American Institute of Mathematical Sciences

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doi: 10.3934/jimo.2020051

Optimal mean-variance reinsurance in a financial market with stochastic rate of return

Yingxu Tian 1, , Junyi Guo 2, and  Zhongyang Sun 3,,

1. 

College of Science, Civil Aviation University of China, Tianjin 300300, China
2. 

School of Mathematical Sciences, Nankai University, Tianjin 300071, China
3. 

School of Statistics, Qufu Normal University, Qufu, Shandong 273165, China

* Corresponding author: Zhongyang Sun

Received  June 2019 Revised  December 2019 Published  March 2020

In this paper, we investigate the optimal investment and reinsurance strategies for a mean-variance insurer when the surplus process is represented by a Cramér-Lundberg model. It is assumed that the instantaneous rate of investment return is stochastic and follows an Ornstein-Uhlenbeck (OU) process, which could describe the features of bull and bear markets. To solve the mean-variance optimization problem, we adopt a backward stochastic differential equation (BSDE) approach and derive explicit expressions for both the efficient strategy and efficient frontier. Finally, numerical examples are presented to illustrate our results.

Keywords: Investment-reinsurance strategy, Rate of investment return, Ornstein-Uhlenbeck process, Backward stochastic differential equation, Efficient frontier.
Mathematics Subject Classification: Primary: 93E20; Secondary: 91B30, 91G80.
Citation: Yingxu Tian, Junyi Guo, Zhongyang Sun. Optimal mean-variance reinsurance in a financial market with stochastic rate of return. Journal of Industrial & Management Optimization, doi: 10.3934/jimo.2020051
References:
[1]

P. Azcue and N. Muler, Optimal reinsurance and dividend distribution policies in the Cramér Lundberg model, Mathematical Finance, 15 (2005), 261-308.  doi: 10.1111/j.0960-1627.2005.00220.x.  Google Scholar

[2]

S. Asmussen, B. Højgaard and M. Taksar, Optimal risk control and dividend distribution policies: Example of excess-of loss reinsurance for an insurance corporation, Finance and Stochastics, 4 (2000), 299-324.  doi: 10.1007/s007800050075.  Google Scholar

[3]

N. Bäuerle, Benchmark and mean-variance problems for insurers, Mathematical Methods of Operations Research, 62 (2005), 159-165.  doi: 10.1007/s00186-005-0446-1.  Google Scholar

[4]

L. H. Bai and H. Y. Zhang, Dynamic mean-variance problem with constraint risk control for the insurers, Mathematical Methods of Operations Research, 68 (2008), 181-205.  doi: 10.1007/s00186-007-0195-4.  Google Scholar

[5]

C. Bender and M. Kohlmann, BSDEs with Stochastic Lipschitz Condition, Universität Konstanz, Fakultät für Mathematik and Informatik, 2000. Google Scholar

[6]

J. N. Bi and J. Y. Guo, Optimal mean-variance problem with constrained controls in a jump-diffusion financial market for an insurer, Journal of Optimization Theory and Applications, 157 (2013), 252-275.  doi: 10.1007/s10957-012-0138-y.  Google Scholar

[7]

J. N. Bi, Z. B. Liang and F. J. Xu, Optimal mean-variance investment and reinsurance problems for the risk model with common shock dependence, Insurance: Mathematics and Economics, 70 (2016), 245-258.  doi: 10.1016/j.insmatheco.2016.06.012.  Google Scholar

[8]

T. R. Bielecki, H. Q. Jin, S. R. Pliskaz and X. Y. Zhou, Continuous-time mean-variance portfolio selection with bankruptcy prohibition, Mathematical Finance, 15 (2005), 213-244.  doi: 10.1111/j.0960-1627.2005.00218.x.  Google Scholar

[9]

S. Browne, Optimal investment policies for a firm with a random risk process: Exponentional utility and minimizing the probability of ruin, Mathematics of Operations Research, 20 (1995), 937-958.  doi: 10.1287/moor.20.4.937.  Google Scholar

[10]

F.J. Fabozzi and J. C. Francis, Mutual fund systematic risk for bull and bear markets: An empirical examination,, Journal of Finance, 34 (1979), 1243-1250.  doi: 10.1111/j.1540-6261.1979.tb00069.x.  Google Scholar

