The paper discusses finite sample properties of optimal portfolio weights, estimated expected portfolio return, and portfolio variance. The first estimator assumes the asset returns to be independent, while the second takes them to be predictable using a linear regression model. The third and the fourth approaches are based on a shrinkage technique and a Bayesian methodology, respectively. In the first two cases, we establish the moments of the weights and the portfolio returns. A consistent estimator of the shrinkage parameter for the third estimator is then derived. The advantages of the shrinkage approach are assessed in an empirical study.Optimal portfolio weights, finite sample moments, shrinkage
Optimal portfolio selection problems are determined by the (unknown) parameters of the data generat...
We study the realized variance of sample minimum variance portfolios of arbitrarily high dimension. ...
We derive analytical expressions for the risk of an investor’s expected utility under parameter unce...
We carry out a comprehensive investigation of shrinkage estimators for asset allocation, and we find...
Shrinkage estimators is an area widely studied in statistics. In this paper, we contemplate the role...
The problem of how to determine portfolio weights so that the variance of portfolio returns is minim...
In this paper, we provide a general framework for identifying portfolios that perform well out-of-sa...
Recently, the shrinkage approach has increased its popularity in theoretical and applied statistics,...
The mean-variance approach was first proposed by Markowitz (1952), and laid the foundation of the mo...
International audience—We study the design of portfolios under a minimum risk criterion. The perform...
International audienceWe study the design of portfolios under a minimum risk criterion. The performa...
We consider the problem of maximizing the out-of-sample Sharpe ratio when portfolio weights have to ...
Abstract—We study the design of portfolios under a minimum risk criterion. The performance of the op...
The concept of portfolio optimization has been widely studied in the academy and implemented in the ...
In this article, we estimate the mean-variance portfolio in the high-dimensional case using the rece...
Optimal portfolio selection problems are determined by the (unknown) parameters of the data generat...
We study the realized variance of sample minimum variance portfolios of arbitrarily high dimension. ...
We derive analytical expressions for the risk of an investor’s expected utility under parameter unce...
We carry out a comprehensive investigation of shrinkage estimators for asset allocation, and we find...
Shrinkage estimators is an area widely studied in statistics. In this paper, we contemplate the role...
The problem of how to determine portfolio weights so that the variance of portfolio returns is minim...
In this paper, we provide a general framework for identifying portfolios that perform well out-of-sa...
Recently, the shrinkage approach has increased its popularity in theoretical and applied statistics,...
The mean-variance approach was first proposed by Markowitz (1952), and laid the foundation of the mo...
International audience—We study the design of portfolios under a minimum risk criterion. The perform...
International audienceWe study the design of portfolios under a minimum risk criterion. The performa...
We consider the problem of maximizing the out-of-sample Sharpe ratio when portfolio weights have to ...
Abstract—We study the design of portfolios under a minimum risk criterion. The performance of the op...
The concept of portfolio optimization has been widely studied in the academy and implemented in the ...
In this article, we estimate the mean-variance portfolio in the high-dimensional case using the rece...
Optimal portfolio selection problems are determined by the (unknown) parameters of the data generat...
We study the realized variance of sample minimum variance portfolios of arbitrarily high dimension. ...
We derive analytical expressions for the risk of an investor’s expected utility under parameter unce...