Abstract
O Desenvolvimento de Novos Produtos (DNP) é considerado como uma atividade fundamental e que possui um impacto relevante no desempenho das empresas. Apesar da relevância do mercado financeiro há uma escassez de trabalhos sobre o desenvolvimento de novos produtos financeiros. O objetivo desta pesquisa é propor o uso dos Algoritmos Genéticos (AG) como um procedimento alternativo para avaliação da combinação mais favorável das variáveis para o lançamento do produto. O estudo almeja: (i) determinar as variáveis essenciais do produto financeiro estudado (fundos de investimento); (ii) determinar como avaliar o sucesso do lançamento de um novo fundo de investimento e (iii) como o AG pode ser aplicado ao problema do desenvolvimento de um novo produto financeiro. O modelo proposto foi testado com o uso de 4 anos de dados reais do mercado financeiro brasileiro e os resultados sugerem que é uma metodologia de desenvolvimento inovadora e útil para o desenho de complexos produtos financeiros com muitos atributos.
Highlights
The multi-attribute product design problem is divided into two groups: (i) a simple product, which involves the launch of a unique product and (ii) a line of products, when many products are launched simultaneously
The proposed framework is divided into two major parts: (i) a product simulator, which involves the main variables and the goals identified during investigation of the product development process and (ii) a market simulator which includes historical scenarios, in extreme and divergent situations, including the product’s life-cycle divided into the launch and maturity periods and with economic turbulence or without it
According to the Basle II Agreement and the risk management procedures adopted by the banks we studied, the value at risk (VAR) of the fund’s daily incomes with a standard deviation σ, an initial investment W0 during a period of time ∆t is given by the following equation (Jorion, 1997):
Summary
The multi-attribute product design problem is divided into two groups: (i) a simple product, which involves the launch of a unique product and (ii) a line of products, when many products are launched simultaneously. Kohli and Krishnamurti (1987, 1989) showed that the market share maximization problem, by introducing new products with multiple attributes and levels, is NP-Hard (high complexity) They proposed and assessed two heuristic approaches: dynamic-programming and shortest-path heuristics. Parallel efforts have been made in the financial area in order to apply intelligent algorithms to financial decisions These efforts have been focused on: (i) portfolio optimization (Crama and Schyns, 2003, Korczak and Lipinski, 2001); (ii) technical trading rules (Allen and Karjalainen, 1999); (iii) financial predictions and insolvency risk (Mckee and Lensberg, 2002, Vareto, 1998) and (iv) investment recommendations (Li and Tsang, 1999, 2000).
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