Risk analysis of the stock market by means self-organizing maps model

Abstract

Defining a relationship among companies that belong to the BMEX group in order to provide investors with information, is a help to minimize the risk at the moment of investing. Using data taken from Yahoo finances and BMEX website, a SOM neural network was used to study the daily data of all companies, which belong to the IBEX35 and the Latibex indexes. Companies which are part of the IBEX35, and appear closer between them in the SOM mesh, were compared in profitable terms showing that eminently there exist economic and business line relationship between them. The opposite happened companies selected randomly from the IBEX35 group in some specific cases. Likewise, the companies of Latibex group, were joined to IBEX35 companies to compare a entire year evolution between them. In fact, demonstrating that the model proposes definitely find and shows associations between companies that are near enough, and which belongs to a determinant index in a stock market environment.