1990issue C061-9
Year-over-year dominant cycle personality audit
A dominant-cycle model is a moving diagnostic, not a fixed market identity. Rank can flip when quieter contracts wake up, so the histogram peak, the center-of-gravity offset, and the share of days above a cycle-content gate should be re-baselined together before any cycle length is reused.
- A short-term cycle counted as valid only when cycle content, a signal-to-noise ratio, cleared a 6 dB gate, equal to cycle power four times the noise power.
- Useful detections were too few for a formal mean and variance, so the histogram peak was treated as a subjective mode and spread was summarized with a weighted-average center of gravity.
- Average occupancy rose from 1988 to 1989, but ranks flipped: sugar went from least cyclic to most cyclic, former leaders generally held their rates, and only gold sat in both leading clusters.
- Editorial view: re-baseline the histogram peak, the center-of-gravity offset, and the share of days above the cycle-content gate together before any cycle length is reused.
The dominant cycle as a yearly diagnostic
A dominant cycle is the cycle length at the peak of a histogram of above-threshold detections, treated as that market’s cycle personality for the measurement year. Spectral analysis compares cycle power against noise across candidate lengths so occupancy, rank, and personality can be evaluated from one year to the next.
Editorial view: that personality is a moving diagnostic, not a fixed market identity. The archive workflow below shows why the histogram peak, the center-of-gravity offset, and the share of days above a cycle-content gate should be read together.
How a valid cycle was counted
A short-term cycle was counted as valid only when cycle content, a decibel signal-to-noise ratio, exceeded a 6 dB gate. That gate is equivalent to cycle power four times the noise power.
Twelve perpetual futures continuations were scored with a maximum-entropy spectrum, a spectral estimator that extracts short-term cycle content from ordered futures prices over a defined lookback and sampling interval. The scores were tallied into cycle-length histograms expected to form a bell-shaped envelope peaked at the dominant cycle.
When detections are too few for a mean
Useful detections were judged too few for a statistically valid mean and variance. The histogram peak was treated as a subjective mode. Spread was summarized with a center of gravity, a weighted average of observed short-term cycle lengths.
Occupancy rose while ranks flipped
Across the twelve contracts, the average share of time with above-threshold cycles rose from 22.7% in 1988 to 32.5% in 1989. Sugar reversed from the least cyclic contract in 1988, above threshold 13% of the time, to the most cyclic in 1989, above threshold 45% of the time.
Former 1988 occupancy leaders generally held their activity rates but dropped in rank because quieter contracts became more cyclic. Only gold sat in both years’ leading clusters.
A stable offset and uneven personalities
The average center-of-gravity cycle length stayed nearly constant versus the average histogram peak, at 127% of the peak in 1988 and 126% in 1989.
Cycle-personality histograms ranged from a well-behaved statistical pattern in gold to no discernible personality in pork bellies, with less dual-peak harmonic pairing than in earlier years.
Year-to-year occupancy change was uneven. Copper, cocoa, and the Deutschemark swung sharply, wheat held the same cyclic share, and the S&P and Treasury bonds stayed relatively stable.
What to re-baseline before reuse
Editorial view: a contract can keep its occupancy and still lose rank when quieter markets become more cyclic. Gold’s well-behaved histogram and the lack of personality in pork bellies also show that occupancy and personality are not the same reading. Re-baseline the histogram peak, the center-of-gravity offset, and the share of days above the cycle-content gate before any cycle length is reused.
All readings on this track · 28 readings
- 1984Constructing maximum-entropy spectra for dominant-cycle forecasts
- 1984How to construct a maximum-entropy cycle model
- 1984Constructing a maximum-entropy forecast from a chosen lookback
- 1985Constructing period-locked half-cycle and full-cycle averages
- 1986Why Fourier windows limit dominant-cycle resolution
- 1987Assembling short-lookback maximum-entropy cycle forecasts
- 1988Why a fitted dominant cycle is not a forecast
- 1989Evaluating commodity cycle personalities with spectral histograms
- 1989Evaluating next-session cycle forecasts with stops
- 1989Constructing cycle-aged volatility trailing stops
- 1990A channel signal-to-noise gate for dominant-cycle forecasts
- 1990Year-over-year dominant cycle personality audit
- 1991Cyclic entry from a locked dominant-cycle phase
- 1992Stationarity states on synchronized futures spectral contours
- 1997Hidden horizon assumptions in dominant-cycle readings
- 1997When market cycles are absent more than present
- 1997A spectral estimator that retunes indicators to the measured cycle
- 2000Constructing a Hilbert dominant cycle and a maximum-entropy refinement
- 2000Switch trend and cycle indicators after a half-cycle dwell test
- 2000Constructing a dominant-cycle squelch trend filter
- 2000Phasor displays for dominant-cycle construction
- 2002Low-lag trendline from elliptic and dominant-cycle notches
- 2004Spectral peaks are mode diagnostics, not forecasts
- 2004Compressive last-stage oscillator construction
- 2013Constructing trend failure curves from qualified-trend transitions
- 2014Lookback range, a two-lag smoother, and next-bar fills
- 2014Constructing a MESA stochastic with roofing and SuperSmoother filters
- 2016Constructing spectral heatmaps for dominant market cycles