September  2020, 16(5): 2195-2211. doi: 10.3934/jimo.2019050

Optimal investment-reinsurance policy with regime switching and value-at-risk constraint

1. 

Coordinated Innovation Center for Computable Modeling in Management Science, Tianjin University of Finance and Economics, Tianjin 300222, China

2. 

Department of Mathematical Sciences, University of Nevada, Las Vegas, NV89154, United States

*Corresponding author

Received  April 2018 Revised  October 2018 Published  May 2019

Fund Project: This project was supported by Tianjin philosophy and social science planning project (TJGLQN18-005)

This paper studies an optimal investment-reinsurance problem for an insurance company which is subject to a dynamic Value-at-Risk (VaR) constraint in a Markovian regime-switching environment. Our goal is to minimize its ruin probability and control its market risk simultaneously. We formulate the problem as an infinite horizontal stochastic control problem with the constrained strategies. The dynamic programming technique is applied to derive the coupled Hamilton-Jacobi-Bellman (HJB) equations and the Lagrange multiplier method is used to tackle the dynamic VaR constraint. Furthermore, we propose an efficient numerical method to solve those HJB equations. Finally, we employ a practical example from the Korean market to verify the numerical method and analyze the optimal strategies under different VaR constraints.

Citation: Ming Yan, Hongtao Yang, Lei Zhang, Shuhua Zhang. Optimal investment-reinsurance policy with regime switching and value-at-risk constraint. Journal of Industrial & Management Optimization, 2020, 16 (5) : 2195-2211. doi: 10.3934/jimo.2019050
References:
[1]

A. Ang and G. Bekaert, International asset allocation with regime shifts, Review of Financial Studies, 15 (2002), 1137-1187.  doi: 10.1093/rfs/15.4.1137.  Google Scholar

[2]

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

[3]

H. Bühlmann, Mathematical Methods in Risk Theory, Springer, Berlin, 1970.  Google Scholar

[4]

Y. Cao and X. Zeng, Optimal proportional reinsurance and investment with minimum probability of ruin, J. Nanjing Norm. Univ. Nat. Sci. Ed., 36 (2013), 1-9.   Google Scholar

[5]

R. ChenK. A. Wong and H. C. Lee, Underwriting cycles in Asia, Journal of Risk and Insurance, 66 (1999), 29-47.  doi: 10.2307/253876.  Google Scholar

[6]

P. Chen and S. C. P. Yam, Optimal proportional reinsurance and investment with regime-switching for mean-variance insurers, Insurance: Mathematics & Economics, 53 (2013), 871-883.  doi: 10.1016/j.insmatheco.2013.10.004.  Google Scholar

[7]

S. ChenZ. Li and K. Li, Optimal investment-reinsurance policy for an insurance company with VaR constraint, Insurance: Mathematics & Economics, 47 (2010), 144-153.  doi: 10.1016/j.insmatheco.2010.06.002.  Google Scholar

[8]

S. Choi and P. D. Thistle, The property/liability insurance cycle: A comparison of alternative models, Southern Economic Journal, 68 (2002), 530-548.  doi: 10.2307/1061716.  Google Scholar

[9]

D. CuocoH. He and S. Isaenko, Optimal dynamic trading strategies with risk limits, Operations Research, 56 (2001), 358-368.  doi: 10.1287/opre.1070.0433.  Google Scholar

[10]

R. J. Elliott, L. Aggoun and J. B. Moore, Hidden Markov Models: Estimation and Control, Springer, 1995.  Google Scholar

[11]

H. G. Fung and R. C. Witt, Underwriting cycles in property and liability insurance: An empirical analysis of industry and byline data, Journal of Risk and Insurance, 65 (1998), 539-561.  doi: 10.2307/253802.  Google Scholar

[12]

A. Gundel and S. Weber, Utility maximization under a shortfall risk constraint, Journal of Mathematical Economics, 44 (2008), 1126-1151.  doi: 10.1016/j.jmateco.2008.01.002.  Google Scholar

[13]

B. G. Jang and K. T. Kim, Optimal reinsurance and asset allocation under regime switching, Journal of Banking and Finance, 56 (2015), 37-47.  doi: 10.1016/j.jbankfin.2015.03.002.  Google Scholar

[14]

Z. JinG. Yin and F. Wu, Optimal reinsurance strategies in regime-switching jump diffusion models: Stochastic differential game formulation and numerical methods, Insurance: Mathematics & Economics, 53 (2013), 733-746.  doi: 10.1016/j.insmatheco.2013.09.015.  Google Scholar

