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2007issue C031-10

Lead-series moving-average crossovers with a stochastic and relative strength index

Two unequal simple moving averages can be inverted into a lead series so a close that intersects that series is a predicted cross and the later change of order is confirmation. This archive article isolates that implied lead and asks, as an editorial question, whether running the same lead on a stochastic oscillator and reading relative strength index as a second oscillator clock changes when the hypothesis is allowed to fire.

  • Two unequal simple moving averages invert into a lead series: a close that meets the lead series is a predicted cross, and the later change of order is the confirmed cross.
  • Each bar can be labelled unlikely, probable soon, expected on the next bar, or already confirmed by comparing the lead series with the close and with an unlikely band built from long-lookback one-bar rate-of-change extremes.
  • The same lead-and-confirm steps can run on a stochastic oscillator so the forecast is an oscillator-versus-lead intersection and confirmation is the later cross of two averages of that stochastic.
  • Crossover anticipation is meant to sit with a slow stochastic and with relative strength index, not to replace those oscillators.
Entries in this reading3 entries

Inverting two averages into a lead series

A moving-average crossover is a signal formed when a shorter simple moving average and a longer simple moving average change order. The archive workflow inverts those two unequal averages into a lead series: the one-bar-ahead close implied by the pair, used to time a predicted cross.

A predicted cross is the bar when price or an oscillator first intersects the lead series. A confirmed cross is the later bar when the two moving averages themselves change order.

Implementations default the shorter average and the longer average on both price and oscillator series, so the same lengths are used whether the lead series is built from price or from an oscillator.

Classifying each bar

Each bar can be classified as unlikely, probable soon, expected on the next bar, or already confirmed. The class depends on where the lead series sits versus the close and versus bands built from recent one-bar rate-of-change extremes.

The unlikely band is a zone around the close built from a long lookback of one-period rate-of-change extremes, scaled into coefficients around the close. A lead series outside those coefficients is treated as an implausible cross.

A probable-soon state requires four conditions at once: the lead series sits inside the likely band, there is no current prediction or confirmation, more than a short span of bars has passed since the last confirmed cross, and a signed comparison of the lead series with the close is in place.

The same construction on a stochastic

The same lead-and-confirm construction can be applied to a stochastic oscillator. That oscillator is bounded: it locates the close inside a lookback high-low range and then smooths that location. The forecast then becomes a stochastic-versus-lead intersection, and confirmation is the later cross of two moving averages of that stochastic.

Relative strength index is a bounded oscillator of average up versus down closes over a defined lookback. In the archive workflow, crossover anticipation is usable together with a slow stochastic and with relative strength index rather than as a standalone replacement for those oscillators.

Scoring predictions and a universe composite

Prediction tallies are scored by whether confirmation arrives on the same bar, after a short delay, or not within a short window.

A universe composite is a daily tally of how many names in a defined list show a prediction or a confirmed cross. In the archive workflow, those composite counts showed the prediction series leading the confirmed-cross series, and that lead was treated as a market-wide property.

Educational research material, not investment advice. Historical source context does not establish present-day performance.
38 of 57 in the Moving-average crossover track
20071-5 pp.Next on Moving-average crossoverNext-bar SMA crossover hypotheses from theoretical crossing valuesA dualLookbackPair of 20-bar and 30-bar simple moving averages can be inverted into a theoreticalCrossingValue, the reconstructed reading at which the two averages would meet.
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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