@inproceedings{30e6bb37b98f4d57ab590d8d1b8a6733,
title = "Multiperiod mean-CVaR portfolio selection",
abstract = "Due to the time inconsistency issue of multiperiod mean- CVaR model, two important policies of the model with finite states, the pre-committed policy and the time consistent policy, are derived and discussed. The pre-committed policy, which is global optimal for the model, is solved through linear programming. A detailed analysis shows that the pre-committed policy doesn{\textquoteright}t satisfy time consistency in efficiency either, i.e., the truncated pre-committed policy is not efficient for the remaining short term mean-CVaR problem. The time consistent policy, which is the subgame Nash equilibrium policy of the multiperson game reformulation of the model, takes a piecewise linear form of the current wealth level and the coefficients can be derived by a series of integer programming problems and two linear programming problems. The difference between two polices indicates the degree of time inconsistency.",
keywords = "Integer programming, Linear programming, Mean-CVaR, Pre-committed policy, Time consistency in efficiency, Time consistent policy",
author = "Xiangyu Cui and Yun Shi",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 3rd International Conference on Modelling, Computation and Optimization in Information Systems and Management Sciences, MCO 2015 ; Conference date: 11-05-2015 Through 13-05-2015",
year = "2015",
doi = "10.1007/978-3-319-18161-5\_25",
language = "英语",
isbn = "9783319181608",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
pages = "293--304",
editor = "Nguyen, \{Ngoc Thanh\} and \{Le Thi\}, \{Hoai An\} and Dinh, \{Tao Pham\}",
booktitle = "Modelling, Computation and Optimization in Information Systems and Management Sciences - Proceedings of the 3rd International Conference on Modelling, Computation and Optimization in Information Systems and Management Sciences, MCO 2015",
address = "德国",
}