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1987issue C041-2

Evaluating weekly price cycles with autocorrelation cutoffs

Historical weekly-close work kept a cycle candidate only after price autocorrelation was positive and chi-square exceeded 3.84. A 22-week lag and a 23-week lag cleared that cutoff. Editorial reading then asks whether a 22-week dominant-cycle plus a 13-week seasonal grid organizes lengths already listed by independent studies.

  • A weekly lag was kept only when price autocorrelation was positive and chi-square exceeded 3.84, the stated 95 percent chi-square-cutoff.
  • A 22-week weekly-close-lag produced a chi-square of 12.61, and a 23-week lag in the same weekly-close series also cleared the 95 percent threshold.
  • Most price and volume auto- and cross-correlations in that series were near random, with only a few highly significant chi-square values at scattered lags.
  • A 22-week period was treated as a possible fundamental cycle, with harmonics placed on a 13-week seasonal grid next to independently listed lengths from 3 weeks through 234 weeks.
Entries in this reading3 entries

A two-gate reading of weekly cycle evaluation

Editorial framing presents the archive workflow as a two-gate test. A weekly-close-lag is kept only after an autocorrelation-test finds positive price dependence and the associated chi-square clears a predeclared chi-square-cutoff. The second gate asks whether one dominant-cycle, read with seasonal-analysis on a 13-week grid, can organize the same lengths that independent historical studies already listed.

An autocorrelation-test is a quantitative-model check on ordered price, volume, or breadth observations. It measures dependence at a chosen lag and compares that result with an explicit statistical baseline over a defined sampling interval and lookback. The weekly-close-lag is the spacing, in weeks, between paired closing observations used as a proxy for cyclic length.

The first gate is a chi-square-cutoff

Candidate weekly cycles were retained only when price autocorrelation was positive and the associated chi-square exceeded 3.84, the stated 95 percent cutoff. A 22-week price-to-price lag produced a chi-square of 12.61, well above that 3.84 cutoff. A 23-week lag in the same weekly-close autocorrelation also cleared the 95 percent threshold.

The same research series had found most price and volume auto- and cross-correlations near random, with only a few highly significant chi-square values at scattered lags.

The second gate uses a dominant-cycle and seasonal-analysis

A dominant-cycle step isolates a standout period from ordered market observations so a candidate length can be compared with a baseline and with other reported periods. A 22-week period was treated as a possible fundamental cycle whose harmonics sit near several of the independently listed lengths.

Seasonal-analysis is a portfolio-and-market-context lens that places a single period inside a weeks-to-months regime map. Here it asks whether one short cycle and its harmonics organize a broader grid of listed lengths. Possible cycle lengths were listed as multiples of 13 weeks and aligned against cycle lengths reported in earlier independent studies.

A consensus of the compared studies clustered near 234, 222, 212, 178, 156, 78, 65, 52, 39, 25-26, 12-13, 9-10, 6-7, and 3 weeks. Earlier cycle work had highlighted a 25-26 week period, whereas this weekly-close autocorrelation highlighted 22 and 23 weeks in that same band.

Editorial note: the archive records the cutoff, the two retained lags, and the comparison grid. It does not claim that 22 or 23 weeks replace the 25-26 week highlight. It only shows that both sit in the same band and that a 13-week seasonal grid can be used to organize the listed family of lengths.

Weekly cycle lengths on the 13-week seasonal grid

Independent weekly-cycle claims sit close to both the 13-week seasonal multiples and Tarkany’s 22-week harmonic family, which is the second gate of the cycle test. Every point is a length copied from the Figure 1 comparison table; range cells such as 25–26 and 12–13 weeks are omitted so each series stays single-valued.
Independent weekly-cycle claims sit close to both the 13-week seasonal multiples and Tarkany’s 22-week harmonic family, which is the second gate of the cycle test. Every point is a length copied from the Figure 1 comparison table; range cells such as 25–26 and 12–13 weeks are omitted so each series stays single-valued.DJIA · weekly

Tarkany kept a lag only when price autocorrelation was positive and chi-square exceeded the 95 percent cutoff of 3.84. He also reported a 22-week chi-square of 12.61. Paired Tarkany cells (234 and 237, 39 and 43, 22 and 23) are omitted rather than averaged.

Educational research material, not investment advice. Historical source context does not establish present-day performance.
1 of 15 in the Autocorrelation test track
19881-5 pp.Next on Autocorrelation testSerial correlation is not an independence testA serial correlogram is a pairing grid: each price is matched to another at a stated lag and the matching cell is incremented.
All readings on this track · 15 readings
  1. 1987Evaluating weekly price cycles with autocorrelation cutoffs
  2. 1988Serial correlation is not an independence test
  3. 1988Event-triggered chi-square tests for jittered serial links
  4. 1988Reverse the rule before you trust the system
  5. 1990Chi-square evaluation of lagged breadth correlations
  6. 1990Two-gate out-of-sample tests for trading rules
  7. 1990Sign-cell correlation, chi-square checks, and lag shifts
  8. 1998Test serial dependence before you optimize a mechanical system
  9. 2003How a one-rank rotation is constructed for an offset autocorrelation check
  10. 2004Constructing first-order residual autocorrelation tests
  11. 2004A two-stage Durbin-Watson residual screen
  12. 2011Constructing trend labels from increment correlation atoms
  13. 2012Overnight versus daytime return evaluation
  14. 2012Constructing a multi-horizon folded-correlation reversal filter
  15. 2016Tuning indicators to measured market cycles
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