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1991issue C051-5

A two-speed breadth reading for intermediate market direction

The archive workflow states a market-direction view for the coming weeks and months from a 21-day moving average of the breadth-volume-ratio crossing a 55-day moving average of the same series. TradersWeek treats that pair as an intermediate-horizon-filter so individual-issue work starts from a stated tape hypothesis rather than from a fixed 1.00 line.

  • Form a market-direction view for the coming weeks and months before any individual-issue work, on the grounds that a valid stock setup can still fail if the broader tape is deteriorating.
  • Smooth the same breadth-volume-ratio with a 21-day moving average and a 55-day moving average, then change long, short, or flat bias only when those lines produce a moving-average-crossover.
  • Treat a raw print above 1.00 as seller dominance and a print below 1.00 as buyer dominance, then invert that map after smoothing so low moving-average values are overbought and high values are oversold.
  • Use the pair as an intermediate-horizon-filter: look for buys when the reading is bullish, sells when it is bearish, and reduce positions that fight a turn in the tape.
Entries in this reading3 entries
Current trackMoving-average crossover108 readingsMarket breadth120 readingsMoving average449 readings

State the tape before the stock

The described workflow forms a market-direction view for the coming weeks and months before any individual-issue work. The stated ground is that a valid stock setup can still fail if the broader tape is deteriorating.

That first step is an intermediate-horizon-filter: the 21-day versus 55-day relationship is used to state multi-week market direction before stock-level entries, rather than to mark an exact turning day.

Build one series from market-breadth

Market-breadth here is a comparison of advancing versus declining issues and the volume attached to each side. That comparison is written as a breadth-volume-ratio: advances divided by declines, divided by advancing volume divided by declining volume.

A raw reading above 1.00 is treated as seller dominance and a reading below 1.00 as buyer dominance.

Reverse the map after smoothing

Once the series is smoothed, that mapping is reversed, so low moving-average values are treated as overbought and high moving-average values as oversold.

That overbought-oversold-inversion is the rule that same-session low readings of the breadth-volume-ratio are treated as buyer control, while low values of its longer moving averages are treated as buyers having been aggressive for too long.

Plot a faster average against a slower one

A moving-average is a simple arithmetic average over a stated lookback of ordered observations. Here the same breadth-volume-ratio is averaged over 21 days and 55 days so a faster path can be compared with a slower baseline.

The constructed pair is a simple arithmetic 21-day moving average of the breadth-volume-ratio plotted against a simple arithmetic 55-day moving average of the same ratio. The 21-day line is described as the more volatile of the two.

Read bias from the moving-average-crossover

A moving-average-crossover is a directional signal created when a shorter moving average of a series crosses a longer moving average of the same series. Here it turns a repeatable breadth-volume condition into a long, short, or flat market hypothesis.

The stated crossover rule assigns a long bias when the 21-day average is below the 55-day average and a short or flat bias when the 21-day average is above the 55-day average.

Treat labeled crossings as context, not a clock

A labeled example marks short-bias events when the 21-day average rises through the 55-day average at points A, C, and E, and long-bias events when it falls through at points B and D.

Those crossings are presented as an intermediate-horizon context tool that can arrive a few days early or late.

Compare the two averages, not a fixed line

Comparing the 21-day average with the 55-day average, rather than with a fixed 1.00 line, is described as producing earlier state changes because the two averages travel together. The slower line is already nearby when the faster line reverses.

Waiting for the 21-day average to fall through 1.00 at point J is presented as a later confirmation.

Use the pair as a market-direction filter

A later sequence flags a multi-day stretch of opposing crossings as a potential whipsaw zone.

The pair is treated as a market-direction filter: look for buys when the reading is bullish, sells when it is bearish, and treat a turn in that state as a reason to reduce positions that now fight the tape.

