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2004issue C051-4

Stress-test seasonal windows across regimes, then add channels

A late-February to mid-March long idea in May orange juice changed character once a longer history was put through a regime-split. A June-into-early-July window in September orange juice kept the same downward path and a Brazil frost-risk story. The preferred next step left the calendar as a research window and applied a three-price-channel breakout that could produce a stand-aside-year.

  • A seasonal-window is a fixed calendar interval used as a research hypothesis, not a date-pair-rule that buys one close and exits another.
  • Calendar holds shorter than one month were treated as especially likely chance alignments of two dates rather than durable seasonals.
  • A genuine seasonal was expected to rest on an identifiable fundamental driver and to keep the same character in every regime-split chart.
  • A window that repeated across subperiods and rested on a weather-fear-window story was then run as a three-price-channel procedure that allowed years with no entry.
Entries in this reading3 entries
Breakout system48 readingsSeasonal trading60 readingsCurrent trackPrice channel77 readings

A seasonal-window is a research hypothesis

A seasonal-window is a fixed calendar interval used as a research hypothesis for when a market may tend to move, not as an automatic entry and exit.

A date-pair-rule buys or sells on one calendar close and exits on another, without requiring confirmation from price structure. Calendar holds shorter than one month were treated as especially likely to be chance alignments of two dates rather than durable seasonals.

A genuine seasonal was expected to rest on an identifiable fundamental driver. A missing driver was treated as a marker of a computer-generated date pair.

The May orange juice window changed character

A late-February to mid-March long idea in May orange juice had been examined over only the most recent 17 years, even though a longer futures history was available.

Rebuilding May orange juice from 1968 through 2002 showed only a slight rise between 26 February and 17 March. A regime-split into four subperiod charts showed a downward path in 1968-76 and 1977-85, and the expected rise only in 1986-94 and 1995-2002.

Trade-by-trade review of that same May window reversed in character between 1968-85 and 1986-2002. That reversal was used to argue that a strong seasonal should appear in every subperiod chart.

A weather-fear-window that kept its shape

A June-into-early-July window in September orange juice showed a repeated downtrend on the full 1968-2002 chart and on each of four subperiod charts.

That second window was framed as a weather-fear-window: a Southern Hemisphere winter frost-risk episode in Brazil, with prices typically easing after freeze fears fade.

The calendar span stayed a research window

The preferred implementation treated the calendar span as a research window only, then applied a three-price-channel breakout procedure inside that span. The overlay used one channel for entry, one for a protective stop, and one for a trailing profit stop.

The same rules included the stand-aside-year case: a year inside the seasonal-window in which the channel-breakout rules generate no position.

Win rate of four orange-juice seasonal tests

The late-February to mid-March long in May orange juice looks nearly automatic at 94.1 percent winners in 1986–2002, then falls to 27.8 percent in 1968–85, so those dates fail a regime split. The June-into-early-July short in September orange juice holds 74.3 percent winners over the full 1968–2002 sample and rises to 83.3 percent when the same span is used only as a window for a three-price-channel breakout. All four figures come from the article’s performance-summary tables.
The late-February to mid-March long in May orange juice looks nearly automatic at 94.1 percent winners in 1986–2002, then falls to 27.8 percent in 1968–85, so those dates fail a regime split. The June-into-early-July short in September orange juice holds 74.3 percent winners over the full 1968–2002 sample and rises to 83.3 percent when the same span is used only as a window for a three-price-channel breakout. All four figures come from the article’s performance-summary tables.May and September orange juice futures · Seasonal windows tested on 1968–2002 history · 1968-01-01T00:00:00.000Z to 2002-12-31T00:00:00.000Z

The channel-breakout test lists five stand-aside years; its 83.3 percent win rate is 25 winners out of 30 trades, not out of 35 calendar years. May and September are different contracts.

Educational research material, not investment advice. Historical source context does not establish present-day performance.
29 of 55 in the Price channel track
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  15. 1993Lead-lag smoothing for weekly trend-channel construction
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  18. 1995Validated trendline and price channel construction
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  44. 2010A multi-timeframe channel from value to an overvalued zone
  45. 2010Asymmetric price channel construction for congested markets
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  47. 2012Constructing adaptive horizontal price channels
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  49. 2015News-sentiment confirmation for support, channel, and volume tests
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  53. 2017Test consolidation channel breakouts as one procedure
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  55. 2025Using IBM's multi-year price channel as a breakout teaching case
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