# Re: FFT of stock market data?

*From*: amit <amit.panda@xxxxxxxxx>*Date*: Wed, 11 Apr 2007 20:38:59 -0400

A couple of things:

1) people do use FFT (or other spectral analysis techniques) to price

series.

2) yes, price series can be non-stationary. for most of the price

series, take log (natural logarithm) of the price series. it remove

seasonality to much extent. more over, a moving average can also be

used to detrend. standard detrend function is not useful here.

3) the problem with FFT is resolution of time periods, what you get.

Moreover, ignore first time-period value (=0), also the first number

after fft is a real number, just the sum of data. thus T(1) = [].

search for Sunspot example on mathworks site, for the simplest

analysis to detect cyclicity.

4) params for FFT: issues like whether to use any filters, whether to

use zeo-padding or data truncation etc etc comes up. For most of the

price series, spectral analysis, with simple fft (without

zero-padding and Filters) works.

5) There is no way to confirm whether the detected (local) peaks of

the spectrum gives to corresponding time periods. They just give you

a hint. Interaction, echos and overtones might be creating peaks on

the spectrum, yet actual data may not contain that period or cycle.

Thus, another Test of significance method is needed.

6) Test of significance: there are tests like F-test, chi-test and

Bartels test to check the significance of a particular cycle/ period

under investigation. Bartels test of the most significant one.

7) alternate ways : wavelett theories, MESA (maximum entropy spectral

analysis) are two other significant schools of ideas for Cycle

research. you might like those ideas too.

There is much more to cycle research before one can think of applying

it for practical trading. People have been working for years (40-50

years) in this area. if i remember correctly, cycle research

foundation and a couple of similar sites provides you more info.

.

**References**:**Re: FFT of stock market data?***From:*Andrew Gentile

**Re: FFT of stock market data?***From:*TreatmentPlant

**Re: FFT of stock market data?***From:*NZTideMan

**Re: FFT of stock market data?***From:*TreatmentPlant

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