Empirical likelihood methods based on characteristic functions with applications to lévy processes
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Detail(s)
Original language | English |
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Pages (from-to) | 1621-1630 |
Journal / Publication | Journal of the American Statistical Association |
Volume | 104 |
Issue number | 488 |
Publication status | Published - Dec 2009 |
Externally published | Yes |
Link(s)
Abstract
Lévy processes have been receiving increasing attention in financial modeling. One distinctive feature of such models is that their characteristic 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. © 2009 American Statistical Association.
Research Area(s)
- Characteristic function, Empirical likelihood, Goodness-of-fit test, Lé, Vy processes
Bibliographic Note
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Citation Format(s)
Empirical likelihood methods based on characteristic functions with applications to lévy processes. / Chan, Ngai Hang; Chen, Song Xi; Peng, Liang et al.
In: Journal of the American Statistical Association, Vol. 104, No. 488, 12.2009, p. 1621-1630.
In: Journal of the American Statistical Association, Vol. 104, No. 488, 12.2009, p. 1621-1630.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review