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2000issue C091-2

Two-average crossover as a check on trend following

A reconstructed trend-following rule and a 20-versus-50 exponential moving-average-crossover were run on 13 large-capitalization stocks from the same start date. Editorial reading treats that simpler crossover as the public rival extra structure still has to face.

  • The reconstructed trend-following rule entered long only after the close had stayed above an instantaneous-trendline for more than half the dominant-cycle, and exited when the close fell below that line.
  • The control was a moving-average-crossover: buy when a 20-day exponential moving average crosses a 50-day exponential moving average, and sell when the close drops below the 50-day average.
  • Both rules used the same 13 large-capitalization stocks from 7 August 1998. The reconstructed test generated 85 trades and the two-average crossover generated 54 trades.
  • Editorial guidance treats published techniques as tools the reader must test on their own instruments and window, and says a tool that fails that test should not be used.
Entries in this reading3 entries
Trend following89 readingsCurrent trackMoving-average crossover108 readingsMoving average449 readings

A reconstructed trend-following rule

A published adaptive trend-following procedure was reconstructed as one entry and exit sequence. A long was taken only after the close had remained above an instantaneous-trendline for more than half the dominant-cycle. The long was closed when the close fell below that trendline.

In this reconstruction, trend-following is a single procedure that stays with direction after a defined persistence test of price versus the trendline. The instantaneous-trendline is the adaptive line the close must hold on the trend side of before a long is accepted. The dominant-cycle is the estimated oscillation length that sets how long that hold must last.

The two-average control

The comparison rule was a moving-average-crossover. It bought when a 20-day exponential moving average crossed a 50-day exponential moving average. It sold when the close dropped below the 50-day average.

Each moving-average is a lookback smoother of closes. Here those smoothers supply both crossover legs and a baseline trend reference. The crossover is the explicit control against the more elaborate trend procedure.

One shared-evaluation-tape

Both rules were run on the same 13 large-capitalization stocks with a shared start date of 7 August 1998. A shared-evaluation-tape is one fixed name list and start date, used so two trend procedures can be compared without changing the sample.

On that shared sample the reconstructed trend-following test generated 85 trades and the two-average crossover generated 54 trades. The evaluation used the simple moving-average-crossover as the baseline procedure against which the more elaborate construction was judged.

Average profit: Ehlers trend rule vs 20/50 EMA crossover

On the same 13 large-cap names from 7 August 1998, the 20-day versus 50-day exponential-average crossover posted higher average profit both per stock (76% vs 69%) and per trade (18.3% vs 10.6%) than the reconstructed Ehlers trend-following rule, and it did so on fewer trades (54 vs 85). These four percentages are the figures Dwight Cook stated in the September 2000 Letters column, not readings from a plotted figure.
On the same 13 large-cap names from 7 August 1998, the 20-day versus 50-day exponential-average crossover posted higher average profit both per stock (76% vs 69%) and per trade (18.3% vs 10.6%) than the reconstructed Ehlers trend-following rule, and it did so on fewer trades (54 vs 85). These four percentages are the figures Dwight Cook stated in the September 2000 Letters column, not readings from a plotted figure.13 large-cap stocks (QCOM and WMI named as range examples) · from 7 August 1998 · 1998-08-07T00:00:00.000Z

Cook chose 13 large-capitalization stocks from 7 August 1998 and noted that big movers such as QCOM lifted the Ehlers averages. The Ehlers rule bought when the close stayed above the instantaneous trendline longer than half the dominant cycle and sold when the close fell below it. The control bought on a 20-day EMA cross of the 50-day EMA and sold when the close dropped below the 50-day EMA.

Educational research material, not investment advice. Historical source context does not establish present-day performance.
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20031-4 pp.Next on Moving-average crossoverStacked exponential-average retracement entries and extreme stopsThe intermediate-term trend in this construction is framed for a planned hold of one to six months and is treated as established only when the 150-day exponential-average slope, the place of the 50-day average above or below that line, and a matching sequence of swing highs and lows coincide.
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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