Partial-least squares regression (PLS) is a statistical tool specifically designed to cope with problems like small datasets, missing values and the presence of multicollinearity . The paper proceeds first with a concise review of the PLS method.

We derive some decision rules to select best predictive regression models in a credibility context, that is, in a 'random effects' linear regression model with replicates. In contrast to usual model selection techniques on a collective level, our proposal allows to detect individual structures,...

...Allerdings existiert noch keine umfassende empirische Studie zum Einfluss der Corporate Governance auf den Unternehmenswertschweizerischer Firmen. Diese Lücke soll durch die vorliegende Arbeit geschlossen werden.

State price density (SPD) contains important information concerning market expectations. In existing literature, a constrained estimator of the SPD is found by nonlinear least squares in a suitable Sobolev space...

Classical regression analysis uses partial coefficients to measure the influences of some variables(regressors) on another variable (regressand). However, a descriptive point of viewshows that these coefficients are very bad measures of influence. Their interpretation as anaverage change of the...

We characterize the robustness of subsampling procedures by deriving a general formula for the breakdown point of subsampling quantiles. This breakdown point can be very low for moderate subsampling block sizes, which implies the fragility of subsampling procedures, even if they are applied to...

The term structure of American interest rates is filtered to reduce the influence of cross correlations and auto correlations on its factors. A three-factor model is fitted to the filtered data. Contrary to most studies of the term structure on monthly data, performing statistical tests we...

Institutional but also private investors have often limited flexibility in timing their investment decision. Therefore, they look for investments that would ideally be independent of the timing decision. We introduce a new class of derivative products whose payoff is linked to the trend of the...

We systematically examine the comparative predictive performance of a number of alternativelinear and non-linear models for stock and bond returns in the G7 countries. Besides Markovswitching, threshold autoregressive (TAR), and smooth transition autoregressive (STAR) regimeswitching...