[15]

Z. Liang and J. Guo, Optimal proportional reinsurance under two criteria: Maximizing the expected utility and minimizing the value at risk, Anziam Journal, 51 (2010), 449-463.  doi: 10.1017/S1446181110000878.  Google Scholar

[16]

J. Liu, K. F. C. Yiu, R. C. Loxton, K. L. Teo, Optimal investment and proportional reinsurance with risk constraint, Journal of Mathematical Finance 3 (4) (2013) 437–447. doi: 10.4236/jmf.2013.34046.  Google Scholar

[17]

J. Liu, K. F. C. Yiu, T. K. Siu and W. K. Ching, Optimal investment-reinsurance with dynamic risk constraint and regime switching, Scandinavian Actuarial Journal, 3 (2013), Article ID: 38147, 11 pages. doi: 10.1080/03461238.2011.602477.  Google Scholar

[18]

H. Schmidli, Stochastic Control in Insurance, Springer, London, 2008.  Google Scholar

[19]

H. Schmidli, Optimal proportional reinsurance policies in a dynamic setting, Scandinavian Actuarial Journal, 1 (2001), 55-68.  doi: 10.1080/034612301750077338.  Google Scholar

[20]

M. I. Taksar and C. Markussen, Optimal dynamic reinsurance policies for large insurance portfolios, Finance and Stochastics, 7 (2003), 97-121.  doi: 10.1007/s007800200073.  Google Scholar

[21]

K. F. C. Yiu, Optimal portfolios under a value-at-risk constraint, Journal of Economic Dynamics & Control, 28 (2004), 1317-1334.  doi: 10.1016/S0165-1889(03)00116-7.  Google Scholar

[22]

K. F. C. YiuJ. LiuT. K. Siu and W. K. Ching, Optimal portfolios with regime switching and value-at-risk constraint, Automatica, 46 (2010), 979-989.  doi: 10.1016/j.automatica.2010.02.027.  Google Scholar

[23]

C. Zhu, Optimal control of the risk process in a regime-switching environment, Automatica, 47 (2011), 1570-1579.  doi: 10.1016/j.automatica.2011.03.007.  Google Scholar

show all references

References:
[1]

A. Ang and G. Bekaert, International asset allocation with regime shifts, Review of Financial Studies, 15 (2002), 1137-1187.  doi: 10.1093/rfs/15.4.1137.  Google Scholar

[2]

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

[3]

H. Bühlmann, Mathematical Methods in Risk Theory, Springer, Berlin, 1970.  Google Scholar

[4]

Y. Cao and X. Zeng, Optimal proportional reinsurance and investment with minimum probability of ruin, J. Nanjing Norm. Univ. Nat. Sci. Ed., 36 (2013), 1-9.   Google Scholar

[5]

R. ChenK. A. Wong and H. C. Lee, Underwriting cycles in Asia, Journal of Risk and Insurance, 66 (1999), 29-47.  doi: 10.2307/253876.  Google Scholar

[6]

P. Chen and S. C. P. Yam, Optimal proportional reinsurance and investment with regime-switching for mean-variance insurers, Insurance: Mathematics & Economics, 53 (2013), 871-883.  doi: 10.1016/j.insmatheco.2013.10.004.  Google Scholar

[7]

S. ChenZ. Li and K. Li, Optimal investment-reinsurance policy for an insurance company with VaR constraint, Insurance: Mathematics & Economics, 47 (2010), 144-153.  doi: 10.1016/j.insmatheco.2010.06.002.  Google Scholar

[8]

S. Choi and P. D. Thistle, The property/liability insurance cycle: A comparison of alternative models, Southern Economic Journal, 68 (2002), 530-548.  doi: 10.2307/1061716.  Google Scholar

[9]

D. CuocoH. He and S. Isaenko, Optimal dynamic trading strategies with risk limits, Operations Research, 56 (2001), 358-368.  doi: 10.1287/opre.1070.0433.  Google Scholar

[10]

R. J. Elliott, L. Aggoun and J. B. Moore, Hidden Markov Models: Estimation and Control, Springer, 1995.  Google Scholar

[11]

H. G. Fung and R. C. Witt, Underwriting cycles in property and liability insurance: An empirical analysis of industry and byline data, Journal of Risk and Insurance, 65 (1998), 539-561.  doi: 10.2307/253802.  Google Scholar

[12]

