doi: 10.3934/jimo.2018154

Optimal investment and dividend for an insurer under a Markov regime switching market with high gain tax

1. 

School of Mathematics and Statistics, Anhui Normal University, Wuhu 241002, China

2. 

School of Finance, Nanjing University of Finance and Economics, Nanjing 210023, China

3. 

School of Economics, Nanjing University of Finance and Economics, Nanjing 210023, China

Received  March 2018 Revised  May 2018 Published  September 2018

This study examines the optimal investment and dividend problem for an insurer with CRRA preference. The insurer's goal is to maximize the expected discounted accumulated utility from dividend before ruin and the insurer subjects to high gain tax payment. Both the surplus process and the financial market are modulated by an external Markov chain. Using the weak dynamic programming principle (WDPP), we prove that the value function of our control problem is the unique viscosity solution to coupled Hamilton-Jacobi-Bellman (HJB) equations with first derivative constraints. Solving an auxiliary problem without regime switching, we prove that, it is optimal for the insurer in a multiple-regime market to adopt the policies in the same way as in a single-regime market. The regularity of the viscosity solution on its domain is proved and thus the HJB equations admits classical solution. A numerical scheme for the value function is provided by the Markov chain approximation method, two numerical examples are given to illustrate the impact of the high gain tax and regime switching on the optimal policies.

Citation: Lin Xu, Dingjun Yao, Gongpin Cheng. Optimal investment and dividend for an insurer under a Markov regime switching market with high gain tax. Journal of Industrial & Management Optimization, doi: 10.3934/jimo.2018154
References:
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P. Azcue and N. Muler, Optimal dividend policies for compound poisson processes: The case of bounded dividend rates, Insurance: Mathematics and Economics, 51 (2012), 26-42. doi: 10.1016/j.insmatheco.2012.02.011. Google Scholar

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A. BarthS. M. Bromberg and O. Reichmann, A non-stationary model of dividend distribution in a stochastic interest-rate setting, Computational Economics, 47 (2016), 447-472. Google Scholar

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J. CaiH. U. Gerber and H. Yang, Optimal dividends in an ornstein-uhlenbeck type model with credit and debit interest, North American Actuarial Journal, 10 (2006), 94-119. doi: 10.1080/10920277.2006.10596250. Google Scholar

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T. ChoulliM. Taksar and X. Zhou, A diffusion model for optimal dividend distribution for a company with constraints on risk control, SIAM Journal on Control and Optimization, 41 (2003), 1946-1979. doi: 10.1137/S0363012900382667. Google Scholar

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J. FuJ. Wei and H. Yang, Portfolio optimization in a regime-switching market with derivatives, European Journal of Operational Research, 233 (2014), 184-192. doi: 10.1016/j.ejor.2013.08.033. Google Scholar

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P. GranditsF. HubalekW. Schachermayer and M. Žigo, Optimal expected exponential utility of dividend payments in a brownian risk model, Scandinavian Actuarial Journal, 2007 (2007), 73-107. doi: 10.1080/03461230601165201. Google Scholar

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B. Jgaard and M. Taksar, Controlling risk exposure and dividends payout schemes: insurance company example, Mathematical Finance, 9 (1999), 153-182. doi: 10.1111/1467-9965.00066. Google Scholar

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B. Højgaard and M. Taksar, Optimal dynamic portfolio selection for a corporation with controllable risk and dividend distribution policy, Quantitative Finance, 4 (2004), 315-327. doi: 10.1088/1469-7688/4/3/007. Google Scholar

[32]

F. Hubalek and W. Schachermayer, Optimizing expected utility of dividend payments for a brownian risk process and a peculiar nonlinear model, Insurance: Mathematics and Economics, 34 (2004), 193-225. doi: 10.1016/j.insmatheco.2003.12.001. Google Scholar

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[34]

B. Jang and K. 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

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Z. Jin and G. Yin, Numerical methods for optimal dividend payment and investment strategies of Markov-modulated jump diffusion models with regular and singular controls, Journal of Optimization Theory and Applications, 159 (2013), 246-271. doi: 10.1007/s10957-012-0263-7. Google Scholar

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Z. JinH. Yang and G. Yin, Numerical methods for optimal dividend payment and investment strategies of regime-switching jump diffusion models with capital injections, Automatica J. IFAC, 49 (2013), 2317-2329. doi: 10.1016/j.automatica.2013.04.043. Google Scholar

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Q. Song and C. Zhu, On singular control problems with state constraints and regime-switching: a viscosity solution approach, Automatica, 70 (2016), 66-73. doi: 10.1016/j.automatica.2016.03.017. Google Scholar

