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2007issue C031-6

Anticipating a moving-average crossover before confirmation

A 20-day and 30-day simple moving average pair can be rewritten as a next-bar threshold close, so a moving-average-crossover is visible one day before the averages cross. The archive workflow then keeps only probable cross days and treats a cross prediction as a rule-based-entry only when trend-following conditions already hold.

  • A 20-day and 30-day simple moving average pair can be turned into a threshold close that identifies a descending or ascending crossover one day before the averages themselves cross.
  • Requiring the next bar’s return to stay inside twice the extreme one-day return from a long lookback rejects unreachable threshold closes and leaves only a small share of bars as probable cross days.
  • Across the same 100-stock NASDAQ 100 universe, the prediction series led the confirmed-cross series by one day on individual names and on a composite breadth ticker, and most predictions later confirmed.
  • Knowing the prediction at the close of day zero defines an execution window through the next session, but the archive presents that rule-based-entry as a short-horizon trend-following test rather than a congestion trade.
Entries in this reading3 entries

Rewrite the crossover as a threshold close

A moving-average-crossover is a rule that fires when a shorter simple moving average crosses a longer one. In this workflow that cross is the event to anticipate, not the entry itself.

A 20-day and 30-day simple moving average pair can be turned into a next-bar threshold close: the next-session close that would make the shorter and longer simple moving averages meet on the following bar. A cross prediction is a same-day signal that the current close has already crossed that threshold close, which implies a confirmed average cross is expected on the next bar.

Keep only probable cross days

A negative or otherwise unreachable threshold close can be rejected by requiring the next bar’s return to stay inside twice the extreme one-day return observed over a long lookback. That filter leaves only a small share of bars as probable cross days, meaning the implied threshold close still lies inside a realistic next-bar return band so a crossover is possible rather than arithmetically excluded.

On a single-name example using an 800-bar lookback, that realistic-return band implied a next-bar daily-return range of +48% to -26%, and most candles were classified as having no practical chance of a 20/30-day average cross.

A one-day lead on names and breadth

When predicted and confirmed crossovers are counted across the same 100-stock NASDAQ 100 universe, the prediction series leads the confirmed-cross series by one day at the market-breadth level as well as on individual names. A composite breadth ticker is that daily count, across a defined stock universe, of how many names show a predicted or confirmed ascending or descending crossover.

Across the NASDAQ 100 sample, four simple-average pairs produced hundreds to thousands of descending and ascending predictions, with the majority later confirmed and only a small percentage failing in each direction. The 20/30-day pair generated 1772 descending and 1766 ascending predictions, of which 85.79% and 88.09% respectively fell into the leading confirmation bucket reported for that pair. Lengthening the slower average reduced prediction counts, for example to 562 descending and 621 ascending predictions on the 20/100-day pair, while the 50/100-day pair showed the highest leading-confirmation shares at 92.50% descending and 91.76% ascending.

The same test on an indicator

The same threshold-close prediction can be applied after replacing raw close with an indicator series, so a slow and fast moving average of that indicator can be anticipated in the same way as a price-average cross.

CSCO next-bar StochD threshold against the 0–100 band

TC1 is the next-session slow-stochastic print that would force the 20-day and 30-day averages of StochD to cross. It only enters the valid 0–100 band at the two events marked A and B; elsewhere a crossover cannot occur. The last TC1 print (985.6) and the 1300 / −1133 scale ends are the labels on the lower CSCO pane; the rest of the curve was read from that pane.
TC1 is the next-session slow-stochastic print that would force the 20-day and 30-day averages of StochD to cross. It only enters the valid 0–100 band at the two events marked A and B; elsewhere a crossover cannot occur. The last TC1 print (985.6) and the 1300 / −1133 scale ends are the labels on the lower CSCO pane; the rest of the curve was read from that pane.CSCO · daily

The source replaces price with StochD (C1) inside the same 20/30 SMA threshold-close formula. Because StochD cannot print outside 0–100, any TC1 outside that interval is an impossible cross.

Place the entry only in a persistent trend

Knowing the prediction at the close of day zero creates a defined execution window through the next session’s range and the following open, so a rule-based-entry can be placed before the lagging confirmed cross would otherwise fire. That rule-based-entry is an entry, delay, or abstention decision defined by a closed-form next-day close, a realistic-return filter, and whether the predicted cross is later confirmed.

The procedure is presented as a short-horizon trend-following test. Trend-following here only treats predicted and confirmed crossovers as actionable when price is already moving in a persistent direction, and treats congestion as a reason to stand aside. Predicted crossovers can be traded during persistent trends, including with partial orders, but are not described as effective during congestion.

Educational research material, not investment advice. Historical source context does not establish present-day performance.
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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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