Functional data are difficult to manage for many traditional statistical techniques given their very high (or intrinsically infinite) dimensionality. The reason is that functional data are essentially functions and most algorithms are designed to work with (low) finite-dimensional vectors....

When observed over a large panel, measures of risk (such as realized volatilities) usually exhibit a secular trend around which individual risks cluster. In this article we propose a vector Multiplicative Error Model achieving a decomposition of each risk measure into a common systematic and an...

In this paper we focus on the impact of additive level outliers on the calculation of risk measures, such as minimum capital risk requirements, and compare four alternatives of reducing these measures' estimation biases. The first three proposals proceed by detecting and correcting outliers...

New evidence on the way oil price fluctuations affect international stock markets is provided in analysis of the exposure of 43 stock markets. Oil price spikes depress international stock markets, but oil price drops do not necessarily increase stock market returns. Moreover, the volatility of...

This paper presents an algebraic analysis using Matrix Padé Aproximation to improve the identification stage of the proposal in [6] on Scalar Component Models, specifically as it refers to the choice of a parameter they denote h. The original methodology in [6] is based on the construction and...

It is usually considered that the proportion of handicapped people grows with age. Namely, the older the man/woman is, the more level of disability he/she suffers. However, empirical evidence shows that this assessment is not always true, or at least, it is not true in the Spanish population....

Bacterial growth models are commonly used in food safety. Such models permit the prediction of microbial safety and the shelf life of perishable foods. In this paper, we study the problem of modelling bacterial growth when we observe multiple experimental results under identical environmental...

We consider Bayesian estimation of the coefficients in a linear regression model, using a conjugate prior, when certain additional exact restrictions are placed on these coefficients. The bias and matrix mean squared errors of the Bayes and restricted Bayes estimators are compared when these...

Extreme value theory (EVT) measures the behavior of extreme observations on a random variable. EVT in risk management, an approach to modeling and measuring risks under rare events, has taken on a prominent role in recent years. This paper contributes to the literature in two respects by...

Given a set of continuous variables with missing data, we prove in this paper that the iterative application of a simple “least-squares estimation/multivariate normal simulation” procedure produces an efficient parameters estimator. There are two main assumptions behind our proof: (1) the...