Title: Simulation-Based Valuation and Counterparty Exposure Estimation of American Options
Abstract: Valuing American options is a central problem in option pricing since the early-exercise feature is very common among financial or insurance derivatives products. For high-dimensional American options, Monte Carlo simulation is generally regarded as the only viable approach to price them, and this is the focus of our work. We propose a new regression-based Monte Carlo algorithm for pricing American options. This method typically generates an upper bound of the option value. It is computationally efficient and generates accurate price estimates.