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A Multinomial Approximation Approach for the Finite Time Survival Probability Under the Markov-modulated Risk Model
by
Li, Jingchao
, Nie, Ciyu
, Su, Bihao
, Wei, Zhenghong
in
Algorithms
/ Approximation
/ Laplace transforms
/ Mathematical analysis
/ Monte Carlo simulation
/ Probability
/ Reinsurance
/ Risk
/ Survival
2022
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A Multinomial Approximation Approach for the Finite Time Survival Probability Under the Markov-modulated Risk Model
by
Li, Jingchao
, Nie, Ciyu
, Su, Bihao
, Wei, Zhenghong
in
Algorithms
/ Approximation
/ Laplace transforms
/ Mathematical analysis
/ Monte Carlo simulation
/ Probability
/ Reinsurance
/ Risk
/ Survival
2022
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Do you wish to request the book?
A Multinomial Approximation Approach for the Finite Time Survival Probability Under the Markov-modulated Risk Model
by
Li, Jingchao
, Nie, Ciyu
, Su, Bihao
, Wei, Zhenghong
in
Algorithms
/ Approximation
/ Laplace transforms
/ Mathematical analysis
/ Monte Carlo simulation
/ Probability
/ Reinsurance
/ Risk
/ Survival
2022
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A Multinomial Approximation Approach for the Finite Time Survival Probability Under the Markov-modulated Risk Model
Journal Article
A Multinomial Approximation Approach for the Finite Time Survival Probability Under the Markov-modulated Risk Model
2022
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Overview
In this paper, we consider the problem of computing different types of finite time survival probabilities for a Markov-Modulated risk model and a Markov-Modulated risk model with reinsurance, both with varying premium rates. We use the multinomial approximation scheme to derive an efficient recursive algorithm to compute finite time survival probabilities and finite time draw-down survival probabilities. Numerical results show that by comparing with MCMC approximation, discretize approximation and diffusion approximation methods, the proposed scheme performs accurate results in all the considered cases and with better computation efficiency.
Publisher
Springer Nature B.V
Subject
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