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Spectrum analysis is often used to analyse waveforms. A common configuration, for example, is to create a graph where X is time, Y is frequency, and the brightness of each position represents amplitude.

Has spectrum analysis ever been used successfully as an indicator to analyse historical price data, for example the price of shares over time?

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Those who say don't know. Those who know don't say. --Lao-tzu, Tao Te Ching (via Pat Burns). – Joshua Ulrich Jan 24 '12 at 18:48
Hmm, sounds like a hammer looking for its nail. – chrisaycock Jan 24 '12 at 18:49
Thanks, it seems the concept has been used before and there are even books on the topic. Thanks as well for the assertion that moving averages are like a low frequency filter. I've marked the most voted answer as correct. – alan2here Jan 30 '12 at 2:18

7 Answers

up vote 5 down vote accepted

I would recommend Marc Wildi's work on signal extraction.

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Singular Spectrum Analysis ( SSA ) is a relatively new technique ( although Lorenz suggested something similar 1956 ) that is starting to be more widely used. The jury is still out on just how much underlying structure, if any, there actually is in financial time series. Nonetheless a very powerful and easy to use data smoothing and filtering/de-noising technique. A very basic Excel and VBA demonstration available here

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Something like a moving average smoother is akin to a low pass filter, the 'stochastics' of technical analysis crudely akin to a band pass filter. Going up the ladder of sophistication, you can see something like http://www.jstor.org/pss/3592665 or applications of wavelet decomposition.

This paper from 1963 by GRANGER, CLIVE W. J., and MORGENSTERN, 0. titled “Spectral Analysis of New York Stock Market Prices,” Kyklos, XVI (January, 1963), I-27 should convince you that people have been more than thinking of applying frequency-domain analysis to this.

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Fractal spectra are covered in Multifractal Volatility: Theory, Forecasting, and Pricing. Also note that your run-of-the-mill moving average of a price series is a low-pass filter (filters out the higher frequencies), and moving averages are very used in basic financial analysis.

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I have considered applying Fourier transforms to smoothed Financial and Econometric data but until someone pays me to do it I don't have time. I haven't seen much coverage in the usual complex analysis texts of usage in Financial markets but that is probably because they are more concerned with physical applications. I am also a bit out of date currently, I still use Whittacker and Watson (1902)!

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How is this useful as an answer? If you had any thoughts on applying Fourier transforms to financial data, outlining your thoughts would be more beneficial than to say you don't have time... just sayin... Financial econometric texts do have chapters devoted to spectral analysis btw. – Vishal Belsare Jan 29 '12 at 15:50

Here is a gentle introduction to wavelet methods.

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Yes. Check out Time-Series Analysis by Shumway and Stoffer. Spectral Analysis and Filtering is covered in Chapter 4.

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