In the present we have analyzed the data from 480 companies of the S&P500 using the Random Matrix Theory and the Inverse Participation Ratio, we analyzed the eigenvalues and its respective eigenvectors in order to find structural behaviour in market. We take off the non-random part from the correlation matrix and use the new correlation matrix to calculate the risk for a given portfolio, showing good results as were expected. Also, we give a complex network perspective of the companies, building a network with the Spanning Tree Algorithm, in order to obtain some useful different measure of group behaviour.