reason to halt trading. Exceptions over a 15-year window were cited as the case for staying in the program and adding a sideways-safeguard instead.

Most programs were described as tied to major trends created by the price environment, so mixing books solely for noncorrelation was presented as harder than it first appears.

Editorial reading: a regime-overlay uses the calendar as context for an existing program. It does not replace process with a rule that starts or stops trading.

Educational research material, not investment advice. Historical source context does not establish present-day performance.
5 of 41 in the Seasonality analysis track
19961-6 pp.Next on Seasonality analysisEvaluating presidential party terms as equity regimesParty-term-regime windows were labeled by the party occupying the White House, not by a specific president, and a same-party successor was treated as continuing that term's policy regime.
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 year199488 readings
All 65 readings tagged Seasonality analysis
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