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Conditional LQ time-inconsistent Markov-switching stochastic optimal control problem for diffusion with jumps
Volume 9, Issue 2 (2022), pp. 157–205
Nour El Houda Bouaicha   Farid Chighoub ORCID icon link to view author Farid Chighoub details   Ishak Alia   Ayesha Sohail  

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https://doi.org/10.15559/22-VMSTA199
Pub. online: 3 February 2022      Type: Research Article      Open accessOpen Access

Received
12 October 2021
Revised
9 January 2022
Accepted
12 January 2022
Published
3 February 2022

Abstract

The paper presents a characterization of equilibrium in a game-theoretic description of discounting conditional stochastic linear-quadratic (LQ for short) optimal control problem, in which the controlled state process evolves according to a multidimensional linear stochastic differential equation, when the noise is driven by a Poisson process and an independent Brownian motion under the effect of a Markovian regime-switching. The running and the terminal costs in the objective functional are explicitly dependent on several quadratic terms of the conditional expectation of the state process as well as on a nonexponential discount function, which create the time-inconsistency of the considered model. Open-loop Nash equilibrium controls are described through some necessary and sufficient equilibrium conditions. A state feedback equilibrium strategy is achieved via certain differential-difference system of ODEs. As an application, we study an investment–consumption and equilibrium reinsurance/new business strategies for mean-variance utility for insurers when the risk aversion is a function of current wealth level. The financial market consists of one riskless asset and one risky asset whose price process is modeled by geometric Lévy processes and the surplus of the insurers is assumed to follow a jump-diffusion model, where the values of parameters change according to continuous-time Markov chain. A numerical example is provided to demonstrate the efficacy of theoretical results.

