A new lattice-based scheme for swing option pricing under mean-reverting regime-switching jump–diffusion processes

Abstract

Swing options are complex path-dependent contracts, granting their holders a prefixed number of transaction rights to buy/sell a variable amount of the underlying asset (e.g. energy commodities) subject to daily or periodic constraints. Stating the swing option price as the solution of a stochastic optimal control problem, we employ a dynamic programming formulation in which the underlying asset price is modeled by a mean-reverting regime-switching jump–diffusion process. We explore a newly devised lattice-based pricing framework to find the premium of swing options in a cost-effective and easily implementable manner. We compare the performance of the proposed tree building procedure with a simulation-based Least-Squares Monte-Carlo (LSM) approach.