An asymmetric information non-zero sum differential game of mean-field backward stochastic differential equation with applications

Huang, Pengyan; Wang, Guangchen; Zhang, Huanjun

doi:10.1186/s13662-019-2166-5

Cited by 9 publications

(8 citation statements)

References 26 publications

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“…On account of the abstract concept of the sub-σ-algebra G 1 and G 2 which is not generated by known Brownian motion or observation process, we have difficulty in obtaining the specific filtering equations under the general information filtration. Same phenomenon can also be seen in the reference such as [17], [34] and [35]. Therefore, we only consider the special case when the follower's information filtration is…”

mentioning

confidence: 87%

“…However, our problems are essentially different in that we study the pension fund problem in the framework of Stackelberg game of BSDE with partial information. For more details about financial applications for partial information differential games, please refer to Wang and Yu [41], Shi and Wang [32], Huang et al [17], Xiong et al [43], etc.…”

Section: 2mentioning

confidence: 99%

“…Du and Wu [10] investigated a kind of Stackelberg game of mean-field BSDEs. Huang et al [17] focused on a kind of non-zero sum differential game driven by mean-field BSDE with asymmetric information.…”

mentioning

confidence: 99%

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A stackelberg game of backward stochastic differential equations with partial information

Zheng¹,

Shi²

2021

MCRF

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<p style='text-indent:20px;'>This paper is concerned with a Stackelberg game of backward stochastic differential equations (BSDEs) with partial information, where the information of the follower is a sub-<inline-formula><tex-math id="M1">\begin{document}$ \sigma $\end{document}</tex-math></inline-formula>-algebra of that of the leader. Necessary and sufficient conditions of the optimality for the follower and the leader are first given for the general problem, by the partial information stochastic maximum principles of BSDEs and forward-backward stochastic differential equations (FBSDEs), respectively. Then a linear-quadratic (LQ) Stackelberg game of BSDEs with partial information is investigated. The state estimate feedback representation for the optimal control of the follower is first given via two Riccati equations. Then the leader's problem is formulated as an optimal control problem of FBSDE. Four high-dimensional Riccati equations are introduced to represent the state estimate feedback for the optimal control of the leader. Theoretic results are applied to a pension fund management problem of two players in the financial market.</p>

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mentioning

confidence: 87%

Section: 2mentioning

confidence: 99%

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A stackelberg game of backward stochastic differential equations with partial information

Zheng¹,

Shi²

2021

MCRF

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show abstract

“…However, our problems are essentially different in that we study the pension fund problem in the framework of Stackelberg game of BSDE with partial information. For more details about financial applications for partial information differential games, please refer to Wang and Yu [40], Shi and Wang [31], Huang et al [17], Xiong et al [42], etc.…”

Section: Application To Pension Fund Management Problemmentioning

confidence: 99%

“…Du and Wu [10] investigated a new kind of Stackelberg differential game of mean-field BSDEs. Huang et al [17] focused on a kind of non-zero sum differential game driven by mean-field BSDE with asymmetric information.…”

Section: Introductionmentioning

confidence: 99%

A Stackelberg Game of Backward Stochastic Differential Equations with Applications

Zheng

Shi

2019

Dyn Games Appl

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This paper is concerned with a Stackelberg game of backward stochastic differential equations (BSDEs) with partial information, where the information of the follower is a sub-σ-algebra of that of the leader. Necessary and sufficient conditions of the optimality for the follower and the leader are first given for the general problem, by the partial information stochastic maximum principles of BSDEs and forward-backward stochastic differential equations (FBSDEs), respectively. Then a linear-quadratic (LQ) Stackelberg game of BSDEs with partial information is investigated. The state estimate feedback representation for the optimal control of the follower is first given via two Riccati equations. Then the leader's problem is formulated as an optimal control problem of FBSDE. Four high-dimensional Riccati equations are introduced to represent the state estimate feedback for the optimal control of the leader. Theoretic results are applied to a pension fund management problem of two players in the financial market.

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A partial information linear-quadratic optimal control problem of backward stochastic differential equation with its applications

Huang

Wang

Zhang

2020

Sci. China Inf. Sci.

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An asymmetric information non-zero sum differential game of mean-field backward stochastic differential equation with applications

Cited by 9 publications

References 26 publications

A stackelberg game of backward stochastic differential equations with partial information

A stackelberg game of backward stochastic differential equations with partial information

A Stackelberg Game of Backward Stochastic Differential Equations with Applications

A partial information linear-quadratic optimal control problem of backward stochastic differential equation with its applications

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