[11]

W. H. Fleming and H. M. Soner, Controled Markov Processes and Viscosity Solutions, Second edition. Stochastic Modelling and Applied Probability, 25. Springer, New York, 2006.  Google Scholar

[12]

M. Kobylanski, Backward stochastic differential equations and partial differential equations with quadratic growth, The Annals of Probability, 28 (2000), 558-602.  doi: 10.1214/aop/1019160253.  Google Scholar

[13]

X. Li, X. Y. Zhou and A. E. B. Lim, Dynamic mean-variance portfolio selection with no-shorting constraints, SIAM Journal on Control and Optimization, 40 (2002), 1540-1555.  doi: 10.1137/S0363012900378504.  Google Scholar

[14]

Z. B. Liang, K. C. Yuen and J. Y. Guo, Optimal proportional reinsurance and investment in a stock market with Ornstein-Uhlenbeck process, Insurance: Mathematics and Economics, 49 (2011), 207-215.  doi: 10.1016/j.insmatheco.2011.04.005.  Google Scholar

[15]

A. E. B. Lim, Mean-variance hedging when there are jumps, SIAM Journal on Control and Optimization, 44 (2005), 1893-1922.  doi: 10.1137/040610933.  Google Scholar

[16]

A. E. B. Lim, Quadratic hedging and mean-variance portfolio selection with random parameters in an incomplete market, Mathematics of Operations Research, 29 (2004), 132-161.  doi: 10.1287/moor.1030.0065.  Google Scholar

[17]

H. M. Markowitz, Portfolio selection, Journal of Finance, 7 (1952), 77-91.   Google Scholar

[18]

R. C. Merton, Theory of rational option pricing, The Bell Journal of Economics and Management Science, 4 (1973), 141-183.  doi: 10.2307/3003143.  Google Scholar

[19]

E. Pardoux and A. Rǎşcanu, Stochastic Differential Equations, Backward SDEs, Partial Differential Equations, Stochastic Modelling and Applied probability, 69. Springer, Switzerland, 2014. doi: 10.1007/978-3-319-05714-9.  Google Scholar

[20]

R. Rishel, Optimal portfolio management with partial observation and power utility function, Stochastic Analysis, Control, Optimization and Applications, Systems Control Found. Appl., Birkhäuser Boston, Boston, MA, (1999), 605–619.  Google Scholar

[21]

H. Schmidli, On minimizing the ruin probability by investment and reinsurance, The Annals of Applied Probability, 12 (2002), 890-907.  doi: 10.1214/aoap/1031863173.  Google Scholar

[22]

Y. Shen, Mean-variance portfolio selection in a complete market with unbounded random coefficients, Automatica J. IFAC, 55 (2015), 165-175.  doi: 10.1016/j.automatica.2015.03.009.  Google Scholar

[23]

Y. Shen and Y. Zeng, Optimal investment-reinsurance strategy for mean-variance insurers with square-root factor process, Insurance: Mathematics and Economics, 62 (2015), 118-137.  doi: 10.1016/j.insmatheco.2015.03.009.  Google Scholar

[24]

Y. Shen, X. Zhang and T. K. Siu, Mean-variance portfolio selection under a constant elasticity of variance model, Operations Research Letters, 42 (2014), 337-342.  doi: 10.1016/j.orl.2014.05.008.  Google Scholar

[25]

Z. Y. Sun, Upper bounds for ruin probabilities under model uncertainty, Communications in Statistics-Theory and Methods, 48 (2019), 4511-4527.  doi: 10.1080/03610926.2018.1491991.  Google Scholar

[26]

Z. Y. Sun and J. Y. Guo, Optimal mean-variance investment and reinsurance problem for an insurer with stochastic volatility, Mathematical Methods of Operations Research, 88 (2018), 59-79.  doi: 10.1007/s00186-017-0628-7.  Google Scholar

[27]

Z. Y. Sun and X. P. Guo, Equilibrium for a time-inconsistent stochastic linear-quadratic control system with jumps and its application to the mean-variance problem, Journal of Optimization Theory and Applications, 181 (2019), 383-410.  doi: 10.1007/s10957-018-01471-x.  Google Scholar

[28]

