Infinite horizon backward stochastic Volterra integral equations and discounted control problems
ESAIM: Control, Optimisation and Calculus of Variations, Tome 27 (2021), article no. 101

Infinite horizon backward stochastic Volterra integral equations (BSVIEs for short) are investigated. We prove the existence and uniqueness of the adapted M-solution in a weighted L2-space. Furthermore, we extend some important known results for finite horizon BSVIEs to the infinite horizon setting. We provide a variation of constant formula for a class of infinite horizon linear BSVIEs and prove a duality principle between a linear (forward) stochastic Volterra integral equation (SVIE for short) and an infinite horizon linear BSVIE in a weighted L2-space. As an application, we investigate infinite horizon stochastic control problems for SVIEs with discounted cost functional. We establish both necessary and sufficient conditions for optimality by means of Pontryagin’s maximum principle, where the adjoint equation is described as an infinite horizon BSVIE. These results are applied to discounted control problems for fractional stochastic differential equations and stochastic integro-differential equations.

Reçu le :
Accepté le :
Première publication :
Publié le :
DOI : 10.1051/cocv/2021098
Classification : 60H20, 45G05, 49K45, 49N15
Keywords: Infinite horizon backward stochastic Volterra integral equation, stochastic Volterra integral equation, duality principle, discounted stochastic control
@article{COCV_2021__27_1_A103_0,
     author = {Hamaguchi, Yushi},
     title = {Infinite horizon backward stochastic {Volterra} integral equations and discounted control problems},
     journal = {ESAIM: Control, Optimisation and Calculus of Variations},
     year = {2021},
     publisher = {EDP-Sciences},
     volume = {27},
     doi = {10.1051/cocv/2021098},
     language = {en},
     url = {https://www.numdam.org/articles/10.1051/cocv/2021098/}
}
TY  - JOUR
AU  - Hamaguchi, Yushi
TI  - Infinite horizon backward stochastic Volterra integral equations and discounted control problems
JO  - ESAIM: Control, Optimisation and Calculus of Variations
PY  - 2021
VL  - 27
PB  - EDP-Sciences
UR  - https://www.numdam.org/articles/10.1051/cocv/2021098/
DO  - 10.1051/cocv/2021098
LA  - en
ID  - COCV_2021__27_1_A103_0
ER  - 
%0 Journal Article
%A Hamaguchi, Yushi
%T Infinite horizon backward stochastic Volterra integral equations and discounted control problems
%J ESAIM: Control, Optimisation and Calculus of Variations
%D 2021
%V 27
%I EDP-Sciences
%U https://www.numdam.org/articles/10.1051/cocv/2021098/
%R 10.1051/cocv/2021098
%G en
%F COCV_2021__27_1_A103_0
Hamaguchi, Yushi. Infinite horizon backward stochastic Volterra integral equations and discounted control problems. ESAIM: Control, Optimisation and Calculus of Variations, Tome 27 (2021), article no. 101. doi: 10.1051/cocv/2021098

[1] E. Abi Jaber, E. Miller and H. Pham, Linear–Quadratic control for a class of stochastic Volterra equations: solvability and approximation. Preprint (2020). | arXiv

[2] N. Agram, Dynamic risk measure for BSVIE with jumps and semimartingale issues. Stoch. Anal. Appl. 37 (2019) 361–376.

[3] N. Agram and B. Øksendal, Mallivain calculus and optimal control of stochastic Volterra equations. J. Optim. Theory Appl. 167 (2015) 1070–1094.

[4] J. Appleby, pth mean integrability and almost sure asymptotic stability of solutions of Itô–Volterra equations. J. Integral Equ. Appl. 15 (2003) 321–341.

[5] P. Beissner and E. Rosazza Gianin, The term structure of Sharpe ratios and arbitrage-free asset pricing in continuous time. Probab. Uncertain. Quantit. Risk 6 (2021) 23–52.

[6] M. A. Berger and V. J. Mizel, Volterra equations with Itô integrals—I. J. Integral Equ. 2 (1980) 187–245.

[7] S. Chen and J. Yong, A linear quadratic optimal control problem for stochastic Volterra integral equations. Control theory and related topics – in memory of professor Xunjing Li, Fudan university, China. (2007) 44–66.

[8] T. L. Cromer, Asymptotically periodic solutions to Volterra integral equations in epidemic models. J. Math. Anal. Appl. 110 (1985) 483–494.

[9] J. P. C. Dos Santos, H. Henríquez and E. Hernández, Existence results for neutral integro-differential equations with unbounded delay. J. Integr. Equ. Appl. 23 (2011) 289–330.

[10] M. Fuhrman and Y. Hu, Infinite horizon BSDEs in infinite dimensions with continuous driver and applications. J. Evol. Equ. 6 (2006) 459–484.

[11] M. Fuhrman and G. Tessitore Infinite horizon backward stochastic differential equations and elliptic equations in Hilbert spaces. Ann. Probab. 32 (2004) 607–660.

[12] J. Gatheral, T. Jaisson, and M. Rosenbaum, Volatility is rough. Quant. Finance 18 (2018) 933–949.

[13] Y. Hamaguchi, Extended backward stochastic Volterra integral equations and their applications to time-inconsistent stochastic recursive control problems. Math. Control Relat. Fields 11 (2021) 197–242.

