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2016issue C0539-44

Use RSI, MACD, and a moving average as a market-health consensus

A saved multi-filter screener can list names that meet the same criteria on the run date. Editorial reading: count how many names sit at RSI extremes, then require MACD and moving-average agreement before treating the count as a trend-change hypothesis rather than a buy list.

  • A saved multi-filter screener can list names from US equities, OTC issues, indexes, ETFs, and non-SIC stocks that meet the same criteria on the run date.
  • RSI in a high band such as 70 to 90, or a low band below 30, is used here to count how many names sit at that extreme and to track the count over time.
  • MACD and moving averages are companion filters so a single oscillator reading is not used alone as a market-health verdict.
  • Daily scan counts, such as 90 percent of names failing to meet a buy rule, are offered as a spreadsheet-style way to flag a possible downside reversal.
Entries in this reading3 entries
Current trackMACD115 readingsRelative Strength Index186 readingsMoving average449 readings

A saved scan over a defined universe

A saved multi-filter screener can list names from a universe of US equities, OTC issues, indexes, ETFs, and non-SIC stocks that meet the same criteria on the run date. Used here as a proscreener, that scan can be rerun to track how many names still meet the same criteria.

One illustrated four-filter scan returned 10 names that met the stated criteria on the date it was run. Those results could be shown in multiple views, including a performance view.

Returns of the nine names that passed the four-filter ProScreener

These nine tickers are every name that cleared the saved scan on the run date: last price $5–$20, overall strength 90–100, yesterday buy, and overall direction 90–100. Year-to-date and three-month percent changes come from the Performance view of that results table. The spread is the point a trader should take away — Vera Bradley is down more than 20 percent year-to-date while USMD Holdings and South32 are up more than 50 percent — so the output is a criteria snapshot, not a ranked buy list.
These nine tickers are every name that cleared the saved scan on the run date: last price $5–$20, overall strength 90–100, yesterday buy, and overall direction 90–100. Year-to-date and three-month percent changes come from the Performance view of that results table. The spread is the point a trader should take away — Vera Bradley is down more than 20 percent year-to-date while USMD Holdings and South32 are up more than 50 percent — so the output is a criteria snapshot, not a ranked buy list.

The on-screen total is 9 matching names; the magazine text said 10. Per-filter result counts (2,708 last price, 392 overall strength, 530 yesterday buy, 466 overall direction) are independent match totals, not a sequential funnel. One-year and weighted-alpha columns from the same table are omitted.

Count how many names sit at RSI extremes

The relative-strength-index is a lookback oscillator of recent price gains versus losses, used here as a breadth filter that counts how many names sit in a high or low range on a given day. Setting RSI in a 70 to 90 range is presented as a way to count how many names sit in that high band on a given day and then track that count over time for extreme readings.

Add MACD and a moving average as companion filters

MACD is a moving-average-convergence chart condition used with other filters to test whether an RSI-extreme count is also a directional signal. A moving average is a lookback average of ordered prices used as a second confirming forecast layer beside RSI and MACD.

MACD and moving averages are specified as companion filters to RSI so a single oscillator reading is not used alone as a market-health verdict. The combination is using RSI, MACD, and a moving average together so no single filter is treated as a standalone trade trigger.

Editorial reading: a dashboard, not a buy list

Editorial interpretation, not an archive claim: treat the multi-filter equity screener as a market-health dashboard. First count how many names sit at RSI extremes. Then require MACD and moving-average agreement before treating that count as a trend-change hypothesis rather than a buy list.

A market-health consensus is a reading that most names in a scanned universe share the same RSI extreme and also agree on MACD and moving-average direction. The illustrated four-filter scan that returned 10 names shows who met the stated criteria on that date. Editorial interpretation: that short list is not, by itself, the same as a market-health consensus.

Reuse the output and track daily counts

Saved screener output can be reused as an index-style view and then further filtered by trend, volume, sector, and industry. Daily scan counts, such as 90 percent of names failing to meet a buy rule, are offered as a spreadsheet-style way to flag a possible downside reversal.

Editorial interpretation: keep those daily counts as a market-health series. A high fail rate is a reversal hypothesis about the scanned universe, not a ready-made list of trades.

