Stability improvement for index tracking during a healthcare crisis using a dual decomposition approach
作者:Wu, DX (Wu, Dexiang) [1]
卷175
文献号108820
DOI: 10.1016/j.cie.2022.108820
出版时间: JAN 2023
已索引: 2023-03-10
文献类型: Article
摘要
This paper developed a factor-based robust approach to improve the tracking fund's stability. Similar to the financial crisis, the recent coronavirus pandemic amplify the global market volatility significantly, which suggests that healthcare-based factor can be used to hedge against the jump risk. The index tracking fund is constructed by a developed cardinality constrained conic programming. To overcome the large-scale computational challenge, we decompose the problem into two simplified cases and quickly calculate the tighter lower bound and its feasible upper bound. In addition, a subgradient-based inequalities are derived to exclude the suboptimal points that have been traveled in previous iterations. It turns out that the proposed model, along with the designed solving technique, can be used as an alternative to build reliable tracking portfolios. We demonstrate the effectiveness and robustness of the proposed method by testing different large real data sets.
作者关键词: Enhanced index tracking; Portfolio stability; Cardinality constrained conic programming; Dual decomposition
通讯作者地址
Wu, Dexiang
(通讯作者)
Beihang Univ, Sch Econ & Management, Beijing 100191, Peoples R China
地址
1 Beihang Univ, Sch Econ & Management, Beijing 100191, Peoples R China
电子邮件地址dextre.wu@alum.utoronto.ca
原文地址：
https://www.sciencedirect.com/science/article/pii/S0360835222008087?via%3Dihub
