Pricing of American Parisian option as executive option based on the least‐squares Monte Carlo approach
研究了一种可用于上市公司激励员工的新型美式双障碍巴黎看涨期权，利用最小二乘蒙特卡洛方法和多种Lévy过程进行定价，发现正态逆高斯过程精度更高，并分析了障碍宽度、窗口长度和行权价对期权价格的影响。
Abstract In this study, we create a novel American double‐barrier Parisian call option contract that may be utilized as an executive option for listed companies to incentivize staff and replace the classic American option. We address the option pricing problem by developing state variables to identify the price state and using the least‐squares Monte Carlo approach. We present several Lévy processes to simulate the movement path of the underlying asset. We discover that geometric Brownian motion and normal inverse Gaussian (NIG) process have successful outcomes, and NIG process has greater calculation accuracy than variance gamma process. The barrier width and window length are positively connected with the price of an American Parisian option, whereas the strike price is negatively correlated with it. Increasing the number of discrete periods of the contract will enhance the pricing accuracy.