Abstract
In almost all documented applications, the normal-based Lugannani and Rice (1980) formula provides an extremely accurate approximation to tail probabilities. However, it would be wrong to conclude that this formula is always reliable. In the present paper, we consider an example, the first passage time of a random walk with drift, in which the overall performance of the normal-based Lugannani and Rice formula is rather poor. In contrast, a modified Lugannani and Rice formula, in which the normal base is replaced by an inverse Gaussian base, gives an excellent approximation. A similar modification of Barndorff-Nielsen's (1986) formula is also considered. The main focus of this paper is on a detailed study of the approximations in the extreme right tail of the distribution, and our theoretical results go some of the way towards explaining the observed numerical behaviour. However, on closer scrutiny, there is a disconcerting lack of correspondence between some of the theoretical limits and the numerical results, which appears to be due to convergence rates of some quantities being extremely slow.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.