Robust enhanced index tracking problem with mixture of distributions

作者：

Highlights：

• A lower partial moment framework for the enhanced index tracking (EIT) problem.

• The robust EIT that deals with the uncertainty in the proportions of mixture distribution is introduced.

• The robust problem remains tractable under the type of Phi-divergence uncertainty.

• Experiments for tracking the FTSE100 index and S&P500 index.

摘要

•A lower partial moment framework for the enhanced index tracking (EIT) problem.•The robust EIT that deals with the uncertainty in the proportions of mixture distribution is introduced.•The robust problem remains tractable under the type of Phi-divergence uncertainty.•Experiments for tracking the FTSE100 index and S&P500 index.

论文关键词：Enhanced indexing,Lower partial moment,Mixture model,Robust optimization,ϕ-divergence,Sortino index

论文评审过程：Received 18 June 2021, Revised 12 January 2022, Accepted 28 March 2022, Available online 9 April 2022, Version of Record 22 April 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.117110