This paper analyses the evolution of systematic risk of banking industries in eight advanced countries using weekly data from 1990 to 2012. The estimation of time-varying betas is done by means of a Bayesian state space model with stochastic volatility, whose results are contrasted with those of...

Suppose a fund manager uses predictors in changing port-folio allocations over time. How does predictability translate into portfolio decisions? To answer this question we derive a new model within the Bayesian framework, where managers are assumed to modulate the systematic risk in part by...

The study adds an empirical outlook on the predicting power of using data from the future to predict future returns. The crux of the traditional Capital Asset Pricing Model (CAPM) methodology is using historical data in the calculation of the beta coefficient. This study instead uses a battery...

In this work, a Capital Asset Pricing Model (CAPM) with time-varying betas is considered. These betas evolve over time, conditional on financial and non-financial variables. Indeed, the model proposed by Adrian and Franzoni (2009) is adapted to assess the behavior of some selected Brazilian...

We introduce a methodology which deals with possibly integrated variables in the specification of the betas of conditional asset pricing models. In such a case, any model which is directly derived by a polynomial approximation of the functional form of the conditional beta will inherit a...

We derive a nonparametric test for constant (continuous) beta over a fixed interval of time. Continuous beta is defined as the ratio of the continuous covariation between an asset and observable risk factor (e.g., the market return) and the continuous variation of the latter. Our test is based...

The R package partykit provides a flexible toolkit for learning, representing, summarizing, and visualizing a wide range of tree-structured regression and classification models. The functionality encompasses: (a) basic infrastructure for representing trees (inferred by any algorithm) so that...

The paper analyzes factors that influence the adoption of e-learning and gives an example of how to forecast technology adoption based on a post-hoc predictive segmentation using a classification and regression tree (CART). We find strong evidence for the existence of technological...

We use a machine-learning approach known as Boosted Regression Trees (BRT) to reexamine the usefulness of selected leading indicators for predicting recessions. We estimate the BRT approach on German data and study the relative importance of the indicators and their marginal effects on the...

Bush encroachment (BE) describes a global problem severely affecting savanna ecosystems in Africa. Invasive species and woody vegetation spread out in areas where they are not naturally occurring and suppress endemic vegetation, mainly grasses. Livestock is directly affected by decreasing...