Title
Explicit Solution for Constrained Stochastic Linear-Quadratic Control with Multiplicative Noise.
Abstract
We study in this paper a class of constrained linear-quadratic (LQ) optimal control problem formulations for the scalar-state stochastic system with multiplicative noise, which has various applications, especially in the financial risk management. The linear constraint on both the control and state variables considered in our model destroys the elegant structure of the conventional LQ formulation and has blocked the derivation of an explicit control policy so far in the literature. We successfully derive in this paper the analytical control policy for such a class of problems by utilizing the state separation property induced from its structure. We reveal that the optimal control policy is a piece-wise affine function of the state and can be computed off-line efficiently by solving two coupled Riccati equations. Under some mild conditions, we also obtain the stationary control policy for infinite time horizon. We demonstrate the implementation of our method via some illustrative examples and show how to calibrate our model to solve dynamic constrained portfolio optimization problems.
Year
Venue
Field
2017
arXiv: Systems and Control
Affine transformation,Mathematical optimization,Time horizon,Optimal control,Control theory,Separation property,Portfolio optimization,State variable,Mathematics,Multiplicative noise,Stochastic control
DocType
Volume
Citations 
Journal
abs/1709.05529
0
PageRank 
References 
Authors
0.34
5
4
Name
Order
Citations
PageRank
Weipin Wu100.34
Jianjun Gao25111.33
Duan Li35612.31
Yun Shi4123.60