Gestão de risco setorial no mercado de ações brasileiro

Abstract

This work analyzes during the period between 2008/01 and 2011/12 the market risk of six sectorial indexes from the São Paulo´s Stock Market (BM&FBovespa): the real state index (IMOB), the eletric power index (IEE), the consumption index (ICON), the industrial sector index (INDX), the financial index (IFNC) and the telecommunications sector index (ITEL). Throughout the Value-at-Risk metric (VaR), four models are estimated. Two of those models are called unconditional, due to its variance: the Unconditional Gaussian VaR, that admits that the returns follow a normal distribution, and the Unconditional Best Fitting VaR, built from the distribution of probabilities that better fits to the returns series. The other two models are called conditionals, assuming that the volatility changes along the time. The GARCH autoregressive models are used to estimate the conditional variance of each index, allowing an estimation of the Unconditional Gaussian VaR and the Unconditional Best Fitting VaR. Afterwards, the VaR models backtestings are realized, revealing the conditional models superiority. Finally, throughout the Balzer´s graphics, the indexes performances were observed over the confrontations between them. It was found that, for the analyzed period, the IEE wins every confrontation against the all other indexes, showing the best relation risk x return. The real state index sector, represented by the IMOB, lost all the confronts.