Dec 13, 2014 · In this work, we show that the performance of the minimum-variance portfolio can be substantially improved by using regularization methods that ...

Nov 2, 2012 · We show empirically that these alternative penalties can lead to the construction of portfolios with superior out-of-sample performance.

Winker, 2015. "Constructing optimal sparse portfolios using regularization methods," Computational Management Science, Springer, vol. 12(3), pages 417-434, July ...

A new, simple type of penalty that explicitly considers financial information is proposed and then several alternative penalties are considered, ...

Recent studies show that imposing a penalty in form of a l1-norm of the asset weights regularizes the problem, thereby improving the out-of-sample performance ...

... The study explores optimal portfolio construction using regularization methods, albeit focusing on mean-variance constraints, but faces limitations due to ...

Jul 1, 2024 · By B. Fastrich, Sandra Paterlini and Peter Winker; Abstract: Mean-variance portfolios have been criticized because of unsatisfying ...

Recent studies show that imposing a penalty in form of a l1-norm of the asset weights regularizes the problem, thereby improving the out-of-sample performance ...

In this paper, we investigate four regularization techniques to stabilize the inverse of the covariance matrix: the ridge, spectral cut-off, Landweber-Fridman ...

In this paper, we investigate four regularization techniques to stabilize the inverse of the covariance matrix: the ridge, spectral cut-off, Landweber-Fridman ...