In this paper,combining the threshold technique,we reconstruct Nadaraya-Watson estimation using Gamma asymmetric kernels for the unknown jump intensity function of a diffusion process with finite activity jumps.Under ...In this paper,combining the threshold technique,we reconstruct Nadaraya-Watson estimation using Gamma asymmetric kernels for the unknown jump intensity function of a diffusion process with finite activity jumps.Under mild conditions,we obtain the asymptotic normality for the proposed estimator.Moreover,we have verified the better finite-sampling properties such as bias correction and efficiency gains of the underlying estimator compared with other nonparametric estimators through a Monte Carlo experiment.展开更多
基金supported by the National Natural Science Foundation of China(No.11701331)Shandong Provincial Natural Science Foundation(No.ZR2017QA007)+6 种基金Young Scholars Program of Shandong Universitysupported by Ministry of Education,Humanities and Social Sciences project(No.18YJCZH153)National Statistical Science Research Project(No.2018LZ05)Youth Academic Backbone Cultivation Project of Shanghai Normal University(No.310-AC7031-19-003021)General Research Fund of Shanghai Normal University(SK201720)Key Subject of Quantitative Economics(No.310-AC7031-19-004221)Academic Innovation Team(No.310-AC7031-19-004228)of Shanghai Normal University
文摘In this paper,combining the threshold technique,we reconstruct Nadaraya-Watson estimation using Gamma asymmetric kernels for the unknown jump intensity function of a diffusion process with finite activity jumps.Under mild conditions,we obtain the asymptotic normality for the proposed estimator.Moreover,we have verified the better finite-sampling properties such as bias correction and efficiency gains of the underlying estimator compared with other nonparametric estimators through a Monte Carlo experiment.
