Option Pricing for a Jump-Diffusion Model with General Discrete Jump-Size Distributions
提出一个封闭解公式，用于在一般跳跃扩散模型下对欧式期权定价，该模型可纳入任意离散跳跃大小分布（包括非参数分布），能更好捕捉实际数据中的尖峰特征，且易于实现、收敛快速。
We obtain a closed-form solution for pricing European options under a general jump-diffusion model that can incorporate arbitrary discrete jump-size distributions, including nonparametric distributions such as an empirical distribution. The flexibility in the jump-size distribution allows the model to better capture leptokurtic features found in real-world data. The model uses a discrete-time framework and leads to a pricing formula that is provably convergent to the continuous-time price as the discretization is increased. The solution is easy to implement with fast convergence properties. Numerical results illustrate the efficiency and accuracy of the proposed model and highlight its robustness and flexibility. This paper was accepted by Noah Gans, stochastic models and simulation.