A SOCIAL SPIDER ALGORITHM FOR PRICING A FINANCIAL OPTION: A FORWARD APPROACH BY MONTE CARLO SIMULATION

Igor Michel Santos Leite, Grasiele Regina Duarte, Leonardo Goliatt da Fonseca

Resumo


An option is a type of financial derivative that creates an opportunity for a market player to minimise your risk exposure in the negotiation. The main objective is pricing this derivative. The options classified as American is quite challenging to pricing and one of the most popular options considered in the market. This paper proposes the adoption of the Social Spider Algorithm (SSA) to optimise the parameters of the optimal-stopping with the Monte Carlo Simulation (MCS) for pricing the options classified as American. The experiments were performed using a set of options values/characteristic available in the literature. The results showed the accuracy of the combination SSA+MCS when compared with reference values.

Palavras-chave


Options pricing; Stochastic optimisation; Free boundary problem; Monte Carlo Simulation; Social Spider Algorithm

Texto completo:

PDF


DOI: http://dx.doi.org/10.21575/25254782rmetg2020vol5n21173

Apontamentos

  • Não há apontamentos.


Direitos autorais 2020 Igor Michel Santos Leite, Grasiele Regina Duarte, Leonardo Goliatt da Fonseca

Revista Mundi Engenharia, Tecnologia e Gestão ISSN 2525-4782

Qualis: B4 - Interdisciplinar, B5 - Geografia, B5 - Administração Pública e de Empresas, Ciências Contábeis e Turismo, B5 - Comunicação e Informação, B5 - Engenharias III