The ruin probabilities of a discrete-time risk model with dependent insurance and financial risks

DOI10.1016/J.JMAA.2016.05.047zbMath1342.91018OpenAlexW2420514447MaRDI QIDQ530309

Rongfei Liu, Ding Cheng Wang

Publication date: 29 July 2016

Published in: Journal of Mathematical Analysis and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmaa.2016.05.047

zbMATH Keywords

asymptotic estimateruin probabilityheavy taildependent insurance and financial risk

Mathematics Subject Classification ID

Asymptotic distribution theory in statistics (62E20) Applications of statistics to actuarial sciences and financial mathematics (62P05)

Related Items (8)

Tails of higher-order moments of sums with heavy-tailed increments and application to the Haezendonck-Goovaerts risk measure ⋮ Extensions of Breiman's theorem of product of dependent random variables with applications to ruin theory ⋮ On the evaluation of ruin probabilities in a generalized dual binomial risk model using Markov property ⋮ On the ruin probabilities in a discrete time insurance risk process with capital injections and reinsurance ⋮ Expectation of the truncated randomly weighted sums with dominatedly varying summands ⋮ The finite-time ruin probability of a discrete-time risk model with GARCH discounted factors and dependent risks ⋮ Tails of higher-order moments with dominatedly varying summands ⋮ The finite-time ruin probability of a discrete-time risk model with subexponential and dependent insurance and financial risks

Cites Work

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• Precise estimates for the ruin probability in finite horizon in a discrete-time model with heavy-tailed insurance and financial risks.
• Finite-time ruin probability with an exponential Lévy process investment return and heavy-tailed claims
• Uniform asymptotic estimates for ruin probabilities of renewal risk models with exponential Lévy process investment returns and dependent claims
• Tail Probabilities of Randomly Weighted Sums of Random Variables with Dominated Variation

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