Empirical Likelihood Methods Based on Characteristic Functions With Applications to Lévy Processes
本文利用特征函数发展经验似然方法，用于莱维过程的参数估计、参数类检验（包括跳跃成分存在性）及分布对称性检验，模拟和案例验证了有效性。
Lévy processes have been receiving increasing attention in financial modeling. One distinctive feature of such models is that their character-istic functions are readily available. Inference based on characteristic functions is very useful for studying Lévy processes. By incorporating the recent advances in nonparametric approaches, empirical likelihood methods based on characteristic functions are developed in this paper for parameter estimation, testing a particular parametric class including the presence of a jump component in the Lévy process and testing for symmetry of a distribution. Simulation and case studies confirm the effectiveness of the proposed method. KEY WORDS: Characteristic function; Empirical likelihood; Goodness-of-fit test; Lévy processes. 1.