Using Genetic algorithms and Monte Carlo to price convertible bond

The aim of paper is to use Genetic algorithm and Monte Carlo to price convertible bond with finite maturity. As we known, Monte Carlo is hardly applied to price the derivatives with optimal items. Combined with Genetic algorithm and Cubic sample function, Monte Carlo not only solves the convertible bond with optimal conversion items, but also prices that with long-range dependence property. By evaluating the controlling points of cubic sample function, the optimal convertible boundary is showed. Furthermore, the proposed method can be applied to price derivatives with optimal items, such as American option and optimal investment with muti-risky assets.