Hands-On Machine Learning for Algorithmic Trading

Independent Component Analysis

Independent Component Analysis (ICA) is another linear algorithm that identifies a new basis on which to represent the original data, but pursues a different objective to PCA.

ICA emerged in signal processing, and the problem it aims to solve is called blind source separation. It is typically framed as the cocktail party problem, in which a given number of guests are speaking at the same time so that a single microphone would record overlapping signals. ICA assumes there are as many different microphones as there are speakers, each placed at different locations so as to record a different mix of the signals. ICA then aims to recover the individual signals from the different recordings.

In other words, there ...