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2003issue C121-2

Recursive and cascaded moving-average construction

A simple moving average can be written as an explicit windowed mean, then rebuilt with a compact recurrence and with cascaded finite-impulse stages. Matching transfer responses shows those constructions implement the same average.

  • A simple moving average of length N adds N observations, divides by N, and repeats that construction on each new bar.
  • A compact recurrence builds a long simple moving average from the new observation, the observation delayed by N, and the previous average, then scales that combination by N+1.
  • A three-stage cascade with delays of 1, 2, and 4, then divided by 8, expands to the same eight-term finite-impulse polynomial as an eight-bar simple moving average.
  • The recursive and cascaded constructions are offered as coding simplifications for indicators and strategies that use these averages.
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Write the windowed baseline first

A simple moving average of length N is constructed by adding N observations and dividing by N, then repeating that construction on each new bar. That moving average is a lookback mean of ordered price, volume, or breadth observations, and it is the explicit quantitative baseline being reconstructed.

Writing every delayed term of a long moving average by hand becomes cumbersome, and looped summation is not available in every construction environment. A rolling construction can drop the oldest observation and add the newest one, but that shortcut still requires computing the full-length average at least once to initialize.

Unit delay and transfer response

A unit delay represents a one-bar lag. It is the one-step lag operator that shifts an observation by a single sampling interval.

A filter transfer response is defined as the filter output divided by the filter input. That ratio is used to prove that two constructions implement the same average.

An eight-bar simple moving average has a finite-impulse transfer response equal to the current observation plus the seven preceding delayed observations, all divided by 8. A finite-impulse-response filter outputs a finite combination of the current input and a fixed set of delayed inputs, with no leftover dependence on its own past outputs once the window is written out.

Rebuild with a recursive update

A compact recurrence builds an arbitrarily long simple moving average from the new observation, the observation delayed by N, and the previous average, then scales that combination by N+1. That recursive average update replaces a full-window sum with the new observation, the observation leaving the window, and the previous average.

Exponential smoothing is a recursive smoother that carries memory by folding the previous output into the new estimate, so a long lookback does not have to be summed term by term.

Cascade short finite-impulse stages

Finite-impulse stages can be cascaded so each stage filters the previous stage output. Cascading corresponds to multiplying the stage transfer responses. That cascaded construction builds one longer finite-impulse average by feeding each short stage into the next.

A three-stage cascade with delays of 1, 2, and 4, then divided by 8, expands to the same eight-term finite-impulse polynomial as an eight-bar simple moving average.

Coding simplifications

The recursive and cascaded constructions are offered as coding simplifications for indicators and strategies that use these averages.

Educational research material, not investment advice. Historical source context does not establish present-day performance.
7 of 10 in the Finite Impulse Response Filter track
20061-7 pp.Next on Finite Impulse Response FilterOne second-order transfer function, a family of trend filtersA discrete linear filter is specified as a transfer function: the ratio of output to input written as polynomials in the delay operator Z.
All readings on this track · 10 readings
  1. 1982An odd-length smoother from a cycle cutoff
  2. 1989Smoothing filters, cutoff, poles, and sample delay
  3. 1992Constructing a cycle-aware finite impulse response detrender
  4. 2002Rebuild a smoother by writing the lag into the coefficients
  5. 2002Timing market cycles with finite impulse response filters and FFT
  6. 2002Constructing the relative strength index with an even-order finite-impulse-response prefilter
  7. 2003Recursive and cascaded moving-average construction
  8. 2006One second-order transfer function, a family of trend filters
  9. 2019Constructing the Voss line from a bandpass and a short FIR sum
  10. 2020Truncated bandpass construction as a finite-length trend filter
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