This paper revisits the methodology of Stein (1975, 1986) for estimating a covariance matrix in the setting where the number of variables can be of the same magnitude as the sample size. Stein proposed to keep the eigenvectors of the sample covariance matrix but to shrink the eigenvalues. By...

In this paper we study the connection between matrix measures and random walks with a tridiagonal block transition matrix. We derive sufficient conditions such that the blocks of the n-step transition matrix of the Markov chain can be represented as integrals with respect to a matrix valued...

This paper draws attention to two important characteristics of knowledge which so far have been left unexplored, and proposes a new method to capture them in economic modeling with the help of vectors. The direction of the vector represents the knowledge's complementarity with other knowledge...

This paper builds a model in which clustering emerges as the equilibrium outcome driven by informational imperfections and the importance of knowledge and uncertainty in innovative production even when knowledge is fully exclusive and appropriable. This motive for clustering will be stronger the...

Banks could achieve substantial improvements of their portfolio credit risk assessment by estimating rating transition matrices within a time-continuous Markov model, thereby using continuous-time rating transitions provided by internal rating systems instead of discrete-time rating information....

The first three factors resulting from a principal components analysis of term structure data are in the literature typically interpreted as driving the level, slope and curvature of the term structure. Using slight generalisations of theorems from total positivity, we present sufficient...