Option pricing using Particle Swarm Optimization

ABSTRACT

Option pricing is one of the challenging areas of computational finance. In this paper an attempt is made to apply Particle Swarm Optimization (PSO) for pricing options. PSO is one of the novel global search algorithm based on swarm intelligence. It is shown that PSO could be effectively used for single variate option pricing problem. The results are compared with standard classical Black-Scholes model for simple European options. With the current understanding from these initial experiments we suggest various avenues for further exploration.

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.8 Problem Solving, Control Methods, and Search
          Subjects: Heuristic methods

General Terms:
Economics, Performance

Keywords:
Black-Scholes, computational finance, option pricing, particle swarm optimization, swarm intelligence