摘要
We proposed a new model to price employee stock options （ESOs）. The model is based on nonparametric statistical methods with market data. It incorporates the kernel estimator and employs a three-step method to modify Black- Scholes formula. The model overcomes the limits of Black-Scholes formula in handling option prices with varied volatility. It disposes the effects of ESOs self-characteristics such as non-tradability, the longer term for expiration, the eady exercise feature, the restriction on shorting selling and the employee＇s risk aversion on risk neutral pricing condition, and can be applied to ESOs valuation with the explanatory variable in no matter the certainty case or random case.
We proposed a new model to price employee stock options (ESOs). The model is based on nonparametric statistical methods with market data. It incorporates the kernel estimator and employs a three-step method to modify Black-Scholes formula. The model overcomes the limits of Black-Scholes formula in handling option prices with varied volatility. It disposes the effects of ESOs self-characteristics such as non-tradability, the longer term for expiration, the early exercise feature, the restriction on shorting selling and the employee’s risk aversion on risk neutral pricing condition, and can be applied to ESOs valuation with the explanatory variable in no matter the certainty case or random case.
基金
Funded by the No. 12 Project of Joint Research Projects of Shanghai Stock Exchange with Chongqing University.
