A stochastic receding horizon control approach to constrained index tracking

被引：24

作者：

Primbs J.A. ^{[1
]}

Sung C.H. ^{[2
]}

机构：

[1] Management Science and Engineering, Stanford University, Stanford, CA 94305

[2] Barclay's Global Investors, San Francisco, CA

来源：

Asia-Pacific Financial Markets | 2008年 / 15卷 / 1期

关键词：

Computational methods; Constraints; Index tracking; Receding horizon control; Stochastic control;

D O I：

10.1007/s10690-008-9073-1

中图分类号：

学科分类号：

摘要：

This paper develops stochastic receding horizon control for a constrained index tracking problem. By modeling the asset dynamics in the problems as a linear system subject to state and control multiplicative noise, and approximating linear chance constraints with quadratic expectation constraints, we show that index tracking can be approached using stochastic receding horizon control. In particular, we use a closed loop version of stochastic receding horizon control where the on-line optimization is solved as a semi-definite program. Numerical examples demonstrate the computations involved in these problems and indicate that stochastic receding horizon control is a promising new approach to constrained index tracking. © 2008 Springer Science+Business Media, LLC.

引用

页码：3 / 24

页数：21

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