This paper investigates, in a particular parametric framework, the geometric meaning of joint unpredictability for a bivariate discrete process. In particular, the paper provides a characterization of the joint unpredictability in terms of distance between information sets in an Hilbert space.

This paper aims to introduce a nonlinear model to forecast macroeconomic time series using a large number of predictors. The technique used to summarize the predictors in a small number of variables is Principal Component Analysis (PC), while the method used to capture nonlinearity is artificial...

We investigate the relationship between corporate social responsibility (CSR) and I/B/E/S analysts’ earnings per share (EPS) forecasts using a large sample of US firms for 1992–2011. Based on literature findings, we decompose the CSR effect into four factors: accounting opacity, corporate...