Bandpass cycle models cannot promise certainty

What the filter makes visible

Spectral analysis reads an ordered price series as frequency parts such as wavelength, phase, and amplitude rather than as an opaque chart. Each frequency component is the part of that series that can be represented as a cycle.

A bandpass filter emphasizes an intermediate frequency band and rejects high and low frequencies. The passband is the band of frequencies the filter transmits most efficiently. The usual construction applies a low-pass filter and then a high-pass filter.

Questions the cycle model does not answer

A spectral cycle model does not identify when or why the relative amplitude of important cycles will change, a shift that can move a market from trending to cycling. The dominant cycle is only the cycle treated as most important in the current state.

The same model does not report how much supply or demand sits at a defending price line.

Because of the in-bar noise assumption, bar range is treated as purely noise. The model does not say how much of the current high-to-low movement is signal.

Confirmation adds free choices

A defending price line is a discrete price level used as a clear confirmation source instead of a stack of possibly dependent indicators. A consensus built from several indicators can rest on signal sources that are not independent.

Adding extra confirmation sources increases degrees of freedom and makes a valid backtest harder and more time-consuming.

Forecasts stay probabilistic

After describing wavelength, phase, amplitude, noise, lag, and defending price lines, forecasts remain probabilistic. Those probabilities are obtained through backtesting rather than certainty.