Title
A Maximum Principle for Partial Information Backward Stochastic Control Problems with Applications
Abstract
This paper studies the partial information control problems of backward stochastic systems. There are three major contributions made in this paper: (i) First, we obtain a new stochastic maximum principle for partial information control problems. Our method relies on a direct calculation of the derivative of the cost functional. (ii) Second, we introduce two classes of partial information linear-quadratic backward control problems for the first time and then investigate them using the maximum principle. Complete and explicit solutions are obtained in terms of some forward and backward stochastic differential filtering equations. (iii) Last but not least, we study a class of full information stochastic pension fund optimization problems which can be viewed as a special case of our general partial information ones. Applying the aforementioned maximum principle, we derive the optimal contribution policy in closed-form and present some related economic remarks.
Year
DOI
Venue
2009
10.1137/080738465
SIAM J. Control and Optimization
Keywords
Field
DocType
partial information backward stochastic,general partial information,full information stochastic pension,partial information linear-quadratic,paper study,maximum principle,stochastic system,new stochastic maximum principle,stochastic differential,partial information control problem,aforementioned maximum principle,control problems,stochastic control
Differential equation,Mathematical optimization,Maximum principle,Optimal control,Stochastic partial differential equation,Stochastic programming,Optimization problem,Mathematics,Complete information,Stochastic control
Journal
Volume
Issue
ISSN
48
4
0363-0129
Citations 
PageRank 
References 
19
2.38
2
Authors
3
Name
Order
Citations
PageRank
Jianhui Huang18114.20
Guangchen Wang215318.94
Jie Xiong379865.00