Exact lower bounds on the exponential moments of truncated random variables
Document Type
Article
Publication Date
6-1-2011
Abstract
Exact lower bounds on the exponential moments of min(y,X) and X 1{X < y } are provided given the first two moments of a random variable X. These bounds are useful in work on large deviation probabilities and nonuniform Berry-Esseen bounds, when the Cramér tilt transform may be employed. Asymptotic properties of these lower bounds are presented. Comparative advantages of the so-called Winsorization min(y,X) over the truncation X 1{X < y} are demonstrated. An application to option pricing is given. © Applied Probability Trust 2011.
Publication Title
Journal of Applied Probability
Recommended Citation
Pinelis, I.
(2011).
Exact lower bounds on the exponential moments of truncated random variables.
Journal of Applied Probability,
48(2), 547-560.
http://doi.org/10.1239/jap/1308662643
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/13150