  In this paper we present a mathematical model for collaborative filtering
implementation in stock market predictions. In popular literature collaborative
filtering, also known as Wisdom of Crowds, assumes that group has a greater
knowledge than the individual while each individual can improve group's
performance by its specific information input. There are commercially available
tools for collaborative stock market predictions and patent protected web-based
software solutions. Mathematics that lies behind those algorithms is not
disclosed in the literature, so the presented model and algorithmic
implementation are the main contributions of this work.
