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1995issue C041-2

Pin one reference close and roll companion correlations as an overlay

Treat rolling intermarket correlation as a construction problem first. Lock one reference-close, estimate each companion-series over a copied lookback-window, and read the strip against the same contract instead of in isolation.

  • A correlation-coefficient measures the degree and direction of a linear association between two series and is bounded by 1 and -1.
  • Pin every companion estimate to one reference-close so the short market strip stays aligned to the same contract.
  • A 30-session lookback-window copied down the history produces a rolling series rather than a single static reading.
  • A dual-axis-overlay can keep the reference high, low, and close on the primary scale and the rolling coefficients on a secondary scale.
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Current trackCorrelation analysis52 readings

What the coefficient measures

A correlation-coefficient measures the degree and direction of a linear association between two series and is bounded by 1 and -1. Illustrative readings of 0.90, 0, and -0.90 are used to mark a strong same-direction linear link, no linear link, and a strong inverse link.

The coefficient is formed with one series treated as independent and the other as dependent. The same measure can be applied to weekly closes of a stock versus a broad equity benchmark or to daily closes in a multi-market workbook.

Lock a single reference-close

One construction pins every companion correlation to a single Treasury-bond futures closing-price column while storing the date, high, low, and close for that reference contract. Companion-series in the worked sheet cover a dollar index, a commodity index, an equity benchmark, gold, a finance-sector index, and a utility-sector index.

Editorial reading: the sheet is built so a single position can be read against a short companion-market strip, not as an isolated reading.

Copy the lookback-window down the sheet

Each coefficient is estimated over a 30-session lookback-window that is then copied down the history to produce a rolling series. Locking the reference-close column while copying the formula across companion columns keeps every estimate aligned to the same contract.

Place coefficients on a second axis

The reference high, low, and close can occupy the primary price axis while the rolling coefficients occupy a secondary overlay axis. That dual-axis-overlay keeps the contract path and the linkage strip visible together.

Educational research material, not investment advice. Historical source context does not establish present-day performance.
11 of 37 in the Correlation analysis track
19951-8 pp.Next on Correlation analysisRolling correlation windows for shifting intermarket regimesStories that one market moved because another market moved assume a usable intermarket-linkage, yet the same pair can support or contradict that story depending on the window.
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 year199575 readings
All 52 readings tagged Correlation analysis
Also on Correlation analysis5 readings
1988Building consensus indicators with correlation and the chi-square test1988Constructing a lead-aware correlation coefficient1989A precious-metal price as a changing intermarket equation1990Two clocks for copper: a factor regime, a regression baseline, and leftover moving-average timing1990Earnings yield, rate correlation and regression for equity value