An efficient grid lattice algorithm for pricing American-style options

Abstract

Option pricing is an important area of research in the finance community. In this paper, we develop a computationally feasible and efficient lattice algorithm in pricing American-style options. The key idea is to build a time adjusted grid lattice model and afterwards implement backward induction to price options. The time adjusted grid lattice guarantees high accuracy in relatively few discrete finite nodes. To illustrate the performance of the lattice algorithm, European and American options are priced separately, and results are compared to other popular methods in terms of both accuracy and efficiency. All suggest that the proposed lattice algorithm does a better job. Moreover, the fast convergence behaviors of the lattice algorithm as well as the relationship between the converged option price and the number of determination dates are studied as well.