Z. Y. Sun, K. C. Yuen and J. Y. Guo, A BSDE approach to a class of dependent risk model of mean-variance insurers with stochastic volatility and no-short selling, Journal of Computational and Applied Mathematics, 366 (2019), 112413, 21 pp. doi: 10.1016/j.cam.2019.112413.  Google Scholar

[29]

Z. Y. Sun, X. Zhang and K. C. Yuen, Mean-variance asset-liability management with affine diffusion factor process and a reinsurance option, Scandinavian Actuarial Journal, (2019), DOI: https://doi.org/10.1080/03461238.2019.1658619. doi: 10.1080/03461238.2019.1658619.  Google Scholar

[30]

Z. Y. Sun, X. X. Zheng and X. Zhang, Robust optimal investment and reinsurance of an insurer under variance premium principle and default risk, Journal of Mathematical Analysis and Applications, 446 (2017), 1666-1686.  doi: 10.1016/j.jmaa.2016.09.053.  Google Scholar

[31]

Z. W. Wang, J. M. Xia and L. H. Zhang, Optimal investment for an insurer: the martingale approach, Insurance: Mathematics and Economics, 40 (2007), 322-334.  doi: 10.1016/j.insmatheco.2006.05.003.  Google Scholar

[32]

H. L. Yang and L. H. Zhang, Optimal investment for an insurer with jump-diffusion risk process, Insurance: Mathematics and Economics, 37 (2005), 615-634.  doi: 10.1016/j.insmatheco.2005.06.009.  Google Scholar

[33]

J. M. Yong and X. Y. Zhou, Stochastic Controls: Hamilton Systems and HJB Equations, Applications of Mathematics (New York), 43. Springer-Verlag, New York, 1999. doi: 10.1007/978-1-4612-1466-3.  Google Scholar

[34]

M. Zhang and P. Chen, Mean-variance asset-liability management under constant elasticity of variance process, Insurance: Mathematics and Economics, 70 (2016), 11-18.  doi: 10.1016/j.insmatheco.2016.05.019.  Google Scholar

[35]

X. Y. Zhou and D. Li, Continuous-time mean-variance portfolio selection: A stochastic LQ framework, Applied Mathematics and Optimization, 42 (2000), 19-33.  doi: 10.1007/s002450010003.  Google Scholar

[36]

X. Y. Zhou and G. Yin, Markowitz's mean-variance portfolio selection with regime switching: A continuous-time model, SIAM Journal on Control and Optimization, 42 (2003), 1466-1482.  doi: 10.1137/S0363012902405583.  Google Scholar

show all references

References:
[1]

P. Azcue and N. Muler, Optimal reinsurance and dividend distribution policies in the Cramér Lundberg model, Mathematical Finance, 15 (2005), 261-308.  doi: 10.1111/j.0960-1627.2005.00220.x.  Google Scholar

[2]

S. Asmussen, B. Højgaard and M. Taksar, Optimal risk control and dividend distribution policies: Example of excess-of loss reinsurance for an insurance corporation, Finance and Stochastics, 4 (2000), 299-324.  doi: 10.1007/s007800050075.  Google Scholar

[3]

N. Bäuerle, Benchmark and mean-variance problems for insurers, Mathematical Methods of Operations Research, 62 (2005), 159-165.  doi: 10.1007/s00186-005-0446-1.  Google Scholar

[4]

L. H. Bai and H. Y. Zhang, Dynamic mean-variance problem with constraint risk control for the insurers, Mathematical Methods of Operations Research, 68 (2008), 181-205.  doi: 10.1007/s00186-007-0195-4.  Google Scholar

[5]

C. Bender and M. Kohlmann, BSDEs with Stochastic Lipschitz Condition, Universität Konstanz, Fakultät für Mathematik and Informatik, 2000. Google Scholar

[6]

J. N. Bi and J. Y. Guo, Optimal mean-variance problem with constrained controls in a jump-diffusion financial market for an insurer, Journal of Optimization Theory and Applications, 157 (2013), 252-275.  doi: 10.1007/s10957-012-0138-y.  Google Scholar

[7]

