1990issue C091-3
Crowd questions that switch cycle regimes
A trading-psychology process first asks whether the crowd is posing a direction question or a momentum question. Dominant-cycle and spectral readings then follow only when that question selects a telegrapher regime rather than a diffusion regime.
- Broad technical work can treat price behavior as chaotic, cyclical, patterned, or random rather than as a closed set of chart patterns, ratios, or indicators.
- Non-causal observation studies synthesized price without first requiring a fundamental reason, while the market is described as looking ahead of past fundamental statistics.
- A trading-psychology process treats the crowd's direction question or momentum question as the random variable that selects a diffusion regime or a telegrapher regime.
- Editorial reading: apply a dominant cycle or spectral analysis when the crowd question points to a telegrapher regime, and read a diffusion regime as random or trending.
Price as chaotic, cyclic, patterned, or random
Broad technical work is described as able to treat price behavior as chaotic, cyclical, patterned, or random rather than as a closed set of chart patterns, ratios, or indicators.
A non-causal observation studies what ordered prices did and what they tend to foreshadow without first requiring a fundamental reason for the move. That stance is presented as useful because it lets the observer examine historical price phenomena before assigning a cause.
Traded price is described as synthesized price, the single figure that already combines orthodox value opinions with unmeasurable hopes, fears, moods, needs, and resources. Fundamental statistics are characterized as past history, while the market is described as continuously looking ahead and discounting future developments.
Shared rationale, different descriptions
Different technical disciplines are argued to be alternate descriptions of the same market phenomena, held together by a shared rationale. Dominant-cycle work and spectral analysis are quantitative readings of ordered observations that look for cyclic structure over a defined sampling interval and lookback.
One account maintains that the market is cyclic, meaning non-random, only some of the time. A chaos-theory pivotal branch is interpreted as a split between random and nonrandom regions, or between cyclic activity and trends.
Which question the crowd is asking
A drunkard's-walk setup is said to yield either of two partial differential equations depending on which random variable is selected. Collective trader questions are treated as setting that random variable.
A direction question means enough participants are asking whether the market will rise today. That directional random variable maps to a diffusion regime, the random or trending solution.
A momentum question means enough participants are asking whether the existing trend will continue. That momentum random variable maps to a telegrapher regime, the cyclic or correlated solution.
A trading-psychology process is a testable rule that treats the crowd's shared question as the random variable selecting the current market equation.
All readings on this track · 21 readings
- 1982Spectrum-first construction of moving-average trend filters
- 1990Crowd questions that switch cycle regimes
- 1993Antithetic twins to cancel origin-linked forecast bias
- 1994Constructing frequency response from a three-stage filter cascade
- 1994Bench-testing smoothers with cycle phase and power
- 1995Constructing minimum tradable cycles from spectral noise
- 1995Spectral whipsaw limits for a price-crossing average
- 1996Constructing market phase from dominant-cycle components
- 2000Constructing a Hilbert squelch dominant-cycle gate
- 2007When cycle mode fails: regime gates for spectral trades
- 2008Constructing singular-spectrum forecast baselines
- 2008Stacking a midband cycle gate on a short-memory trend filter
- 2011Engineering spectral cycle detection and moving-average harmony
- 2011Evaluating fixed oscillators against a moving dominant cycle
- 2011A construction checklist for a dominant-cycle sinewave
- 2012Assembling a market-mode heatmap from successive band-pass filters
- 2012Adaptive trend detection from dominant-cycle spectra
- 2015Constructing price paths from cycles and support
- 2018Oscillator distribution shape for mean-reversion filters
- 2020Constructing a cosine-correlation cycle and phasor trend filter
- 2020Constructing a correlation-cycle market-state engine