[14] Y. Hamaguchi, On the maximum principle for optimal control problems of stochastic Volterra integral equations with delay. Preprint: (2021). | arXiv

[15] C. Hernández and D. Possamaï, Me, myself and I: a general theory of non-Markovian time-inconsistent stochastic control for sophisticated agents. Preprint: (2021). | arXiv

[16] H. Hilfer, Applications of Fractional Calculus in Physics. World Scientific, Singapore (2000).

[17] Y. Hu and B. Øksendal, Linear Volterra backward stochastic integral equations. Stochastic Process. Appl. 129 (2019) 626–633.

[18] A. A. Kilbas, H. M. Srivastava and J. J. Trujillo, Theory and Applications of Fractional Differential Equations. North-Holland, Amsterdam (2006).

[19] E. Kromer and L. Overbeck, Differentiability of BSVIEs and dynamic capital allocations. Int. J. Theor. Appl. Finance 20 (2017) 1–26.

[20] J. Lin, Adapted solution of a backward stochastic nonlinear Volterra integral equation. Stoch. Anal. Appl. 20 (2002) 165–183.

[21] P. Lin and J. Yong, Controlled singular Volterra integral equations and Pontryagin maximum principle. SIAM J. Control Optim. 58 (2020) 136–164.

[22] J. Ma and J. Yong, Forward-Backward Stochastic Differential Equations and Their Applications. Lecture Notes in Math. 1702, Springer-Verlag, New York (1999).

[23] X. Mao and M. Riedle, Mean square stability of stochastic Volterra integro-differential equations. Syst. Control Lett. 55 (2006) 459–465.

[24] B. Maslowski and P. Veverka, Sufficient stochastic maximum principle for discounted control problem. Appl. Math. Optim. 70 (2014) 225–252.

[25] C. Orrieri and P. Veverka, Necessary stochastic maximum principle for dissipative systems on infinite time horizon. ESAIM: COCV 23 (2017) 337–371.

[26] G. Pang and E. Pardoux, Functional limit theorems for non-Markovian epidemic models. Preprint: (2021). | arXiv

[27] E. Pardoux, BSDEs weak convergence and homogenizations of semilinear PDEs, in Nonlinear Analysis Differential Equations and Control, edited by F. H. Clark, R. J. Stern (1999) 503–509.

[28] S. Peng and Y. Shi, Infinite horizon forward-backward stochastic differential equations. Stochastic Process. Appl. 85 (2000) 75–92.

[29] R. Sakthivel, J. J. Nieto and N. I. Mahmudov, Approximate controllability of nonlinear deterministic and stochastic systems with unbounded delay. Taiwan J. Math. 14 (2010) 1777–1797.

[30] Y. Shi, T. Wang and J. Yong, Mean-field backward stochastic Volterra integral equations. Discrete Contin. Dyn. Syst. 18 (2013) 1929–1967.

[31] Y. Shi, T. Wang and J. Yong, Optimal control problems of forward-backward stochastic Volterra integral equations. Math. Control Relat. Fields 5 (2015) 613–649.

[32] H. Wang, J. Sun and J. Yong, Recursive utility processes, dynamic risk measures and quadratic backward stochastic Volterra integral equations. Appl. Math. Optim. 84 (2021) 145–190.

[33] H. Wang and J. Yong, Time-inconsistent stochastic optimal control problems and backward stochastic Volterra integral equations. ESAIM: COCV 27 (2021).

[34] H. Wang, J. Yong and J. Zhang, Path dependent Feynman–Kac formula for forward backward stochastic Volterra integral equations. To appear Ann. Inst. Henri Poincaré Probab. Stat. Preprint (2021). | arXiv

[35] T. Wang, Linear quadratic control problems of stochastic Volterra integral equations. ESAIM: COCV 24 (2018) 1849–1879.

[36] T. Wang, Necessary conditions of Pontraygin’s type for general controlled stochastic Volterra integral equations. ESAIM: COCV 26 (2020) 16.

[37] T. Wang and J. Yong, Comparison theorems for some backward stochastic Volterra integral equations. Stochastic Process. Appl. 125 (2015) 1756–1798.

[38] T. Wangand H. Zhang, Optimal control problems of forward-backward stochastic Volterra integral equations with closed control regions. SIAM J. Control Optim. 55 (2017) 2574–2602.

[39] Y. Wang, J. Xu and P. E. Kloeden, Asymptotic behavior of stochastic lattice systems with a Caputo fractional time derivative. Nonlinear Anal. 135 (2016) 205–222.

[40] Z. Wu and F. Zhang, Maximum principle for stochastic recursive optimal control problems involving impulse controls. Abstr. Appl. Anal. 32 (2012 1–16.

[41] J. Yin, On solutions of a class of infinite horizon FBSDE’s. Stat. Probab. Lett. 78 (2008) 2412–2419.

[42] J. Yong, Backward stochastic Volterra integral equations and some related problems. Stoch. Anal. Appl. 116 (2006) 779–795.

[43] J. Yong, Continuous-time dynamic risk measures by backward stochastic Volterra integral equations. Appl. Anal. 86 (2007) 1429–1442.

[44] J. Yong, Well-posedness and regularity of backward stochastic Volterra integral equations. Probab. Theory Related Fields 142 (2008) 2–77.

[45] J. Zhang, Backward Stochastic Differential Equations; From Linear to Fully Nonlinear Theory. Springer (2017).

Cité par Sources :

The author was supported by JSPS KAKENHI Grant Number JP21J00460.