V.17:5 (199-208): The Endpoint Fast Fourier Transform System by Dennis Meyers, Ph.D.

V.17:5 (199-208): The Endpoint Fast Fourier Transform System by Dennis Meyers, Ph.D.
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The Endpoint Fast Fourier Transform System

Last time, we explored the Fourier transform, a mathematical technique for analyzing data to determine cyclical component. This time, we use the fast Fourier transform as a trend determinant for a model for trading the Standard & Poor’s 500.

In my previous article, “The Discrete Fourier Transform Illusion,” we demonstrated the misuses of the Fourier transform mathematical technique as applied to the Standard & Poor’s 500 index. We showed how fitting the Fourier transform to the S&P 500 index data series produced a perfect curve-fit on past data, giving the illusion that this technique would predict the major turning points of the S&P 500. However, when we examined the Fourier transform on a day-by- day walk-forward basis, this seemingly wondrous predictive capability disappeared. This time, we will demonstrate how to use Fourier transform using the computational algorithm called the fast Fourier transform (FFT) on a walk-forward basis on the S&P 500 continuous futures contract (SP).

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