Finding subgroups in stock market using the Affinity Propagation model

Affinity Propagation is a clustering algorithm that doesn't require a number of clusters to be specified beforehand. Because of its generic nature and simplicity of implementation, it has found a lot of applications in many fields. It finds out representative clusters, called exemplars, using a technique called message passing. It starts by specifying the measures of similarity that need to be considered. It simultaneously considers all training data points as potential exemplars. It then passes messages between the data points until it finds a set of exemplars.

The message passing happens in two alternate steps, called responsibility and availability. Responsibility refers to the message sent from members of the cluster to candidate exemplars, indicating how well suited the data point would be as a member of this exemplar's cluster. Availability refers to the message sent from candidate exemplars...