Educational research material, not investment advice. Historical source context does not establish present-day performance.
8 of 57 in the Moving-average crossover track
19921-3 pp.Next on Moving-average crossoverA Deutschemark yield map with dual-average and relative-strength timingIntermarket analysis compares pricing elements of two related or inversely related markets, then ordinary technical tools are applied to the Deutschemark and other currencies.
All readings on this track · 57 readings
  1. 1988Constructing moving averages: weights, smoothing and crossovers
  2. 1988Constructing breadth and average trend states
  3. 1989Evaluating an always-in-the-market moving-average crossover
  4. 1989Constructing symmetric market-breadth ratio accumulators
  5. 1989Objective crossover tests of Fibonacci wave ratios
  6. 1990Volume-adjusted moving average construction
  7. 1991Constructing a mechanical crossover on a synthetic price series
  8. 1991A two-speed breadth reading for intermediate market direction
  9. 1992A Deutschemark yield map with dual-average and relative-strength timing
  10. 1992Confirming currency-fund trends with a crossover and a filter
  11. 1992A moving-average slope filter for crossover signals
  12. 1992Occupancy and split-sample tests for average crossovers
  13. 1994Gold-mining seasonality and bond-fund duration switching
  14. 1994Price oscillator from two moving averages
  15. 1995Explicit exponential weights and binary entry filters
  16. 1996Currency futures crossover with slope, bond filter, and stop
  17. 1996Two-market average crossover entry with a fixed stop
  18. 1997Construction of a filtered three-average crossover
  19. 1998Two-group exponential average compression as a trend filter
  20. 1998Constructing r-squared trend filters with dual lookbacks
  21. 1998Moving-average length is a habit, not a secret
  22. 1999Solving the close that triggers a moving-average crossover
  23. 2000Kagi yang and yin control versus crossover noise
  24. 2000Constructing simple moving average crossover filters
  25. 2000Building a vertical-horizontal filter to gate trend signals
  26. 2000Two-average crossover as a check on trend following
  27. 2003Stacked exponential-average retracement entries and extreme stops
  28. 2003Evaluating oscillator thresholds against optimized crossovers
  29. 2004Constructing a semicycle trend-quality filter
  30. 2004Commodity subgroups labeled by crossover, support, or convergence
  31. 2004Full-window evaluation of crossover trend systems
  32. 2004Two-average trend filters as a classroom critique of indicator stacking
  33. 2005Three-layer confirmation from a moving-average cross, candles, and Q-stick
  34. 2005Charting put prices beside an equity breakdown
  35. 2005Range-gated moving-average crossover construction
  36. 2007Anticipating a simple-average crossover with a threshold-close
  37. 2007Anticipating moving-average crossovers one bar ahead
  38. 2007Lead-series moving-average crossovers with a stochastic and relative strength index
  39. 2007Next-bar SMA crossover hypotheses from theoretical crossing values
  40. 2007Anticipating a moving-average crossover before confirmation
  41. 2007A three-horizon moving-average stack as a construction problem
  42. 2007Confirming trend with regression slope and r-squared
  43. 2008Constructing a multi-timeframe smoothed crossover
  44. 2008Best-day clusters versus trend filters
  45. 2008Allied markets as a confirmation gate for crossover and breakout signals
  46. 2008Weekly exponential-average crossover as a mechanical trend case study
  47. 2010Evaluating a 200-day crossover as long, short, and stand-aside rules
  48. 2010Read a 10-and-40 trend on two neighboring time frames
  49. 2012Sampling unit as a first-class parameter on dual simple moving averages
  50. 2012Constructing index-ETF entries from volatility-index persistence
  51. 2013Moving-average baselines versus crossover signals
  52. 2013Constructing a typical-price and heikin-ashi crossover as one mechanical procedure
  53. 2016A three-gate checklist for longs after a sharp drop
  54. 2016Weekly inflation-ratio crossover for commodity regimes
  55. 2017Normalized Laguerre zero-axis warning as a two-marker construction
  56. 2019Range-weighted construction of an adaptive exponential moving average
  57. 2020Construct a second-pullback entry after a moving-average crossover
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All 108 readings tagged Moving-average crossover
Also on Moving-average crossover5 readings
1989Constructing symmetric market-breadth ratio accumulators1988Constructing breadth and average trend states1988Constructing moving averages: weights, smoothing and crossovers1988Five reading rules for smoothed indicator charts1990Volume-adjusted moving average construction