A Simulation-Based Pricing Method for Convertible Bonds

Abstract

We propose a pricing model for convertible bonds based on Monte Carlo simulation that is more flexible than previous lattice-based methods because it allows to better capture the dynamics of the underlying state variables. Furthermore, the model is able to deal with embedded American-style put and call features with path-dependent trigger conditions. The simulation method uses parametric representations of the early exercise decisions and consists of two stages. In the first stage, the parameters representing the exercise strategies are optimized on a set of simulated stock prices. Subsequently, the optimized parameters are applied to a new simulation set to determine the model price. In an empirical analysis, the model is found to provide a better fit compared to previous studies.