The Software fault prediction (SFP) target is to distinguish between faulty and non-faulty
modules. The prediction model's performance is vulnerable to the class imbalance issue in …

This paper studies a distributionally robust portfolio optimization model with a cardinality
constraint for limiting the number of invested assets. We formulate this model as a mixed …

The inverse of the standard estimate of covariance matrix is frequently used in the portfolio
theory to estimate the optimal portfolio weights. For this problem, the distribution of the linear …

In this paper, 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 p depends on the …

The goal of clustering is to identify common structures in a data set by forming groups of
homogeneous objects. The observed characteristics of many economic time series …

Covariance matrix of the asset returns plays an important role in the portfolio selection. A
number of papers is focused on the case when the covariance matrix is positive definite. In …

In this paper we derive the finite-sample distribution of the estimated weights of the tangency
portfolio when both the population and the sample covariance matrices are singular. These …

The problem of estimating a normal covariance matrix is considered from a decision-
theoretic point of view, where the dimension of the covariance matrix is larger than the …

In this paper, we consider optimal portfolio selection when the covariance matrix of the asset
returns is rank-deficient. For this case, the original Markowitz'problem does not have a …

Recently, a test dealing with the linear hypothesis for the global minimum variance portfolio
weights was obtained under the assumption of non-singular covariance matrix. However …