Dimension reduction in mean-variance portfolio optimization

作者：

Highlights：

• Novel methodology for reducing dimensionality in the mean-variance model.

• Notable increase in efficiency as NPCA integrates to the portfolio optimization.

• Comparative analysis of backtesting results for 300 tangency portfolios.

摘要

•Novel methodology for reducing dimensionality in the mean-variance model.•Notable increase in efficiency as NPCA integrates to the portfolio optimization.•Comparative analysis of backtesting results for 300 tangency portfolios.

论文关键词：Non-negative principal components analysis,Non-negative matrix factorization,Multivariate time series,Portfolio backtesting,Statistical variance procedure

论文评审过程：Received 4 March 2017, Revised 18 August 2017, Accepted 8 September 2017, Available online 19 September 2017, Version of Record 26 September 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2017.09.009