The ideas of Markowitz indisputably constitute a milestone in portfolio theory, even though the resulting mean-variance portfolios typically exhibit an unsatisfying out-of-sample performance, especially when the number of securities is large and that of observations is not. The bad performance is caused by estimation errors in the covariance matrix and in the expected return vector that can deposit unhindered in the portfolio weights. 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 of the optimized portfolios. Simultaneously, l1-regularization selects a subset of assets to invest in from a pool of candidates that is often very larg...
Modern Portfolio Theory (MPT) has been the canonical theoretical model of portfolio selection for ov...
Portfolio optimization approaches inevitably rely on multivariate modeling of markets and the econom...
There has been much research about regularizing optimal portfolio selections through $\ell_1$ norm a...
The ideas of Markowitz indisputably constitute a milestone in portfolio theory, even though the resu...
The ideas of Markowitz indisputably constitute a milestone in portfolio theory, even though the resu...
Markowitz portfolios often result in an unsatisfying out-of-sample performance, due to the presence ...
The mean-variance principle of Markowitz (1952) for portfolio selection gives disappointing results ...
UnrestrictedPenalization or regularization is an important integration to the traditional regression...
Abstract In this paper, we propose `p-norm regularized models to seek near-optimal sparse portfolios...
In this paper, we propose `p-norm regularized models to seek near-optimal sparse portfolios. These s...
Financial crises are typically characterized by highly positively correlated asset returns due to th...
Optimal portfolio asset allocation has played an increasingly important role in finance ever since M...
In this short report, we discuss how coordinate-wise descent algorithms can be used to solve minimum...
We introduce a financial portfolio optimization framework that allows to automatically select the re...
We consider the l1 -regularized Markowitz model, where a l1 -penalty term is added to the objecti...
Modern Portfolio Theory (MPT) has been the canonical theoretical model of portfolio selection for ov...
Portfolio optimization approaches inevitably rely on multivariate modeling of markets and the econom...
There has been much research about regularizing optimal portfolio selections through $\ell_1$ norm a...
The ideas of Markowitz indisputably constitute a milestone in portfolio theory, even though the resu...
The ideas of Markowitz indisputably constitute a milestone in portfolio theory, even though the resu...
Markowitz portfolios often result in an unsatisfying out-of-sample performance, due to the presence ...
The mean-variance principle of Markowitz (1952) for portfolio selection gives disappointing results ...
UnrestrictedPenalization or regularization is an important integration to the traditional regression...
Abstract In this paper, we propose `p-norm regularized models to seek near-optimal sparse portfolios...
In this paper, we propose `p-norm regularized models to seek near-optimal sparse portfolios. These s...
Financial crises are typically characterized by highly positively correlated asset returns due to th...
Optimal portfolio asset allocation has played an increasingly important role in finance ever since M...
In this short report, we discuss how coordinate-wise descent algorithms can be used to solve minimum...
We introduce a financial portfolio optimization framework that allows to automatically select the re...
We consider the l1 -regularized Markowitz model, where a l1 -penalty term is added to the objecti...
Modern Portfolio Theory (MPT) has been the canonical theoretical model of portfolio selection for ov...
Portfolio optimization approaches inevitably rely on multivariate modeling of markets and the econom...
There has been much research about regularizing optimal portfolio selections through $\ell_1$ norm a...