A. Gundel and S. Weber, Utility maximization under a shortfall risk constraint, Journal of Mathematical Economics, 44 (2008), 1126-1151.  doi: 10.1016/j.jmateco.2008.01.002.  Google Scholar

[13]

B. G. Jang and K. T. Kim, Optimal reinsurance and asset allocation under regime switching, Journal of Banking and Finance, 56 (2015), 37-47.  doi: 10.1016/j.jbankfin.2015.03.002.  Google Scholar

[14]

Z. JinG. Yin and F. Wu, Optimal reinsurance strategies in regime-switching jump diffusion models: Stochastic differential game formulation and numerical methods, Insurance: Mathematics & Economics, 53 (2013), 733-746.  doi: 10.1016/j.insmatheco.2013.09.015.  Google Scholar

[15]

Z. Liang and J. Guo, Optimal proportional reinsurance under two criteria: Maximizing the expected utility and minimizing the value at risk, Anziam Journal, 51 (2010), 449-463.  doi: 10.1017/S1446181110000878.  Google Scholar

[16]

J. Liu, K. F. C. Yiu, R. C. Loxton, K. L. Teo, Optimal investment and proportional reinsurance with risk constraint, Journal of Mathematical Finance 3 (4) (2013) 437–447. doi: 10.4236/jmf.2013.34046.  Google Scholar

[17]

J. Liu, K. F. C. Yiu, T. K. Siu and W. K. Ching, Optimal investment-reinsurance with dynamic risk constraint and regime switching, Scandinavian Actuarial Journal, 3 (2013), Article ID: 38147, 11 pages. doi: 10.1080/03461238.2011.602477.  Google Scholar

[18]

H. Schmidli, Stochastic Control in Insurance, Springer, London, 2008.  Google Scholar

[19]

H. Schmidli, Optimal proportional reinsurance policies in a dynamic setting, Scandinavian Actuarial Journal, 1 (2001), 55-68.  doi: 10.1080/034612301750077338.  Google Scholar

[20]

M. I. Taksar and C. Markussen, Optimal dynamic reinsurance policies for large insurance portfolios, Finance and Stochastics, 7 (2003), 97-121.  doi: 10.1007/s007800200073.  Google Scholar

[21]

K. F. C. Yiu, Optimal portfolios under a value-at-risk constraint, Journal of Economic Dynamics & Control, 28 (2004), 1317-1334.  doi: 10.1016/S0165-1889(03)00116-7.  Google Scholar

[22]

K. F. C. YiuJ. LiuT. K. Siu and W. K. Ching, Optimal portfolios with regime switching and value-at-risk constraint, Automatica, 46 (2010), 979-989.  doi: 10.1016/j.automatica.2010.02.027.  Google Scholar

[23]

C. Zhu, Optimal control of the risk process in a regime-switching environment, Automatica, 47 (2011), 1570-1579.  doi: 10.1016/j.automatica.2011.03.007.  Google Scholar

Figure 1.  $ u_1^*(x) $ with different MVaR levels
Figure 2.  $ u_2^*(x) $ with different MVaR levels
Figure 3.  $ \pi_1^*(x) $ with different MVaR levels
Figure 4.  $ \pi_2^*(x) $ with different MVaR levels
Figure 5.  $ V_1(x) $ with different MVaR levels
Figure 6.  $ V_2(x) $ with different MVaR levels
[1]

Christoforidou Amalia, Christian-Oliver Ewald. A lattice method for option evaluation with regime-switching asset correlation structure. Journal of Industrial & Management Optimization, 2021, 17 (4) : 1729-1752. doi: 10.3934/jimo.2020042

[2]

Kehan Si, Zhenda Xu, Ka Fai Cedric Yiu, Xun Li. Open-loop solvability for mean-field stochastic linear quadratic optimal control problems of Markov regime-switching system. Journal of Industrial & Management Optimization, 2021  doi: 10.3934/jimo.2021074

[3]

Yan Zhang, Peibiao Zhao, Xinghu Teng, Lei Mao. Optimal reinsurance and investment strategies for an insurer and a reinsurer under Hestons SV model: HARA utility and Legendre transform. Journal of Industrial & Management Optimization, 2021, 17 (4) : 2139-2159. doi: 10.3934/jimo.2020062

[4]

Mohammed Abdelghany, Amr B. Eltawil, Zakaria Yahia, Kazuhide Nakata. A hybrid variable neighbourhood search and dynamic programming approach for the nurse rostering problem. Journal of Industrial & Management Optimization, 2021, 17 (4) : 2051-2072. doi: 10.3934/jimo.2020058

