Hacking the Uncertainty Principle: Time Frequency
Wavelet convolution is a powerful signal processing tool, used on Sigma-L to examine cycles in markets that are changing in power and frequency over time. We look at some of the key features
Time Frequency Analysis and the FFT
Time frequency analysis and the fast Fourier transform (FFT) are two approaches used to analyse the frequency content of a signal. Financial markets can be thought of as noisy signals, a time series that is assumed to be composed of a number of periodic functions and random components. Time frequency analysis allows for the identification of how a signal's frequency content varies over time, while the static FFT provides a snapshot of a signal's frequency content at a single point in time. The FFT squashes any temporal information out of the final analysis (how a signal is changing over time) and is solely based in the frequency domain.
At the time of writing Profit Magic for Stock Transaction Timing there was huge excitement over the newly established FFT algorithm and it’s application across a great many disciplines. Areas of modern life we take for granted now - the internet, mobile communication, streaming video and much much more, were made poss…