References

[1] 
Basak, S., Chabakauri, G.: Dynamic mean-variance asset allocation. Rev. Financ. Stud. 23, 2970–3016 (2010). https://doi.org/10.1093/rfs/hhq028
[2] 
Bensoussan, A., Sung, K.C.J., Yam, S.C.P.: Linear-quadratic time-inconsistent mean field games. Dyn. Games Appl. 3(4), 537–552 (2013). MR3127149. https://doi.org/10.1007/s13235-013-0090-y
[3] 
Björk, T., Khapko, M., Murgoci, A.: On time-inconsistent stochastic control in continuous time. Finance Stoch. 21, 331–360 (2017). MR3626618. https://doi.org/10.1007/s00780-017-0327-5
[4] 
Björk, T., Murgoci, A., Zhou, X.Y.: Mean-variance portfolio optimization with state-dependent risk aversion. Math. Finance 24(1), 1–24 (2014). MR3157686. https://doi.org/10.1111/j.1467-9965.2011.00515.x
[5] 
Chen, P., Yang, H., Yin, G.: Markowitz’s mean-variance asset-liability management with regime switching: a continuous-time model. Insur. Math. Econ. 43(3), 456–465 (2008). MR2479605. https://doi.org/10.1016/j.insmatheco.2008.09.001
[6] 
Chen, P., Yang, H.: Markowitz’s mean-variance asset-liability management with regime switching: a multi period model. Appl. Math. Finance 18(1), 29–50 (2011). MR2786975. https://doi.org/10.1080/13504861003703633
[7] 
Cohen, S.N., Elliott, R.J.: Solutions of backward stochastic differential equations on Markov chains. Commun. Stoch. Anal. 2, 251–262 (2008). MR2446692. https://doi.org/10.31390/cosa.2.2.05
[8] 
Czichowsky, C.: Time-consistent mean-variance porftolio selection in discrete and continuous time. Finance Stoch. 17(2), 227–271 (2013). MR3038591. https://doi.org/10.1007/s00780-012-0189-9
[9] 
Delong, Ł., Gerrard, R.: Mean-variance portfolio selection for a nonlife insurance company. Math. Methods Oper. Res. 66, 339–367 (2007). MR2342219. https://doi.org/10.1007/s00186-007-0152-2
[10] 
Ekeland, I., Mbodji, O., Pirvu, T.A.: Time-consistent portfolio management. SIAM J. Financ. Math. 3, 1–32 (2012). MR2968026. https://doi.org/10.1137/100810034
[11] 
Ekeland, I., Pirvu, T.A.: Investment and consumption without commitment. Math. Financ. Econ. 2, 57–86 (2008). MR2461340. https://doi.org/10.1007/s11579-008-0014-6
[12] 
Elliott, R.J., Aggoun, L., Moore, J.B.: Hidden Markov Models: Estimation and Control. Springer, New York (1994). MR1323178
[13] 
Goldman, S.M.: Consistent plans. Rev. Financ. Stud. 47, 533–537 (1980)
[14] 
Hu, Y., Jin, H., Zhou, X.: Time inconsistent stochastic linear-quadratic control: characterization and uniqueness of equilibrium. SIAM J. Control Optim. 55(2), 1261–1279 (2017). MR3639569. https://doi.org/10.1137/15M1019040
[15] 
Hu, Y., Jin, H., Zhou, X.Y.: Time-inconsistent stochastic linear quadratic control. SIAM J. Control Optim. 50(3), 1548–1572 (2012). MR2968066. https://doi.org/10.1137/110853960
[16] 
Krusell, P., Smith, A.: Consumption and savings decisions with quasi-geometric discounting. Econometrica 71, 366–375 (2003)
[17] 
Li, Y., Li, Z.: Optimal time-consistent investment and reinsurance strategies for mean-variance insurers with state dependent risk aversion. Insur. Math. Econ. 53(1), 86–97 (2013). MR3081464. https://doi.org/10.1016/j.insmatheco.2013.03.008
[18] 
Liang, Z., Song, M.: Time-consistent reinsurance and investment strategies for mean-variance insurer under partial information. Insur. Math. Econ. 65, 66–76 (2015). MR3430397. https://doi.org/10.1016/j.insmatheco.2015.08.008
[19] 
Nguyen, S.L., Yin, G., Nguyen, D.T.: A general stochastic maximum principle for mean-field controls with regime switching. Appl. Math. Optim. 84, 3255–3294 (2021). MR4308229. https://doi.org/10.1007/s00245-021-09747-x
[20] 
Øksendal, B., Sulem, A.: Applied Stochastic Control of Jump Diffusions, 2nd edn. Springer, New York (2007). MR2322248. https://doi.org/10.1007/978-3-540-69826-5
[21] 
Pham, H.: Linear quadratic optimal control of conditional McKean-Vlasov equation with random coefficients and applications. Probab. Uncertain. Quant. Risk 1, 7 (2016). MR3583182. https://doi.org/10.1186/s41546-016-0008-x
[22] 
Peng, S.: A general stochastic maximum principle for optimal control problems. SIAM J. Control Optim. 28, 966–979 (1990). MR1051633. https://doi.org/10.1137/0328054
[23] 
Phelps, E.S., Pollak, R.A.: On second-best national saving and game-equilibrium growth. Rev. Econ. Stud. 35, 185–199 (1968). https://doi.org/10.2307/2296547
[24] 
Pollak, R.: Consistent planning. Rev. Financ. Stud. 35, 185–199 (1968)
[25] 
Rong, S.: Theory of Stochastic Differential Equations with Jumps and Applications: Mathematical and Analytical Techniques with Applications to Engineering. Springer, New York (2006). MR2160585
[26] 