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Q. SongG. Yin and Z. Zhang, Numerical methods for controlled regime-switching diffusions and regime-switching jump diffusions, Automatica, 42 (2006), 1147-1157. doi: 10.1016/j.automatica.2006.03.016. Google Scholar

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S. TanZ. Jin and G. Yin, Optimal dividend payment strategies with debt constraint in a hybrid regime-switching jump-diffusion model, Nonlinear Analysis: Hybrid Systems, 27 (2018), 141-156. doi: 10.1016/j.nahs.2017.08.007. Google Scholar

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show all references

References:
[1]

B. Avanzi, Strategies for dividend distribution: A review, North American Actuarial Journal, 13 (2009), 217-251. doi: 10.1080/10920277.2009.10597549. Google Scholar

[2]

F. AvramZ. Palmowski and M. Pistorius, On gerber-shiu functions and optimal dividend distribution for a lévy risk process in the presence of a penalty function, The Annals of Applied Probability, 25 (2015), 1868-1935. doi: 10.1214/14-AAP1038. Google Scholar

[3]

P. Azcue and N. Muler, Optimal investment policy and dividend payment strategy in an insurance company, The Annals of Applied Probability, 20 (2010), 1253-1302. doi: 10.1214/09-AAP643. Google Scholar

[4]

P. Azcue and N. Muler, Optimal dividend policies for compound poisson processes: The case of bounded dividend rates, Insurance: Mathematics and Economics, 51 (2012), 26-42. doi: 10.1016/j.insmatheco.2012.02.011. Google Scholar

[5]

L. Bai and J. Guo, Optimal dividend payments in the classical risk model when payments are subject to both transaction costs and taxes, Scandinavian Actuarial Journal, 2010 (2010), 36-55. doi: 10.1080/03461230802591098. Google Scholar

[6]

G. Barles and C. Imbert, Second-order elliptic integro-differential equations: Viscosity solutions' theory revisited, Annales de l'IHP Analyse non linéaire, 25 (2008), 567-585. doi: 10.1016/j.anihpc.2007.02.007. Google Scholar

[7]

A. BarthS. M. Bromberg and O. Reichmann, A non-stationary model of dividend distribution in a stochastic interest-rate setting, Computational Economics, 47 (2016), 447-472. Google Scholar

[8]

N. Bäuerle and U. Rieder, Portfolio optimization with markov-modulated stock prices and interest rates, IEEE Transactions on Automatic Control, 49 (2004), 442-447. doi: 10.1109/TAC.2004.824471. Google Scholar

[9]

B. HamadéneR. BelfadliS. Hamadéne and Y. Ouknine, On one-dimensional stochastic differential equations involving the maximum process, Stochastics and Dynamics, 9 (2009), 277-292. doi: 10.1142/S0219493709002671. Google Scholar

[10]

B. Bouchard and N. Touzi, Weak dynamic programming principle for viscosity solutions, SIAM Journal on Control and Optimization, 49 (2011), 948-962. doi: 10.1137/090752328. Google Scholar

[11]

J. Brinkhuis and V. Tikhomirov, Optimization: Insights and Applications, Princeton University Press, 2005. doi: 10.1515/9781400829361. Google Scholar

[12]

A. CadenillasS. Sarkar and F. Zapatero, Optimal dividend policy with mean-reverting cash reservoir, Mathematical Finance, 17 (2007), 81-109. doi: 10.1111/j.1467-9965.2007.00295.x. Google Scholar

[13]

J. CaiH. U. Gerber and H. Yang, Optimal dividends in an ornstein-uhlenbeck type model with credit and debit interest, North American Actuarial Journal, 10 (2006), 94-119. doi: 10.1080/10920277.2006.10596250. Google Scholar

[14]

S. ChenZ. Li and Y. Zeng, Optimal dividend strategies with time-inconsistent preferences, Journal of Economic Dynamics and Control, 46 (2014), 150-172. doi: 10.1016/j.jedc.2014.06.018. Google Scholar

[15]

T. ChoulliM. Taksar and X. Zhou, A diffusion model for optimal dividend distribution for a company with constraints on risk control, SIAM Journal on Control and Optimization, 41 (2003), 1946-1979. doi: 10.1137/S0363012900382667. Google Scholar

[16]

K. L. Chung, A Course in Probability Theory, Academic press, 2001. Google Scholar

[17]

H. M. Clements and M. Krolzig, Can regime-switching models reproduce the business cycle features of us aggregate consumption, investment and output?, International Journal of Finance and Economics, 9 (2004), 1-14. doi: 10.1002/ijfe.231. Google Scholar

[18]

