113 citations · 569 across the 28 of their papers we have counts for
8 papers · 1 filter
Consistent Estimation of the High-Dimensional Efficient Frontier
Taras Bodnar, Nikolaus Hautsch, Yarema Okhrin +1
In this paper, we analyze the asymptotic behavior of the main characteristics of the mean-variance efficient frontier employing random matrix theory. Our particular interest covers…
Two is better than one: Regularized shrinkage of large minimum variance portfolio
Taras Bodnar, Nestor Parolya, Erik Thorsén
In this paper we construct a shrinkage estimator of the global minimum variance (GMV) portfolio by a combination of two techniques: Tikhonov regularization and direct shrinkage of…
Is the empirical out-of-sample variance an informative risk measure for the high-dimensional portfolios?
Taras Bodnar, Nestor Parolya, Erik Thorsén
The main contribution of this paper is the derivation of the asymptotic behaviour of the out-of-sample variance, the out-of-sample relative loss, and of their empirical counterpart…
Dynamic Shrinkage Estimation of the High-Dimensional Minimum-Variance Portfolio
Taras Bodnar, Nestor Parolya, Erik Thorsen
In this paper, new results in random matrix theory are derived which allow us to construct a shrinkage estimator of the global minimum variance (GMV) portfolio when the shrinkage t…
Bayesian mean-variance analysis: Optimal portfolio selection under parameter uncertainty
David Bauder, Taras Bodnar, Nestor Parolya +1
The paper solves the problem of optimal portfolio choice when the parameters of the asset returns distribution, like the mean vector and the covariance matrix are unknown and have…
Tests for the weights of the global minimum variance portfolio in a high-dimensional setting
Taras Bodnar, Solomiia Dmytriv, Nestor Parolya +1
In this study, we construct two tests for the weights of the global minimum variance portfolio (GMVP) in a high-dimensional setting, namely, when the number of assets depends o…
Optimal shrinkage-based portfolio selection in high dimensions
Taras Bodnar, Yarema Okhrin, Nestor Parolya
In this paper we estimate the mean-variance portfolio in the high-dimensional case using the recent results from the theory of random matrices. We construct a linear shrinkage esti…
Estimation of the Global Minimum Variance Portfolio in High Dimensions
Taras Bodnar, Nestor Parolya, Wolfgang Schmid
We estimate the global minimum variance (GMV) portfolio in the high-dimensional case using results from random matrix theory. This approach leads to a shrinkage-type estimator whic…