A similarity measurement for time series and its application to the stock market

作者：

Highlights：

• Reflecting the personalization of stock time series by weighting the time series.

• Utilizing dynamic time warping to cope with time shifts and warpings.

• Embedding Canberra distance for eliminating the impact of singularities.

摘要

•Reflecting the personalization of stock time series by weighting the time series.•Utilizing dynamic time warping to cope with time shifts and warpings.•Embedding Canberra distance for eliminating the impact of singularities.

论文关键词：Similarity measurements,Personalization,Multi-perspective,Stock prediction

论文评审过程：Received 29 November 2020, Revised 24 March 2021, Accepted 13 May 2021, Available online 18 May 2021, Version of Record 22 May 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.115217