摘要：In this work, we adapt a Monte Carlo algorithm introduced by Broadie and Glasserman in 1997 to price a inline-formulamath display="inline"semanticsmiπ/mi/semantics/math/inline-formula-option. This method is based on the simulated price tree that comes from discretization and replication of possible trajectories of the underlying asset’s price. As a result, this algorithm produces the lower and the upper bounds that converge to the true price with the increasing depth of the tree. Under specific parametrization, this inline-formulamath display="inline"semanticsmiπ/mi/semantics/math/inline-formula-option is related to relative maximum drawdown and can be used in the real market environment to protect a portfolio against volatile and unexpected price drops. We also provide some numerical analysis.
