数学系Seminar第1373期 Chance-constrained Optimization for Pension Fund Portfolios in the Presence of Default Risk

创建时间:  2016/12/01  龚惠英   浏览次数:   返回

报告主题:Chance-constrained Optimization for Pension Fund Portfolios in the Presence of Default Risk
报告人: Kok Lay Teo  教授 (Curtin University)
报告时间:2016年12月7日(周三)14:30
报告地点:校本部G507
邀请人:余长君
主办部门:永利数学系
报告摘要:In this talk, we consider the portfolio optimization problem for a pension fund consisting of various government and corporate bonds. The aim of the problem is to maximize the fund’s cash position at the end of the time horizon, while allowing for the possibility of bond defaults. We model this problem as a stochastic discrete-time optimal control problem with a chance constraint that ensures all future outgoing commitments can be met with suf?ciently high probability. We then introduce a corresponding deterministic formulation that is a conservative approximation of the original stochastic optimal control problem. This approximate problem can be solved using gradient-based optimization techniques. We conclude the paper with a simulation study.

欢迎教师、学生参加 !

上一条:数学系Seminar第1375期 The Applications of Tensor Eigenvalues, Positive Semi-Definite Tensors and Copositive Tensors in Physics

下一条:数学系Seminar第1374期 不同尺度耦合系统理论研究进展与展望


数学系Seminar第1373期 Chance-constrained Optimization for Pension Fund Portfolios in the Presence of Default Risk

创建时间:  2016/12/01  龚惠英   浏览次数:   返回

报告主题:Chance-constrained Optimization for Pension Fund Portfolios in the Presence of Default Risk
报告人: Kok Lay Teo  教授 (Curtin University)
报告时间:2016年12月7日(周三)14:30
报告地点:校本部G507
邀请人:余长君
主办部门:永利数学系
报告摘要:In this talk, we consider the portfolio optimization problem for a pension fund consisting of various government and corporate bonds. The aim of the problem is to maximize the fund’s cash position at the end of the time horizon, while allowing for the possibility of bond defaults. We model this problem as a stochastic discrete-time optimal control problem with a chance constraint that ensures all future outgoing commitments can be met with suf?ciently high probability. We then introduce a corresponding deterministic formulation that is a conservative approximation of the original stochastic optimal control problem. This approximate problem can be solved using gradient-based optimization techniques. We conclude the paper with a simulation study.

欢迎教师、学生参加 !

上一条:数学系Seminar第1375期 The Applications of Tensor Eigenvalues, Positive Semi-Definite Tensors and Copositive Tensors in Physics

下一条:数学系Seminar第1374期 不同尺度耦合系统理论研究进展与展望

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