You are not currently logged in.
Access your personal account or get JSTOR access through your library or other institution:
If You Use a Screen ReaderThis content is available through Read Online (Free) program, which relies on page scans. Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Precise Large Deviations for the Prospective-Loss Process
Kai W. Ng, Qihe Tang, Jiaan Yan and Hailiang Yang
Journal of Applied Probability
Vol. 40, No. 2 (Jun., 2003), pp. 391-400
Published by: Applied Probability Trust
Stable URL: http://www.jstor.org/stable/3215798
Page Count: 10
Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Preview not available
In this paper, we propose a customer-arrival-based insurance risk model, in which customers' potential claims are described as independent and identically distributed heavy-tailed random variables and premiums are the same for each policy. We obtain some precise large deviation results for the prospective-loss process under a mild assumption on the random index (in our case, the customer-arrival process), which is much weaker than that in the literature.
Journal of Applied Probability © 2003 Applied Probability Trust