73 citations · 87 across the 4 of their papers we have counts for
4 papers
Cross-validation based Nonlinear Shrinkage
Daniel Bartz
Many machine learning algorithms require precise estimates of covariance matrices. The sample covariance matrix performs poorly in high-dimensional settings, which has stimulated t…
Validity of time reversal for testing Granger causality
Irene Winkler, Danny Panknin, Daniel Bartz +2
Inferring causal interactions from observed data is a challenging problem, especially in the presence of measurement noise. To alleviate the problem of spurious causality, Haufe et…
Multi-Target Shrinkage
Daniel Bartz, Johannes Höhne, Klaus-Robert Müller
Stein showed that the multivariate sample mean is outperformed by "shrinking" to a constant target vector. Ledoit and Wolf extended this approach to the sample covariance matrix an…
Directional Variance Adjustment: improving covariance estimates for high-dimensional portfolio optimization
Daniel Bartz, Kerr Hatrick, Christian W. Hesse +2
Robust and reliable covariance estimates play a decisive role in financial and many other applications. An important class of estimators is based on Factor models. Here, we show by…