Access the full text.
Sign up today, get DeepDyve free for 14 days.
M. Kendall, A. Stuart (1979)
The Advanced Theory of Statistics, Vol. 2: Inference and Relationship
D. Beech, M. Kendall, A. Stuart (1962)
The Advanced Theory of Statistics. Volume 2: Inference and Relationship.Applied statistics, 11
Zellner A. (1990)
10.1007/978-1-349-20865-4_4
This article outlines a subjective approach to estimating value at risk VaR and its related confidence intervals based on priors of the profitloss distribution and its parameters. In the tradition of Bayesian statistics, this produces probability density functions for VaR that allow for subjective uncertainty. The author shows that implementing this approach can be intuitive, straightforward, and applicable to any parametric VaR. One of the more difficult issues in this area is how to assess the precision of estimates VaR estimation is usually straightforward, but estimating a confidence interval for a VaR estimate is not. This article suggests that, by inferring VaR from prior beliefs, rather than thinking of VaR as dependent on an objective PL distribution, interpreting estimated confidence intervals is less problematic
The Journal of Risk Finance – Emerald Publishing
Published: Mar 1, 2000
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.