This paper proposes a Bayesian method of performance evaluation for investment managers. We begin with a flexible set of prior beliefs that can be elicited without any reference to probability distributions or their parameters. We then combine these prior beliefs with a general multi-factor...

A robust principal component analysis can be easily performed by computing the eigenvalues and eigenvectors of a robust estimator of the covariance or correlation matrix. In this paper the authors derive the influence functions and the corresponding asumptotic variances for these robust...

The setup of our study is the Principal Component Analysis for dependent Hilbert space valued random vectors with examples taken from the ARH (1) model. We prove that convergence rates of the j ^(th) empirical random projection operator II from n to j for almost sure convergence and convergence...

The aim of this paper is to relate some recent results on Levy processes (see Schoutens and Teugels, 1998) to a recent study of the author (1996) on multidimensional natural exponential families. In this way, we consider a natural construction of Sheffer polynomials associated to a d-dimensional...

In optimization, objective functions which are both pseudoconvex and pseudoconcave have extensively been studied. Generalizing these results, we characterize pseudomonotone maps F where also -F is pseudomonotone and explore their properties in variational inequality problems. In particular, we...

Duality is studied for an abstract equilibrium problem which includes, among others, optimization problems and variational inequality problems. Follwing different schemes, various duals are proposed and primal-dual relationships are established under certaing generalized convexity and...

Five decades ago, Bhattacharyya established a series of lower bounds for the variance of an unbiased estimator, since then called the Bhattacharyya bounds. In 1974 Blight and Rao have shown that the series of Bhattacharyya bounds converges to the variance of the best unbiased estimator. In this...

New results in the asymptotic theory of Markov processes are applied to analysis of the long-run behaviour exhibited by optimal growth models with unbounded productivity shock. The techniques developed here are geometrically intuitive, and are shown to imply global stability for a popular model...

The traditional textbook approach to avoiding the dummy trap problem is to delete a category from each qualitative variable. We illustrate an alternative constraint introduced by Sweeney and Ulveling (1972) which can be used to transform conventional dummy variable coefficients. This constraint...

Bergin and Lipman (1996) show that the refinement effect from the random mutations in the adaptive population dynamics in Kandori, Mailath and Rob (1993) and Young (1993) is due to restrictions on how these mutation rates vary across population states. We here model mutation rates as...