The estimation of multivariate GARCH time series models is a difficult task mainly due to the excessive parameterization exhibited by the problem, usually referred to as the "curse of dimensionality." For the VEC family, the number of parameters involved in the model grows as a polynomial of...

This paper presents the most comprehensive out-of-U.S.-sample examination of information variables and equity premium predictability by focusing on Canada to reassess the growing U.S.-based evidence casting doubt on predictability. Using monthly data for 36 variables from 1950 to 2013, we test...

This paper introduces a method based on the use of various linear and nonlinear state space models that uses non-synchronous data to extract global stochastic financial trends (GST). These models are specifically constructed to take advantage of the intraday arrival of closing information coming...

Reservoir computing is a recently introduced machine learning paradigm that has already shown excellent performances in the processing of empirical data. We study a particular kind of reservoir computers called time-delay reservoirs that are constructed out of the sampling of the solution of a...