Randomly weighted sums of dependent subexponential random variables with applications to risk theory

DOI10.1080/03461238.2017.1329160zbMath1396.62021OpenAlexW2618324891MaRDI QIDQ4585942

Fengyang Cheng, Dong Ya Cheng

Publication date: 11 September 2018

Published in: Scandinavian Actuarial Journal (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03461238.2017.1329160

zbMATH Keywords

subexponential distributionsruin probabilitiesconditional dependencerandomly weighted sumsinsurance and financial risks

Mathematics Subject Classification ID

Asymptotic distribution theory in statistics (62E20)

Related Items (13)

Randomly weighted sums of conditionally dependent and dominated varying-tailed increments with application to ruin theory ⋮ Uniform asymptotics for a non standard renewal risk model with CLWD heavy-tailed claims ⋮ The finite-time ruin probability of the nonhomogeneous Poisson risk model with conditionally independent subexponential claims ⋮ Tails of higher-order moments of sums with heavy-tailed increments and application to the Haezendonck-Goovaerts risk measure ⋮ Uniform asymptotics for the finite-time ruin probability of a generalized bidimensional risk model with Brownian perturbations ⋮ A note on randomly weighted sums of dependent subexponential random variables ⋮ A Kesten-type inequality for randomly weighted sums of dependent subexponential random variables with applications to risk theory* ⋮ Asymptotic finite-time ruin probabilities for a bidimensional delay-claim risk model with subexponential claims ⋮ Asymptotic finite-time ruin probabilities in a dependent bidimensional renewal risk model with subexponential claims ⋮ Tails of higher-order moments with dominatedly varying summands ⋮ A Kesten-type bound for sums of randomly weighted subexponential random variables ⋮ Tail probability of randomly weighted sums of dependent subexponential random variables with applications to risk theory ⋮ Tail asymptotics of randomly weighted sums of dependent strong subexponential random variables

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