Chunwei Wang

Prof. Chunwei Wang

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Research Focus & Metrics

Academic Career Length

19Years (2008-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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4 November 2008 in Methodology and Computing in Applied Probability
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CYChuancun Yin
Chuancun Yin
Chunwei WangChunwei Wang
Chunwei Wang

9 July 2008 in Applied Stochastic Models in Business and Industry
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Chunwei WangChunwei Wang
Chunwei Wang
CYChuancun Yin
Chuancun Yin

1 March 2010 in Statistics & Probability Letters
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Chunwei WangChunwei Wang
Chunwei Wang
CYChuancun Yin
Chuancun Yin
ELErqiang Li
Erqiang Li

22 December 2022 in Mathematics
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Chunwei WangChunwei Wang
Chunwei Wang
NDNaidan Deng
Naidan Deng
SSSilian Shen
Silian Shen
In this paper, we study the perturbed risk model with a threshold dividend strategy and proportional investment. The insurance companies are allowed to invest their surplus in a financial market consisting of a risk-free asset and a risky asset in fixed proportions; the risky assets are modeled by the jump-diffusion process. Firstly, using the theory of the stochastic process and stochastic analysis, we obtained the integro-differential equations satisfied by the expected discounted dividend payments and the discounted penalty function. Secondly, we obtained the numerical approximate solutions of the integro-differential equations through the sinc method, since the analytical solutions of them are not easy to obtain, and we found that the error is within a manageable range. Finally, we considered some numerical examples where the claim sizes follow an exponential distribution, a mixture of two exponential distributions or the lognormal distribution in detail, and explored how perturbations and proportional investment affect dividends and ruin probability. Moreover, sensitive analysis showed that the proportion of the risky investment, the diffusion coefficient, the distribution of the claims and the positive jump in the risky assets investment all have explicit impacts on dividends and ruin probability.

1 January 2024 in AIMS Mathematics
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Chunwei WangChunwei Wang
Chunwei Wang
SWShujing Wang
Shujing Wang
JXJiaen Xu
Jiaen Xu
SLShaohua Li
Shaohua Li
In this paper, a classical risk model with liquid reserves and proportional investment is considered, and the expected total discounted dividend before ruin of insurance companies under the threshold dividend strategy is studied. First, the integral differential equations of the expected total discounted dividend before ruin satisfying certain boundary conditions is derived. Second, since the explicit solutions of the equations cannot be obtained, the numerical approximation solutions are obtained by the sinc approximation method. Finally, we discuss the effects of parameters such as risk capital ratio and liquid reserve on the expected total discounted dividend before ruin by some examples.

24 March 2023 in Mathematics
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JXJiaen Xu
Jiaen Xu
Chunwei WangChunwei Wang
Chunwei Wang
NDNaidan Deng
Naidan Deng
SWShujing Wang
Shujing Wang
In this paper, we consider a risk model with two-sided jumps and proportional investment. The upward jumps and downward jumps represent gains and claims, respectively. Suppose the company invests all of its surplus in a certain proportion in two types of investments, one is risk-free (such as bank accounts) and the other is risky (such as stocks). Our aim is to find the optimal admissible strategy (including the optimal dividend rate and the optimal ratio of investment in risky assets), to maximize the dividend value function, and discuss the effects of a number of parameters on dividend payments. Firstly, the HJB equation of the dividend value function is obtained by the stochastic analysis theory and the dynamic programming method, and the optimal admissible strategy is obtained. Since the integro-differential equation satisfied by the dividend value function is difficult to solve, we turn to the sinc numerical method to approximate solve it. Then, the error between the exact solution (ES) and the sinc approximate solution (SA) is analyzed. Finally, the relative error of a special numerical solution and an ES is given, and some examples of sensitivity analysis are discussed. This study provides a theoretical basis for insurance companies to prevent risks better.