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1982issue C071-9

Evaluating half-hour crossovers with cycle priors and stops

A historical half-hour design treated a moving-average crossover as a locked long-or-short hypothesis. A Fourier scan nominated the average lengths, the flip rule stayed fixed, and a one-percent stop was then asked whether leftover event risk still broke the bound.

  • The oscillator is the difference between a short and a long moving average of closes, and the stance stays always in the market until the opposite cross.
  • Fourier analysis of half-hour prices nominated moving-average lengths and was not used as a standalone trade signal.
  • A one-percent stop-loss bound was part of the design, and Friday afternoon money-supply releases produced adverse moves larger than that bound.
  • Editorial: the evaluation keeps the flip rule fixed and asks the cycle prior and the stop to do separate jobs.
Entries in this reading3 entries
Current trackFourier analysis41 readingsMoving-average crossover126 readingsStop-loss order297 readings

A locked long-or-short hypothesis

Editorial framing: evaluate the crossover as a locked long-or-short hypothesis. Let a cycle scan nominate average lengths, keep the flip rule fixed, and then ask whether a pre-declared stop still contains leftover event risk. The paragraphs that follow record the historical workflow only.

The always-in-market flip rule

The oscillator is the difference between a short and a long moving average of closes. A long signal is the short average crossing above the long average, and a short signal is the reverse cross.

The rule stays continuously long or short. It is always in the market and reverses only when the short average violates the long-average trend.

Half-hour bars from ten-second quotes

Quotes taken every ten seconds were grouped into half-hour high-low-close bars. The session ran from 9:00 a.m. to 3:15 p.m. Central Time and produced thirteen bars, with the final fifteen minutes treated as one bar.

The same half-hour design was applied to S&P 500 and Value Line futures over 31 May 1983 through 19 August 1983.

Cycle peaks as length priors

A Fourier scan of the half-hour series listed candidate cycles at 16, 17, 18, 25, 32, 36, 42, 51, and 64 periods. A later fast-Fourier pass on the Value Line series placed a major peak at 29.26 periods and a secondary peak at 64 periods.

Average lengths were then set near half the indicated cycle, focusing a 14-to-20-period search band on the Value Line series. Fourier peaks were used as starting values for moving-average lengths rather than as standalone trade signals.

A one-percent stop and leftover event risk

The test design included a one-percent stop-loss bound applied while the crossover position remained open.

Holding through Friday afternoon money-supply releases produced adverse moves larger than that bound.

Value Line Profit Matrix: long, short, and net P&L by line item

A trader should see that the always-in-market half-hour oscillator on Value Line finished the test net positive, with both sides contributing and the 1 percent stop failing to contain a few large leftover losses. Numbers are read from the Profit Matrix Final Report printout, not redrawn from a plot.
A trader should see that the always-in-market half-hour oscillator on Value Line finished the test net positive, with both sides contributing and the 1 percent stop failing to contain a few large leftover losses. Numbers are read from the Profit Matrix Final Report printout, not redrawn from a plot.Value Line stock-index futures · 30-minute bars built from 10-second quotes · 1983-05-31T00:00:00.000Z to 1983-08-19T00:00:00.000Z

One point equals $500. The system stayed through Friday money-supply prints; several losses exceeded the declared 1 percent stop.

Educational research material, not investment advice. Historical source context does not establish present-day performance.
2 of 26 in the Fourier analysis track
19841-10 pp.Next on Fourier analysisBuilding moving-window spectral cycle forecastsEstimate numerical relationships among historical observations first, then apply those parameters to form future values of the same univariate price series.
All readings on this track · 26 readings
  1. 1982Critiquing Fourier, Elliott, and seasonal commodity models
  2. 1982Evaluating half-hour crossovers with cycle priors and stops
  3. 1984Building moving-window spectral cycle forecasts
  4. 1988Fourier cycles versus calendar seasonal regimes
  5. 1989Constructing analog cycle signatures from price lows
  6. 1990Curve fits fail the forecast test
  7. 1991Auditing moving-average length with Fourier spectra
  8. 1991Closed-form phase for dominant-cycle spectra
  9. 1993Evaluating windowed spectral forecasts of index turning points
  10. 1994Window length for moving-window spectral forecasts
  11. 1994Constructing WAMI power and phase spectra
  12. 1994Fourier-tuned momentum filter design
  13. 1994Aliasing, leakage, and dominant-cycle reads from sampled prices
  14. 1995Constructing indicator lookbacks from Fourier spectra
  15. 1996Constructing phase from a dominant-cycle sine and cosine pair
  16. 1999Sinusoidal pseudo-securities for indicator evaluation
  17. 2000Constructing dominant cycle length from Hilbert phase
  18. 2000Constructing adaptive channel breakouts from a measured cycle period
  19. 2005Embedding forex prices into a singular-spectrum forecast basis
  20. 2005Constructing recurrent forecasts from grouped spectral components
  21. 2007Constructing a dominant cycle from transformed Fourier spectra
  22. 2010Why cycle indicators fail when parameters shift
  23. 2019Constructing futures momentum as open-interest-scaled rate of change
  24. 2019Judging a dominant cycle and a trend filter by sample, lag and the move they keep
  25. 2020Constructing futures turnover time and urgency
  26. 2020Stock power ratio as a growth trend filter
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All 41 readings tagged Fourier analysis
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1982Building FFT spectra to size cycle filters1982Critiquing Fourier, Elliott, and seasonal commodity models1984Building moving-window spectral cycle forecasts1984Constructing maximum-entropy spectra for dominant-cycle forecasts1986Why Fourier windows limit dominant-cycle resolution