Educational research material, not investment advice. Historical source context does not establish present-day performance.
73 of 80 in the MACD track
20167-7 pp.Next on MACDMACD line versus histogram is a display problem firstMACD is sometimes drawn as a MACD line and sometimes as a MACD histogram, so two charts that share the name may not show the same picture.
All readings on this track · 80 readings
  1. 1988Rebuild MACD-Mo and MACD-H before treating them as signals
  2. 1989Four-span MACD lookbacks as perishable parameters
  3. 1989Weekly then daily MACD confirmation on individual stocks
  4. 1991Regime-gated MACD and stochastic rules inside a checklist
  5. 1991Constructing MACD signal lines and divergence tests
  6. 1991MACD parameter order and cycle phase lag
  7. 1992Lengthened bond MACD as an equity regime filter
  8. 1992Long-horizon MACD construction from paired exponential averages
  9. 1993Constructing a signed ten-point trend filter
  10. 1994Constructing lag-reduced double exponential averages for MACD
  11. 1994Seeding DEMA2 filters to build a MACD signal
  12. 1994Constructing MACD from lag-reduced exponential averages
  13. 1994TEMA1 from nested exponential averages, then a two-horizon MACD
  14. 1994Constructing entry and exit on a relative-strength MACD
  15. 1994Constructing a relative-strength MACD crossover spreadsheet
  16. 1995Consensus presignal filters for Relative Strength Index, MACD and the Stochastic oscillator
  17. 1997Confirm the MACD turn with price, then exit on the histogram
  18. 1997Reconstructing a stochastic oscillator, MACD, and a triple-smoothed oscillator
  19. 1997Moving-average windows before crossovers and MACD
  20. 1999Second-stage MACD on relative-strength inputs
  21. 1999Constructing MACD from exponential-average spreads for crossover and divergence
  22. 1999Coding candlesticks into numeric indicators
  23. 2001Second-low confirmation with a percentage oscillator and money-flow filter
  24. 2001Constructing MACD from exponential average spreads and a signal line
  25. 2002Separate bounded and trend-following oscillator rules
  26. 2002Sort the regime before assigning MACD and stochastic jobs
  27. 2002Building classic divergence filters from RSI and MACD
  28. 2002Weekly highs and lows as trend gates
  29. 2002Constructing channel-normalized Fisher reversal signals
  30. 2002Affine-price and the Fisher transform as a constructed companion to MACD
  31. 2003Regularized EMA construction with a MACD line and a thrust oscillator
  32. 2003Curvature-penalized exponential averages versus MACD
  33. 2003MACD, moving averages, and a trend filter as one timing system
  34. 2003Fractional MACD and linear-regression reversal construction
  35. 2004Weekly MACD-histogram timing of bear-market rallies
  36. 2004Candlestick triggers filtered by MACD divergence
  37. 2004Staging energy-complex tops with trendline, breakout, and MACD
  38. 2005Selling climax holds versus fails
  39. 2006Treat a sideways Wave as permission before a breakout
  40. 2007MACD with a Stochastic oscillator for spotting trend reversals
  41. 2007Rebuilding an S&P 500 fifth-wave count after a broken target
  42. 2007Constructing MACD, RSI, and stochastic confirmation for futures
  43. 2007MACD histogram divergence needs a confirming close
  44. 2007Write the plan as a stack: ratio, boundary, then oscillators
  45. 2008MACD divergence and Stochastic oscillator confirmation on lumber futures
  46. 2008Assign confirmation, timing, and a stop before a currency pair is tested
  47. 2008Confirm the ten-bagger launch path before the MACD exit
  48. 2008Reading the offloaded evidence file
  49. 2008A Leader companion for MACD direction warnings
  50. 2008Relative strength exits with MACD averages and RSI
  51. 2008Assign one job per indicator in a three-screens rule set
  52. 2008Sequencing RSI, MACD, and average crossovers
  53. 2010Constructing the Schaff Trend Cycle from MACD and a dominant-cycle window
  54. 2010Schaff Trend Cycle as a MACD and Stochastic oscillator combination
  55. 2010Combining Relative Strength Index, the stochastic oscillator, and MACD as slope filters
  56. 2010Short-term wave and ratio clues without direction calls
  57. 2010A precise pullback entry and an unplanned profit-protection exit
  58. 2010Filtering MACD false signals with trendline breaks
  59. 2011Vendor feeds as an input variable in a MACD evaluation
  60. 2012Out-of-the-money versus in-the-money option sensitivity to implied volatility
  61. 2012MACD window tuning as hold-time control
  62. 2012Combining a moving-average crossover with MACD and support-resistance
  63. 2012Testing a published MACD entry with a histogram and signal-line agreement filter
  64. 2012Treat sample systems as a lab before live rules
  65. 2013Constructing moving averages and MACD from one price series
  66. 2013The next-bar price that forces a MACD signal-line cross
  67. 2013Constructing next-bar MACD reversal prices
  68. 2013Constructing inverted MACD reversal prices
  69. 2014Shared-filter combinations of the stochastic oscillator, MACD, and RSI
  70. 2014Square-root lookbacks for combined MACD and RSI
  71. 2015Audit open interest and trend before trusting oscillator crossovers
  72. 2016MACD without a signal line, confirmed by moving-average trend filters
  73. 2016Use RSI, MACD, and a moving average as a market-health consensus
  74. 2016MACD line versus histogram is a display problem first
  75. 2017Weekly and daily MACD on a single daily chart
  76. 2017Weekly and daily MACD as a stacked momentum filter
  77. 2017Nested weekly and daily MACD from paired EMA spreads
  78. 2018Weekly and daily PPO scale versus MACD, with bounded RSI and stochastic readings
  79. 2018Constructing a weekly and daily percentage price oscillator
  80. 2020Constructing Wyckoff tape reading with MACD, moving-average, and RSI filters
By fieldIndicators and filters682 readingsBy year201678 readings
All 115 readings tagged MACD
Also on MACD5 readings
2002Constructing channel-normalized Fisher reversal signals2008Assign one job per indicator in a three-screens rule set2008Relative strength exits with MACD averages and RSI2020Constructing Wyckoff tape reading with MACD, moving-average, and RSI filters1995Consensus presignal filters for Relative Strength Index, MACD and the Stochastic oscillator