论文标题
关于$π$ - 选项的模拟定价的注释
Note on simulation pricing of $π$-options
论文作者
论文摘要
在这项工作中，我们调整了Broadie和Glasserman（1997）引入的一种蒙特卡洛算法，以定价$π$ - 选择。此方法基于由离散化和复制基础资产价格的可能轨迹复制产生的模拟价格树。结果，该算法会随着树木深度的增加而产生的下限和上限。在特定的参数化下，这种$π$ - 选项与相对最大抽吸有关，可以在室内市场环境中使用，以保护投资组合免受波动和意外的价格下跌。我们还提供了一些数值分析。
In this work, we adapt a Monte Carlo algorithm introduced by Broadie and Glasserman (1997) to price a $π$-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 $π$-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.