J. N. Bi, Z. B. Liang and F. J. Xu, Optimal mean-variance investment and reinsurance problems for the risk model with common shock dependence, Insurance: Mathematics and Economics, 70 (2016), 245-258.  doi: 10.1016/j.insmatheco.2016.06.012.  Google Scholar

[8]

T. R. Bielecki, H. Q. Jin, S. R. Pliskaz and X. Y. Zhou, Continuous-time mean-variance portfolio selection with bankruptcy prohibition, Mathematical Finance, 15 (2005), 213-244.  doi: 10.1111/j.0960-1627.2005.00218.x.  Google Scholar

[9]

S. Browne, Optimal investment policies for a firm with a random risk process: Exponentional utility and minimizing the probability of ruin, Mathematics of Operations Research, 20 (1995), 937-958.  doi: 10.1287/moor.20.4.937.  Google Scholar

[10]

F.J. Fabozzi and J. C. Francis, Mutual fund systematic risk for bull and bear markets: An empirical examination,, Journal of Finance, 34 (1979), 1243-1250.  doi: 10.1111/j.1540-6261.1979.tb00069.x.  Google Scholar

[11]

W. H. Fleming and H. M. Soner, Controled Markov Processes and Viscosity Solutions, Second edition. Stochastic Modelling and Applied Probability, 25. Springer, New York, 2006.  Google Scholar

[12]

M. Kobylanski, Backward stochastic differential equations and partial differential equations with quadratic growth, The Annals of Probability, 28 (2000), 558-602.  doi: 10.1214/aop/1019160253.  Google Scholar

[13]

X. Li, X. Y. Zhou and A. E. B. Lim, Dynamic mean-variance portfolio selection with no-shorting constraints, SIAM Journal on Control and Optimization, 40 (2002), 1540-1555.  doi: 10.1137/S0363012900378504.  Google Scholar

[14]

Z. B. Liang, K. C. Yuen and J. Y. Guo, Optimal proportional reinsurance and investment in a stock market with Ornstein-Uhlenbeck process, Insurance: Mathematics and Economics, 49 (2011), 207-215.  doi: 10.1016/j.insmatheco.2011.04.005.  Google Scholar

[15]

A. E. B. Lim, Mean-variance hedging when there are jumps, SIAM Journal on Control and Optimization, 44 (2005), 1893-1922.  doi: 10.1137/040610933.  Google Scholar

[16]

A. E. B. Lim, Quadratic hedging and mean-variance portfolio selection with random parameters in an incomplete market, Mathematics of Operations Research, 29 (2004), 132-161.  doi: 10.1287/moor.1030.0065.  Google Scholar

[17]

H. M. Markowitz, Portfolio selection, Journal of Finance, 7 (1952), 77-91.   Google Scholar

[18]

R. C. Merton, Theory of rational option pricing, The Bell Journal of Economics and Management Science, 4 (1973), 141-183.  doi: 10.2307/3003143.  Google Scholar

[19]

E. Pardoux and A. Rǎşcanu, Stochastic Differential Equations, Backward SDEs, Partial Differential Equations, Stochastic Modelling and Applied probability, 69. Springer, Switzerland, 2014. doi: 10.1007/978-3-319-05714-9.  Google Scholar

[20]

R. Rishel, Optimal portfolio management with partial observation and power utility function, Stochastic Analysis, Control, Optimization and Applications, Systems Control Found. Appl., Birkhäuser Boston, Boston, MA, (1999), 605–619.  Google Scholar

[21]

H. Schmidli, On minimizing the ruin probability by investment and reinsurance, The Annals of Applied Probability, 12 (2002), 890-907.  doi: 10.1214/aoap/1031863173.  Google Scholar

[22]

Y. Shen, Mean-variance portfolio selection in a complete market with unbounded random coefficients, Automatica J. IFAC, 55 (2015), 165-175.  doi: 10.1016/j.automatica.2015.03.009.  Google Scholar

[23]

Y. Shen and Y. Zeng, Optimal investment-reinsurance strategy for mean-variance insurers with square-root factor process, Insurance: Mathematics and Economics, 62 (2015), 118-137.  doi: 10.1016/j.insmatheco.2015.03.009.  Google Scholar

[24]

Y. Shen, X. Zhang and T. K. Siu, Mean-variance portfolio selection under a constant elasticity of variance model, Operations Research Letters, 42 (2014), 337-342.  doi: 10.1016/j.orl.2014.05.008.  Google Scholar

