An online portfolio selection algorithm using clustering approaches and considering transaction costs

作者：

Highlights：

• In this paper, four new online portfolio selection algorithms have been proposed.

• In these algorithms, clustering techniques are used in pattern matching approaches.

• Transaction costs have been considered in the proposed algorithms.

• Based on the results, the proposed algorithms outperform the competing algorithms.

摘要

•In this paper, four new online portfolio selection algorithms have been proposed.•In these algorithms, clustering techniques are used in pattern matching approaches.•Transaction costs have been considered in the proposed algorithms.•Based on the results, the proposed algorithms outperform the competing algorithms.

论文关键词：Online portfolio selection,Algorithmic trading,Pattern-matching,Data mining,Clustering

论文评审过程：Received 30 May 2019, Revised 25 March 2020, Accepted 8 May 2020, Available online 12 May 2020, Version of Record 29 May 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113546