Tail Probabilities of Randomly Weighted Sums of Random Variables with Dominated Variation

2006 ◽  
Vol 22 (2) ◽  
pp. 253-272 ◽  
Author(s):  
Dingcheng Wang ◽  
Qihe Tang
Keyword(s):  
Random Variables ◽  
Weighted Sums ◽  
Tail Probabilities ◽  
Sums Of Random Variables ◽  
Dominated Variation ◽  
Randomly Weighted Sums

scholarly journals On the Kesten-type inequality for randomly weighted sums with applications to an operational risk model

Filomat ◽  
2021 ◽  
Vol 35 (6) ◽  
pp. 1879-1888
Author(s):  
Yishan Gong ◽  
Yang Yang ◽  
Jiajun Liu
Keyword(s):  
Value At Risk ◽  
Risk Model ◽  
Cell Model ◽  
Type Inequality ◽  
Random Variables ◽  
Operational Risk ◽  
Weighted Sums ◽  
Asymptotic Formulas ◽  
Tail Probabilities ◽  
Randomly Weighted Sums

This paper considers the randomly weighted sums generated by some dependent subexponential primary random variables and some arbitrarily dependent random weights. To study the randomly weighted sums with infinitely many terms, we establish a Kesten-type upper bound for their tail probabilities in presence of subexponential primary random variables and under a certain dependence among them. Our result extends the study of Chen [5] to the dependent case. As applications, we derive some asymptotic formulas for the tail probability and the Value-at-Risk of total aggregate loss in a multivariate operational risk cell model.

Sign in / Sign up

Export Citation Format

Share Document