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).