Abstract
In this paper, supposing that the price process of the risky asset is described by a CEV stochastic volatility model, we investigate a stochastic differential investment and proportional reinsurance game problem with delay between two competing insurers. Each insurer’s risk process is described by the diffusion approximated process of the classical Cramér-Lundberg model. Each insurer can purchase the proportional reinsurance to mitigate their claim risks; and can invest in one risk-free asset and one risky asset whose price dynamics follows the CEV model. The main objective of each insurer is to maximize the utility of his terminal surplus relative to that of his competitor. For the representative cases of the mean-variance utility and exponential utility, we derive the explicit equilibrium reinsurance and investment strategies by applying the techniques of differential game theory and stochastic control theory. Finally, we perform some numerical examples to illustrate the influence of model parameters on the equilibrium reinsurance and investment strategies. Numerical simulation results indicate that: whether delay information and the elasticity parameter is considered or not will greatly affect the final equilibrium reinsurance strategy and optimal investment strategy. The more value of wealth at an earlier time is considered, the insurer will be more cautious and rational in their investment; however, the investment strategy of the insurer with the relative performance concern is riskier than that without the concern; meanwhile, the elasticity parameter will significantly affect the investment strategy of the insurer, and its influence trend varies with the price of risky assets.
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All data generated during the current study are available from the corresponding author on reasonable request.
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Funding
This work is supported by the National Natural Science Foundation of China (No.72171056), National Social Science Foundation of China (No.21FJYB025), Guangdong Basic and Applied Basic Research Foundation (No. 2023A1515012335).
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Appendices
Appendix A
Proof of Theorem 2.  To solve (19)–(22), we try to conjecture the solutions in the following forms
with the boundary conditions \(A^i(T) = F^i(T) = 1\), \(B^i(T) = G^i(T) = 0\), and \(C^i(t,s) = H^i(t,s) = 0\). Substituting (48) with its partial derivatives into (19) and (21), we get
and
By differentiating (49) with respect to \(q_i\) and \(u_i\), we obtain
Substituting (51) back into (49) and (50), and conditionally on \(\varphi _i =\omega _i\mathrm {e}^{-\delta _ih_i}\), the following equations hold:
and
With the condition of \(\beta _1 + \omega _1 = \beta _2 + \omega _2\) in Theorem 2, and separating the variables with \(\left( \hat{x}_i + \omega _iy_i - \kappa _i\omega _jy_j\right)\), we obtain
Considering the boundary conditions, we have
To solve (58), we assume that \(H_i(t,s)\) admits the following affine form:
when substituting M(t) and N(t) into (58), we have
Matching coefficients yields
and
Recalling the boundary conditions, we can obtain
Similiarly, we can get that \(C_i(t, s)\) is a solution of the linear ordinary differential equations, which admits the form in (29).
Moreover, the time-consistent Nash equilibrium reinsurance-investment strategy of insurer i should satisfy
From (67), we can get explicit expressions for the equilibrium reinsurance and investment strategy of each insurer as displayed in (25) and (26).
The proof of Theorem 2 is completed.
Appendix B
Proof of Theorem 3.
To solve HJB Eq. (37), consider the following Ansatz:
with \(R_i(T) = 1\), \(O_i(T) = 0\) and \(\tilde{C}_i(T, s) = 0\), for all \(s \in \mathbb {R}\). By some simple calculation, we obtain the partial derivatives of \(W_i\), which are shown as follows
Inserting (68) and (69) into (37) yields
By differentiating (70) with respect to \(q_i\) and \(u_i\), we obtain
Substituting (71) back into (70), we obtain
With the condition of \(\beta _1 + \omega _1 = \beta _2 + \omega _2\) in Theorem 3, we can further get
By separating the variables with and without \(\left( \hat{x}_i + \omega _iy_i - \kappa _i\omega _jy_j\right)\), we can derive the following equations:
Considering the boundary conditions, we have
Substituting \(u_i^*(t)\) in (71) into the Eq. (76), we have
To solve (79), we assume that \(\tilde{C}_i(t,s)\) admits the following affine form:
when substituting \(\tilde{M}(t)\) and \(\tilde{N}(t)\) into (79), we have
Matching coefficients yields
and
Recalling the boundary conditions, we can obtain
Plugging \(R_i(t)\) and \(C_i(t,s)\) into (71) implies
From (85), the desired expressions of the Nash equilibrium strategies are given by (41) and (42).
This completes the proof of Theorem 3.
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Bin, N., Zhu, H. & Zhang, C. Stochastic Differential Games on Optimal Investment and Reinsurance Strategy with Delay Under the CEV Model. Methodol Comput Appl Probab 25, 54 (2023). https://doi.org/10.1007/s11009-023-10009-2
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DOI: https://doi.org/10.1007/s11009-023-10009-2