I Can the Fourier transform be applied to moving averages with Python?

AI Thread Summary
The discussion centers on applying the Fourier transform (FT) to signals derived from moving averages for analysis and backtesting. Participants question the effectiveness of using FT on lowpass filtered signals versus the original signals. The original poster clarifies their intent to analyze the Fourier transform of the original signal for better insights. There is a call for more specific details regarding the characteristics of the signals in question to facilitate more targeted assistance. Overall, the conversation emphasizes the importance of clarity in defining the signals and the analysis goals.
herchell
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I would like to compare and backtest these signals by applying Fourier transform to the signals received from moving averages. I would be very pleased if you could share your opinions and suggestions on this issue.
 
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Welcome to PF.

Can you say more about "these signals"? What are their characteristics? And when you do a moving average on a signal, that is basically a lowpass digital filter that you are applying. Do you really want a FT (or FFT) of this lowpass filtered signal, or do you want to FT the original signal?
 
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berkeman said:
Welcome to PF.

Can you say more about "these signals"? What are their characteristics? And when you do a moving average on a signal, that is basically a lowpass digital filter that you are applying. Do you really want a FT (or FFT) of this lowpass filtered signal, or do you want to FT the original signal?
I want the fourier transform of the original signal. Wouldn't that be more effective for analysis?
 
herchell said:
these signals
herchell said:
the original signal
herchell said:
the signals received from moving averages

:welcome:

Perhaps you could be a bit more specific about what exactly you have and what you want to do. Now we have to guess how to help you .

##\ ##
 
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