M. CrandallH. Ishii and P. L. Lions, User's guide to viscosity solutions of second order partial differential equations, Bulletin of the American Mathematical Society, 27 (1992), 1-67. doi: 10.1090/S0273-0979-1992-00266-5. Google Scholar

[19]

Finetti De, Su un'impostazione alternativa della teoria collettiva del rischio, Transactions of the XVth International Congress of Actuaries, 2 (1957), 433-443. Google Scholar

[20]

D. DuffieW. FlemingH. M. Soner and T. Zariphopoulou, Hedging in incomplete markets with hara utility, Journal of Economic Dynamics and Control, 21 (1997), 753-782. doi: 10.1016/S0165-1889(97)00002-X. Google Scholar

[21]

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

[22]

R. J. Elliott and P. E. Kopp, Mathematics of Financial Markets, Springer, 2005. Google Scholar

[23]

W. H. Fleming and T. Pang, A stochastic control model of investment, production and consumption, Quarterly of Applied Mathematics, 63 (2005), 71-87. doi: 10.1090/S0033-569X-04-00941-1. Google Scholar

[24]

W. H. Fleming and H. M. Soner, Controlled Markov Processes and Viscosity Solutions, Springer, 2006. Google Scholar

[25]

J. FuJ. Wei and H. Yang, Portfolio optimization in a regime-switching market with derivatives, European Journal of Operational Research, 233 (2014), 184-192. doi: 10.1016/j.ejor.2013.08.033. Google Scholar

[26]

J. GaierP. Grandits and W. Schachermayer, Asymptotic ruin probabilities and optimal investment, Annals of Applied Probability, 13 (2003), 1054-1076. doi: 10.1214/aoap/1060202834. Google Scholar

[27]

H. U. Gerber and E. S. W. Shiu, Optimal dividends: analysis with brownian motion, North American Actuarial Journal, 8 (2004), 1-20. doi: 10.1080/10920277.2004.10596125. Google Scholar

[28]

J. Grandell, Aspects of Risk Theory, Springer, 1991. doi: 10.1007/978-1-4613-9058-9. Google Scholar

[29]

P. GranditsF. HubalekW. Schachermayer and M. Žigo, Optimal expected exponential utility of dividend payments in a brownian risk model, Scandinavian Actuarial Journal, 2007 (2007), 73-107. doi: 10.1080/03461230601165201. Google Scholar

[30]

B. Jgaard and M. Taksar, Controlling risk exposure and dividends payout schemes: insurance company example, Mathematical Finance, 9 (1999), 153-182. doi: 10.1111/1467-9965.00066. Google Scholar

[31]

B. Højgaard and M. Taksar, Optimal dynamic portfolio selection for a corporation with controllable risk and dividend distribution policy, Quantitative Finance, 4 (2004), 315-327. doi: 10.1088/1469-7688/4/3/007. Google Scholar

[32]

F. Hubalek and W. Schachermayer, Optimizing expected utility of dividend payments for a brownian risk process and a peculiar nonlinear model, Insurance: Mathematics and Economics, 34 (2004), 193-225. doi: 10.1016/j.insmatheco.2003.12.001. Google Scholar

[33]

K. Janecek and M. Sîrbu, Optimal investment with high-watermark performance fee, SIAM Journal on Control and Optimization, 50 (2012), 790-819. doi: 10.1137/100790884. Google Scholar

[34]

B. Jang and K. 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

[35]

Z. Jiang and M. Pistorius, Optimal dividend distribution under markov regime switching, Finance and Stochastics, 16 (2012), 449-476. doi: 10.1007/s00780-012-0174-3. Google Scholar

[36]

Z. Jin and G. Yin, Numerical methods for optimal dividend payment and investment strategies of Markov-modulated jump diffusion models with regular and singular controls, Journal of Optimization Theory and Applications, 159 (2013), 246-271. doi: 10.1007/s10957-012-0263-7. Google Scholar

[37]

Z. JinH. Yang and G. Yin, Numerical methods for optimal dividend payment and investment strategies of regime-switching jump diffusion models with capital injections, Automatica J. IFAC, 49 (2013), 2317-2329. doi: 10.1016/j.automatica.2013.04.043. Google Scholar

[38]

N. V. Krylov, Nonlinear Elliptic and Parabolic Equations of the Second Order, Springer, 1987.Google Scholar

[39]

H. Kushner and P. Dupuis, Numerical Methods for Stochastic Control Problems in Continuous Time, Springer, 2001. doi: 10.1007/978-1-4613-0007-6. Google Scholar

[40]

G. LeobacherM. Szölgyenyi and S. Thonhauser, Bayesian dividend optimization and finite time ruin probabilities, Stochastic Models, 30 (2014), 216-249. doi: 10.1080/15326349.2014.900390. Google Scholar

