Confidence Interval Estimation for Right-Tailed Deviation Risk Measures Under Heavy-Tailed Losses
Monchaya Chiangpradit, Sa-aat Niwitpong* Author for corresponding; e-mail address: monchaya_c@hotmail.com
Volume: Vol.38 No.1 (JANUARY 2011)
Research Article
DOI:
Received: 7 June 2010, Revised: -, Accepted: 21 September 2010, Published: -
Citation: Chiangpradit M. and Niwitpong S., Confidence Interval Estimation for Right-Tailed Deviation Risk Measures Under Heavy-Tailed Losses, Chiang Mai Journal of Science, 2011; 38(1): 13-22.
Abstract
The estimation of the price of an insurance risk is a very important actuarial problem. This price has to reflect the property of the distribution of the random variable describing the corresponding loss. If the loss variable has a heavy-tailed distribution (i.e. distribution with an infinite variance) then, the risk measure (as a measure of the risk premium) should be higher. For providing risk measures with heavy-tailed distributions, standard procedures from classical statistics (when the variance is finite) cannot be applied. In this paper we propose confidence interval estimation for the Wang’s right-tailed deviation risk measure for heavy-tailed losses.