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

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SUMMARY

The discussion focuses on applying the Fourier Transform (FT) to original signals derived from moving averages in Python. Participants emphasize that a moving average acts as a lowpass digital filter, which may affect the analysis if the FT is applied to the filtered signal instead of the original. The consensus is that applying FT to the original signal yields more effective analysis for backtesting and comparing signals. Clarification on the characteristics of the signals is necessary for more tailored advice.

PREREQUISITES
  • Understanding of Fourier Transform and Fast Fourier Transform (FFT)
  • Knowledge of moving averages as lowpass digital filters
  • Proficiency in Python programming
  • Familiarity with signal processing concepts
NEXT STEPS
  • Research the implementation of Fourier Transform in Python using libraries like NumPy
  • Explore the characteristics of signals and their impact on Fourier analysis
  • Learn about the effects of lowpass filtering on signal analysis
  • Investigate backtesting methodologies for signals in financial analysis
USEFUL FOR

Data scientists, quantitative analysts, and Python developers interested in signal processing and financial analysis will benefit from this discussion.

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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