Otimização estocástica de portfólio

• Autor(a) principal: Pereira, Yuri Marques Medeiros
• Data de Publicação: 2016
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Repositório Institucional do FGV (FGV Repositório Digital)
• Texto Completo: http://hdl.handle.net/10438/16969
• topic: Controle estocástico; Otimização de portfólio; Equação de Hamilton-Jacobi-Bellman (HJB); Função utilidade; Balanceamento de investimentos com risco; Rebalanceamentos sucessivos; Fundos de índice (ETF); Economia; Processo estocástico; Investimentos; Administração de risco

In Øksendal (1998), we can see the derivation of a classical stochastic optimization between an asset, or a class of assets, risky and other risk-free. But, after the decision of which portion of the resources to allocate in the risky investment class, questions arise about how would the division of the resources between the assets that comprise it. We assume that some investor choose to invest in two risky assets and, following the classic studies of portfolio stochastic optimization, mainly by Øksendal, the proposal is to introduce a new technique of trading consisting in recurrent rebalancing approach stochastic optimization investments with risk. Following the short-term concept provided by Ang, Hodrick, Xing and Zhang (2006) for the stock market, it was considered a sequence of short rebalancing time horizons and, at the beginning of each period, the parameters are recalculated and a new optimal control is established. By adopting this technique, the volatilities of the assets constituting the portfolio are recalculated and, therefore, it is a proxy to solution of the heteroscedasticity problem. Also noteworthy, being something new in literature, the fact of having been derived from an optimal control for a portfolio containing two investments with risk. The stochastic optimization procedure was similar to that adopted by Øksendal, namely, the application of the Hamilton-Jacobi-Bellman theorem to transform the problem of minimizing the cost functional a partial differential equation known as HJB equation, in reference to the authors. The steps followed by Øksenal are the same for us, from the optimization’s point of view, and are well summarized by Ross (2008).