Shen, Y., Siu, T.K.: The maximum principle for a jump-diffusion mean-field model and its application to the mean-variance problem. Nonlinear Anal. 86, 58–73 (2013). MR3053556. https://doi.org/10.1016/j.na.2013.02.029
[27] 
Shi, J., Wu, Z.: Backward stochastic differential equations with Markov switching driven by Brownian motion and Poisson random measure. Stoch. Int. J. Probab. Stoch. Process. 87(1), 1–29 (2015). MR3306809. https://doi.org/10.1080/17442508.2014.914514
[28] 
Strotz, R.: Myopia and inconsistency in dynamic utility maximization. Rev. Econ. Stud. 23, 165–180 (1955). https://doi.org/10.2307/2295722
[29] 
Song, Y., Tang, S., Wu, Z.: The maximum principle for progressive optimal stochastic control problems with random jumps. SIAM J. Control Optim. 58(4), 2171–2187 (2020). MR4127097. https://doi.org/10.1137/19M1292308
[30] 
Sun, Z., Guo, X.: Equilibrium for a time-inconsistent stochastic linear-quadratic control system with jumps and its application to the mean-variance problem. J. Optim. Theory Appl. 181(2), 383–410 (2019). MR3938474. https://doi.org/10.1007/s10957-018-01471-x
[31] 
Tang, S., Li, X.: Necessary conditions for optimal control of stochastic systems with random jumps. SIAM J. Control Optim. 32(5), 1447–1475 (1994). MR1288257. https://doi.org/10.1137/S0363012992233858
[32] 
Wang, T.: Uniqueness of equilibrium strategies in dynamic mean-variance problems with random coefficients. J. Math. Anal. Appl. 490(1), 124199 (2020). MR4099907. https://doi.org/10.1016/j.jmaa.2020.124199
[33] 
Wang, H., Wu, Z.: Partially observed time-inconsistency recursive optimization problem and application. J. Optim. Theory Appl. 161(2), 664–687 (2014). MR3193813. https://doi.org/10.1007/s10957-013-0326-4
[34] 
Wei, J., Wong, K.C., Yam, S.C.P., Yung, S.P.: Markowitz’s mean-variance asset-liability management with regime switching: a time-consistent approach. Insur. Math. Econ. 53(1), 281–291 (2013). MR3081480. https://doi.org/10.1016/j.insmatheco.2013.05.008
[35] 
Wu, Z., Wang, X.: FBSDE with Poisson process and its application to linear quadratic stochastic optimal control problem with random jumps. Acta Autom. Sin. 29, 821–826 (2003). MR2033363
[36] 
Yang, B.Z., He, X.J., Zhu, S.P.: Continuous time mean-variance-utility portfolio problem and its equilibrium strategy. Optimization. MR3175527. https://doi.org/10.1080/02331934.2021.1939339
[37] 
Yong, J.: A deterministic linear quadratic time-inconsistent optimal control problem. Math. Control Relat. Fields 1, 83–118 (2011). MR2822686. https://doi.org/10.3934/mcrf.2011.1.83
[38] 
Yong, J.: Linear quadratic optimal control problems for mean-field stochastic differential equations: time-consistent solutions. SIAM J. Control Optim. 51(4), 2809–2838 (2013). MR3072755. https://doi.org/10.1137/120892477
[39] 
Yong, J.: Time-inconsistent optimal control problems and the equilibrium HJB equation. Math. Control Relat. Fields 2(3), 271–329 (2012). MR2991570. https://doi.org/10.3934/mcrf.2012.2.271
[40] 
Yong, J., Zhou, X.Y.: Stochastic Controls: Hamiltonian Systems and HJB Equations. Springer, New York (1999). MR1696772. https://doi.org/10.1007/978-1-4612-1466-3
[41] 
Zhang, X., Sun, Z., Xiong, J.: A general stochastic maximum principle for a Markov regime switching jump-diffusion model of mean-field type. SIAM J. Control Optim. 56(4), 2563–2592 (2018). MR3828847. https://doi.org/10.1137/17M112395X
[42] 
Zhao, Q., Shen, Y., Wei, J.: Consumption-investment strategies with non-exponential discounting and logarithmic utility. Eur. J. Oper. Res. 238(3), 824–835 (2014). MR3214861. https://doi.org/10.1016/j.ejor.2014.04.034
[43] 
Zeng, Y., Li, Z.: Optimal time-consistent investment and reinsurance policies for mean-variance insurers. Insur. Math. Econ. 49, 145–154 (2011). MR2811903. https://doi.org/10.1016/j.insmatheco.2011.01.001
[44] 
Zeng, Y., Li, Z., Lai, Y.: Time-consistent investment and reinsurance strategies for mean-variance insurers with jumps. Insur. Math. Econ. 52(3), 498–507 (2013). MR3054742. https://doi.org/10.1016/j.insmatheco.2013.02.007
[45] 
Zhou, X.Y., Li, D.: Continuous-time mean-variance portfolio selection: a stochastic LQ framework. Appl. Math. Optim. 42, 19–33 (2000). MR1751306. https://doi.org/10.1007/s002450010003
[46] 
Zhou, X.Y., Yin, G.: Markowitzs mean-variance portfolio selection with regime switching: a continuous-time model. SIAM J. Control Optim. 42, 1466–1482 (2003). MR2044805. https://doi.org/10.1137/S0363012902405583

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Keywords
Stochastic maximum principle time-inconsistency LQ control problem equilibrium control variational inequality

MSC2010
93E20 60H30 93E99 60H10

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