[5]

Reza Lotfi, Yahia Zare Mehrjerdi, Mir Saman Pishvaee, Ahmad Sadeghieh, Gerhard-Wilhelm Weber. A robust optimization model for sustainable and resilient closed-loop supply chain network design considering conditional value at risk. Numerical Algebra, Control & Optimization, 2021, 11 (2) : 221-253. doi: 10.3934/naco.2020023

[6]

Patrick Henning, Anders M. N. Niklasson. Shadow Lagrangian dynamics for superfluidity. Kinetic & Related Models, 2021, 14 (2) : 303-321. doi: 10.3934/krm.2021006

[7]

Min Li, Jiahua Zhang, Yifan Xu, Wei Wang. Effects of disruption risk on a supply chain with a risk-averse retailer. Journal of Industrial & Management Optimization, 2021  doi: 10.3934/jimo.2021024

[8]

Chris Guiver, Nathan Poppelreiter, Richard Rebarber, Brigitte Tenhumberg, Stuart Townley. Dynamic observers for unknown populations. Discrete & Continuous Dynamical Systems - B, 2021, 26 (6) : 3279-3302. doi: 10.3934/dcdsb.2020232

[9]

Yuri Chekanov, Felix Schlenk. Notes on monotone Lagrangian twist tori. Electronic Research Announcements, 2010, 17: 104-121. doi: 10.3934/era.2010.17.104

[10]

Yingxu Tian, Junyi Guo, Zhongyang Sun. Optimal mean-variance reinsurance in a financial market with stochastic rate of return. Journal of Industrial & Management Optimization, 2021, 17 (4) : 1887-1912. doi: 10.3934/jimo.2020051

[11]

Alexandr Mikhaylov, Victor Mikhaylov. Dynamic inverse problem for Jacobi matrices. Inverse Problems & Imaging, 2019, 13 (3) : 431-447. doi: 10.3934/ipi.2019021

[12]

Chonghu Guan, Xun Li, Rui Zhou, Wenxin Zhou. Free boundary problem for an optimal investment problem with a borrowing constraint. Journal of Industrial & Management Optimization, 2021  doi: 10.3934/jimo.2021049

[13]

Manuel de León, Víctor M. Jiménez, Manuel Lainz. Contact Hamiltonian and Lagrangian systems with nonholonomic constraints. Journal of Geometric Mechanics, 2021, 13 (1) : 25-53. doi: 10.3934/jgm.2021001

[14]

Knut Hüper, Irina Markina, Fátima Silva Leite. A Lagrangian approach to extremal curves on Stiefel manifolds. Journal of Geometric Mechanics, 2021, 13 (1) : 55-72. doi: 10.3934/jgm.2020031

[15]

Akio Matsumoto, Ferenc Szidarovszky. Stability switching and its directions in cournot duopoly game with three delays. Discrete & Continuous Dynamical Systems - B, 2021  doi: 10.3934/dcdsb.2021069

[16]

Samira Shahsavari, Saeed Ketabchi. The proximal methods for solving absolute value equation. Numerical Algebra, Control & Optimization, 2021, 11 (3) : 449-460. doi: 10.3934/naco.2020037

[17]

Simone Cacace, Maurizio Falcone. A dynamic domain decomposition for the eikonal-diffusion equation. Discrete & Continuous Dynamical Systems - S, 2016, 9 (1) : 109-123. doi: 10.3934/dcdss.2016.9.109

[18]

Ardeshir Ahmadi, Hamed Davari-Ardakani. A multistage stochastic programming framework for cardinality constrained portfolio optimization. Numerical Algebra, Control & Optimization, 2017, 7 (3) : 359-377. doi: 10.3934/naco.2017023

[19]

Luke Finlay, Vladimir Gaitsgory, Ivan Lebedev. Linear programming solutions of periodic optimization problems: approximation of the optimal control. Journal of Industrial & Management Optimization, 2007, 3 (2) : 399-413. doi: 10.3934/jimo.2007.3.399

[20]

Mrinal K. Ghosh, Somnath Pradhan. A nonzero-sum risk-sensitive stochastic differential game in the orthant. Mathematical Control & Related Fields, 2021  doi: 10.3934/mcrf.2021025

2019 Impact Factor: 1.366

Metrics

  • PDF downloads (186)
  • HTML views (591)
  • Cited by (0)

Other articles
by authors

[Back to Top]