Re: Fast Fourier Transform (raw)

["Lionel Issen" <lissen@xxxxxxxxx>]

I don't use  Metastock's FFT. The dominant 
cycle always appears to be the length of the displayed data.  Fourier 
transforms give an infinity of solutions. In practice I've rarely had to use 
more than the first 3 frequencies (this was for engineering applications).  
Larry Ehlers sells the MESA software which is supposed to generate the 
dominant cycles better than FFT.
 
Back in the days before PCs 
James Hurst  wrote a book on charting, "The Profit Magic Of Stock 
Transaction Timing". In it he gave a simple graphical manual method for 
determining the dominant cycles. If your local library doesn't have it, you 
might be able to get it on interlibrary loan. 
Lionel Issen<A 
href="mailto:lissen@xxxxxxxxx";>lissen@xxxxxxxxx
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  Sent: Saturday, February 10, 2001 10:28 
  PM
  Subject: Fast Fourier Transform 
  (raw)
  
  Hello,
   
  This question is directed to anyone who has 
  played around with (and preferably understood) MetaStock's Fast Fourier 
  Transform (FFT) built-in indicator...
   
  The FFT indicator can be displayed either as an 
  INTERPRETED plot or as a RAW plot.
   
  The INTERPRETED plot isolates and displays the 
  data's 3 most predominant cycle lengths (displayed on the y-axis in days) and 
  their relative strength (to each other) shown by the proportion of the 
  x-axis the cycle length occupies. Knowing the predominant cycle 
  of a security's price data enables various indicators to be optimised 
  by using the cycle length (or more commonly, half this period) to adjust 
  the indicator's variable(s). The same effect can usually be achieved by 
  simply optimising an indicator.
   
  The RAW FFT plot has me 
  more interested but quite confused. When the RAW option is chosen it 
  displays a plot of the raw data upon which the INTERPRETED plot is 
  based.
   
  Now for the question... What characteristics 
  would this RAW FFT plot of a security's price data have if this data was very 
  predictably cyclic? That is, I'm NOT interested in finding out what 
  the data's predominant cycle is (as given by the INTERPRETED FFT) but how 
  predictably cyclic it is and being able to quantify this relative to other 
  data series. I'm hoping that this might then form the basis for a very 
  valuable exploration that could be used when selecting candidates for 
  application of cycle-based or period reliant indicators.
   
  Any insights into the interpretation of the RAW 
  FFT indicator and ideas for its application would be very much 
  appreciated.
   
  Thanks in advance,
   
  Paul.