We propose an extension of a seasonal modulation smooth model with P-splines for times series data using a mixed model formulation. A smooth trend with seasonality decomposition can be estimated simultaneously. We extend the model to consider the forecasting of new future observations in the...

The motivation for this paper arises from an article written by Peña et al. [40] in 2010,where they propose the eigenvectors associated with the extreme values of a kurtosismatrix as interesting directions to reveal the possible cluster structure of a dataset. In recent years many research...

n this paper we attempt to establish a nexus between migration decisions and selfassessed happiness, where migration is taken as a mechanism for revealing preferences. The happiness literature has proposed both economic and non-economic determinants of happiness which are very similar to the...

Outliers of moderate magnitude cause large changes in financial time series of prices and returns and affect both the estimation of parameters and volatilities when fitting a GARCH-type model. The multivariate setting is still to be studied, but similar biases and impacts on correlation dynamics...

In this work we propose the combination of P-splines with traditional spatial econometric models in such a way that it allows for their representation as a mixed model. The advantages of combining these models include: (i) dealing with complex non-linear and non-separable trends, (ii) estimating...

This paper analyzes whether web search queries predict stock market activity in a sample of the largest European stocks. We provide evidence that i) an increase in web searches for stocks on Google engine is followed by a temporary increase in volatility and volume and a drop in cumulative...

Functional Regression has been an active subject of research in the last two decades but still lacks a secure variable selection methodology. Lasso is a well known effective technique for parameters shrinkage and variable selection in regression problems. In this work we generalize the Lasso...

The objective of this paper is to model and forecast all the components of a macro orbusiness variable. Our contribution concerns cases with a large number (hundreds) ofcomponents where multivariate approaches are not feasible. We extend in several directions the pairwise approach originally...

We carry out an analytical investigation on the optimal portfolio policy for a multiperiod mean-variance investor facing multiple risky assets. We consider the case with proportional, market impact, and quadratic transaction costs. For proportional transaction costs, we find that a buy-and-hold...

In this paper we explore, analyse and apply the change-points detection and location procedures to conditional heteroskedastic processes. We focus on processes that have constant conditional mean, but present a dynamic behavior in the conditional variance and which can also be affected by...