Conditional LQ time-inconsistent Markov-switching stochastic optimal control problem for diffusion with jumps        
        
    
        Volume 9, Issue 2 (2022), pp. 157–205
            
    
                    Pub. online: 3 February 2022
                    
        Type: Research Article
            
                
            
Open Access
        
            
    
                Received
12 October 2021
                                    12 October 2021
                Revised
9 January 2022
                                    9 January 2022
                Accepted
12 January 2022
                                    12 January 2022
                Published
3 February 2022
                    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
 Basak, S., Chabakauri, G.: Dynamic mean-variance asset allocation. Rev. Financ. Stud. 23, 2970–3016 (2010). https://doi.org/10.1093/rfs/hhq028
 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
 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
 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
 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
 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
 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
 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
 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
 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
 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
 Elliott, R.J., Aggoun, L., Moore, J.B.: Hidden Markov Models: Estimation and Control. Springer, New York (1994). MR1323178
 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
 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
 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
 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
 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
 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
 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
 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
 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
 Rong, S.: Theory of Stochastic Differential Equations with Jumps and Applications: Mathematical and Analytical Techniques with Applications to Engineering. Springer, New York (2006). MR2160585
 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
 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
 Strotz, R.: Myopia and inconsistency in dynamic utility maximization. Rev. Econ. Stud. 23, 165–180 (1955). https://doi.org/10.2307/2295722
 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
 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
 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
 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
 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
 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
 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
 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
 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
 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
 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
 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
 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
 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
 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
 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
 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
 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