Bias Free Threshold Estimation for Jump Intensity Function
| Autor: | Yu-ping Song, Zhen-wei Li, Yi-wei Lin |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Applied Mathematics
05 social sciences Monte Carlo method Nonparametric statistics Estimator Asymptotic distribution Intensity function 01 natural sciences 010104 statistics & probability Diffusion process 0502 economics and business Jump Applied mathematics Threshold estimation 0101 mathematics 050205 econometrics Mathematics |
| Zdroj: | Applied Mathematics-A Journal of Chinese Universities. 34:309-325 |
| ISSN: | 1993-0445 1005-1031 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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