[41]

R. C Merton, Optimum consumption and portfolio rules in a continuous-time model, Journal of Economic Theory, 3 (1971), 373-413. doi: 10.1016/0022-0531(71)90038-X. Google Scholar

[42]

B. Oksendal, Stochastic Differential Equations: An Introduction with Applications, Springer Science and Business Media, 2013.Google Scholar

[43]

J. Paulsen, Optimal dividend payouts for diffusions with solvency constraints, Finance and Stochastics, 7 (2003), 457-473. doi: 10.1007/s007800200098. Google Scholar

[44]

I. Pospelov and S. Radionov, Optimal dividend policy when cash surplus follows telegraph process, 2015.Google Scholar

[45]

P. E. Protter, Stochastic Integration and Differential Equations, Springer-Verlag, Berlin, 2005. doi: 10.1007/978-3-662-10061-5. Google Scholar

[46]

M. Reppen, J. Rochet and H. M. Soner. Optimal dividend policies with random profitability, arXiv preprint, arXiv: 1706.01813, 2017.Google Scholar

[47]

L. C. G. Rogers, Optimal Investment, Springer, 2013. doi: 10.1007/978-3-642-35202-7. Google Scholar

[48]

T. Rolski, H. Schmidli, V. Schmidt and J. Teugels, Stochastic Processes for Insurance and Finance, John Wiley & Sons, Ltd., Chichester, 1999. doi: 10.1002/9780470317044. Google Scholar

[49]

J. Sass and U. G. Haussmann, Optimizing the terminal wealth under partial information: The drift process as a continuous time markov chain, Finance and Stochastics, 8 (2004), 553-577. doi: 10.1007/s00780-004-0132-9. Google Scholar

[50]

Q. Song and C. Zhu, On singular control problems with state constraints and regime-switching: a viscosity solution approach, Automatica, 70 (2016), 66-73. doi: 10.1016/j.automatica.2016.03.017. Google Scholar

[51]

Q. SongG. Yin and Z. Zhang, Numerical methods for controlled regime-switching diffusions and regime-switching jump diffusions, Automatica, 42 (2006), 1147-1157. doi: 10.1016/j.automatica.2006.03.016. Google Scholar

[52]

J. Stiglitz, Some aspects of the taxation of capital gains, Journal of Public Economics, 21 (1983), 257-294. doi: 10.3386/w1094. Google Scholar

[53]

M. Szölgyenyi, Dividend maximization in a hidden markov switching model, Statistics and Risk Modeling, 32 (2015), 143-158. doi: 10.1515/strm-2015-0019. Google Scholar

[54]

M. Taksar, Optimal risk and dividend distribution control models for an insurance company, Mathematical Methods of Operations Research, 51 (2000), 1-42. doi: 10.1007/s001860050001. Google Scholar

[55]

S. TanZ. Jin and G. Yin, Optimal dividend payment strategies with debt constraint in a hybrid regime-switching jump-diffusion model, Nonlinear Analysis: Hybrid Systems, 27 (2018), 141-156. doi: 10.1016/j.nahs.2017.08.007. Google Scholar

[56]

A. D. Wentzell, S. Chomet and K. L. Chung, A Course in the Theory of Stochastic Processes, McGraw-Hill International New York, 1981. Google Scholar

[57]

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Figure 1.  Comparison of optimal dividend amount
Figure 2.  Comparison of optimal investment amount
Figure 3.  Optimal dividend amount under bull and bear market
Figure 4.  Optimal investment amount under bull and bear marke
Table 1.  Parameters setting in Example 1
(Investor, Parameter)$\mu_1$$\sigma_1$$\mu_2$$\sigma_2$$p$$\beta$$\lambda$$n$
Merton000.060.30.330.150-
Financial Agent000.060.30.330.150.210
Insurer0.40.50.060.30.330.150.210
(Investor, Parameter)$\mu_1$$\sigma_1$$\mu_2$$\sigma_2$$p$$\beta$$\lambda$$n$
Merton000.060.30.330.150-
Financial Agent000.060.30.330.150.210
Insurer0.40.50.060.30.330.150.210
Table 2.  Parameters setting in Example 2
(State, Parameter)$\mu_1$$\sigma_1$$\mu_2$$\sigma_2$$p$$\beta$$\lambda$$n$
Bull0.40.50.060.30.30.050.210
Bear0.30.50.030.30.30.050.210
(State, Parameter)$\mu_1$$\sigma_1$$\mu_2$$\sigma_2$$p$$\beta$$\lambda$$n$
Bull0.40.50.060.30.30.050.210
Bear0.30.50.030.30.30.050.210
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