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2006issue C081

Intermarket dislocation as context for short-horizon momentum

The archive described a ratio-model and a momentum-model used together when index-to-stock relationships left their usual track. TradersWeek editorial reading treats the two-hour entry as incomplete until that correlation-dislocation is named.

  • The historical process paired a ratio-model of index and stock relationships with a momentum-model that measured how strong a move had become.
  • A correlation-dislocation was treated as a reversible-move-flag: permission to look for a short-horizon turn, not a standalone forecast.
  • Trades were framed on intradaily, daily, and weekly charts, lasted about two hours, and were watched against overnight futures and the European open.
  • Selection favored the formative-stage-instrument, and the same checks were later extended to corn, wheat, oil, and gold.
Entries in this reading3 entries
Current trackCorrelation analysis52 readingsMomentum strategy103 readingsIntermarket analysis136 readings

A two-model process

A two-model process was described. One model analyzes ratio relationships between indexes and stocks. The other examines momentum to measure the strength of a move.

In the vocabulary of this article, those companions are the ratio-model and the momentum-model. The ratio-model judges whether index-to-stock relationships remain intact. The momentum-model then measures how strong a price move is after a relationship has gone off track.

Six years of manual charting of index and stock activity preceded the recognition of technical patterns and the construction of daily indicator-based models.

When a relationship leaves its usual track

The process treats intermarket correlations that appear to leave their usual alignment as a signal that a reversible move may be underway. That break is a correlation-dislocation. The process output is a reversible-move-flag: permission to look for a short-horizon turn rather than a standalone forecast.

Intraday, daily, and weekly charts were used to generate as many as 45 signals per month, with trades lasting about two hours from entry to exit.

Candidates, sessions, and later markets

Candidate selection emphasized instruments still in a formative stage, when a supply of the security could still be obtained at comparatively low prices. That selection target is the formative-stage-instrument.

Daily monitoring included overnight futures activity and the European open in order to judge how overseas trading and higher volatility might affect the U.S. session.

The same techniques were later extended to corn, wheat, oil, and gold after users asked for broader coverage.

Educational research material, not investment advice. Historical source context does not establish present-day performance.
19 of 37 in the Correlation analysis track
20081-6 pp.Next on Correlation analysisMap ordinary 12-month outcomes before stacking valuation, rates, and seasonalityOverlapping 12-month index windows from 1945 through May 2007 averaged an 8.4 percent price change excluding dividends, with a 53.4 percent largest gain, a 41.4 percent largest decline, and fatter tails than the 15.7 percent standard deviation implies.
All readings on this track · 37 readings
  1. 1988Constructing a lead-aware correlation coefficient
  2. 1989A precious-metal price as a changing intermarket equation
  3. 1990Two clocks for copper: a factor regime, a regression baseline, and leftover moving-average timing
  4. 1990Earnings yield, rate correlation and regression for equity value
  5. 1991Name the window, then combine leaders
  6. 1991Constructing a two-market linear correlation check
  7. 1991Constructing a commodity-bond correlation regime filter
  8. 1992Building intermarket context with linear correlation
  9. 1993Inverse-scale overlays as a gold-equity regime filter
  10. 1994Constructing seasonal slots from windows, analog years, and implied volatility
  11. 1995Pin one reference close and roll companion correlations as an overlay
  12. 1995Rolling correlation windows for shifting intermarket regimes
  13. 1998Gold as a cross-market regime barometer
  14. 1999The gold-bond inverse is a regime, not a cause
  15. 1999A nested lag test of gold leading bond yields
  16. 1999Constructing spreads from stock and intermarket correlation
  17. 2000Evaluating headline versus food-and-energy-excluded CPI as bond-yield context
  18. 2005A late EUR/USD fifth wave tested by the Bund-Treasury gap
  19. 2006Intermarket dislocation as context for short-horizon momentum
  20. 2008Map ordinary 12-month outcomes before stacking valuation, rates, and seasonality
  21. 2008A clean-energy theme inside the oil-and-energy regime
  22. 2014Quantitative-easing overlays as fragile belief regimes
  23. 2015Three intermarket checks from the late-2014 crude decline
  24. 2015Basket construction via rank, correlation, and locked rules
  25. 2015Construct a CAD-oil pair from percent-of-range Bollinger maps
  26. 2015CAD/USD and crude: first the correlation, then the band gap
  27. 2017Correlation regime versus moving-average crossover for S&P 500 exposure
  28. 2017Updating intermarket systems after correlation shifts
  29. 2017Constructing a correlation-divergence regime filter for yen and Nikkei context
  30. 2018Clustered negative troughs in an energy-index pairwise correlation
  31. 2018Filter pairwise-correlation before reading an intermarket regime
  32. 2018Moving-average supports in the March 2018 correlation shock
  33. 2020Bond spreads as an equity regime lens
  34. 2020Crash-protection folklore as a correlation regime question
  35. 2020Constructing a bounded correlation-trend-filter
  36. 2020Constructing a correlation-to-line trend filter
  37. 2020Bitcoin correlation regimes across equities and gold
By fieldIntermarket and spreads148 readingsBy year200683 readings
All 52 readings tagged Correlation analysis
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