[25]

Z. Y. Sun, Upper bounds for ruin probabilities under model uncertainty, Communications in Statistics-Theory and Methods, 48 (2019), 4511-4527.  doi: 10.1080/03610926.2018.1491991.  Google Scholar

[26]

Z. Y. Sun and J. Y. Guo, Optimal mean-variance investment and reinsurance problem for an insurer with stochastic volatility, Mathematical Methods of Operations Research, 88 (2018), 59-79.  doi: 10.1007/s00186-017-0628-7.  Google Scholar

[27]

Z. Y. Sun and X. P. Guo, Equilibrium for a time-inconsistent stochastic linear-quadratic control system with jumps and its application to the mean-variance problem, Journal of Optimization Theory and Applications, 181 (2019), 383-410.  doi: 10.1007/s10957-018-01471-x.  Google Scholar

[28]

Z. Y. Sun, K. C. Yuen and J. Y. Guo, A BSDE approach to a class of dependent risk model of mean-variance insurers with stochastic volatility and no-short selling, Journal of Computational and Applied Mathematics, 366 (2019), 112413, 21 pp. doi: 10.1016/j.cam.2019.112413.  Google Scholar

[29]

Z. Y. Sun, X. Zhang and K. C. Yuen, Mean-variance asset-liability management with affine diffusion factor process and a reinsurance option, Scandinavian Actuarial Journal, (2019), DOI: https://doi.org/10.1080/03461238.2019.1658619. doi: 10.1080/03461238.2019.1658619.  Google Scholar

[30]

Z. Y. Sun, X. X. Zheng and X. Zhang, Robust optimal investment and reinsurance of an insurer under variance premium principle and default risk, Journal of Mathematical Analysis and Applications, 446 (2017), 1666-1686.  doi: 10.1016/j.jmaa.2016.09.053.  Google Scholar

[31]

Z. W. Wang, J. M. Xia and L. H. Zhang, Optimal investment for an insurer: the martingale approach, Insurance: Mathematics and Economics, 40 (2007), 322-334.  doi: 10.1016/j.insmatheco.2006.05.003.  Google Scholar

[32]

H. L. Yang and L. H. Zhang, Optimal investment for an insurer with jump-diffusion risk process, Insurance: Mathematics and Economics, 37 (2005), 615-634.  doi: 10.1016/j.insmatheco.2005.06.009.  Google Scholar

[33]

J. M. Yong and X. Y. Zhou, Stochastic Controls: Hamilton Systems and HJB Equations, Applications of Mathematics (New York), 43. Springer-Verlag, New York, 1999. doi: 10.1007/978-1-4612-1466-3.  Google Scholar

[34]

M. Zhang and P. Chen, Mean-variance asset-liability management under constant elasticity of variance process, Insurance: Mathematics and Economics, 70 (2016), 11-18.  doi: 10.1016/j.insmatheco.2016.05.019.  Google Scholar

[35]

X. Y. Zhou and D. Li, Continuous-time mean-variance portfolio selection: A stochastic LQ framework, Applied Mathematics and Optimization, 42 (2000), 19-33.  doi: 10.1007/s002450010003.  Google Scholar

[36]

X. Y. Zhou and G. Yin, Markowitz's mean-variance portfolio selection with regime switching: A continuous-time model, SIAM Journal on Control and Optimization, 42 (2003), 1466-1482.  doi: 10.1137/S0363012902405583.  Google Scholar

Figure 1.  the path of OU process $ m(t) $ with $ \alpha = -0.04 $ and $ \beta = 0.03 $
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Figure 2.  the optimal investment strategy with $ \alpha = -0.04, \beta = 0.03 $ and $ \alpha = \beta = 0 $
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Figure 3.  the optimal reinsurance strategy with $ \alpha = -0.04, \beta = 0.03 $ and $ \alpha = \beta = 0 $
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Figure 4.  the effect of $ \alpha $ on the efficient frontier
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Figure 5.  the effect of $ \lambda $ on the efficient frontier
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Figure 6.  the effect of $ \eta $ on the efficient frontier
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Figure 7.  the effect of $ r $ on the efficient frontier
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