Publications des institutions partenaires
Assessing multivariate predictors of financial market movements: A latent factor framework for ordinal data
Much of the trading activity in Equity markets is directed to brokerage houses. In exchange they provide so-called "soft dollars" which basically are amounts spent in "research" for identifying profitable trading opportunities. Soft dollars represent about USD 1 out of every USD 10 paid in commissions. Obviously they are costly, and it is interesting for an...
Institution partenaire
English / 01/01/2008
Robust Stochastic Dominance: A Semi-Parametric Approach
Lorenz curves and second-order dominance criteria, the fundamental tools for stochastic dominance, are known to be sensitive to data contamination in the tails of the distribution. We propose two ways of dealing with the problem: (1) Estimate Lorenz curves using parametric models and (2) combine empirical estimation with a parametric (robust) estimation of the upper tail of the...
Institution partenaire
English / 01/01/2007
Spatial Dependence, Housing Submarkets and House Price Prediction
This paper compares alternative methods of controlling for the spatial dependence of house prices in a mass appraisal context. Explicit modeling of the error structure is characterized as a relatively fluid approach to defining housing submarkets. This approach allows the relevant submarket to vary from house to house and for transactions involving other dwellings in each submarket...
Institution partenaire
English / 01/01/2007
De-Biasing Weighted MLE via Indirect Inference: The Case of Generalized Linear Latent Variable Models
In this paper we study bias-corrections to the weighted MLE (Dupuis and Morgenthaler, 2002), a robust estimator simply defined through a weighted score function. Indeed, although the WMLE is relatively simple to compute, for most models it is not consistent and hence not very helpful. For example, the model we consider in this paper is the generalized linear latent variable model (...
Institution partenaire
English / 01/01/2007
Modelling Lorenz Curves: Robust and Semi-Parametric Issues
Modelling Lorenz curves (LC) for stochastic dominance comparisons is central to the analysis of income distribution. It is conventional to use non-parametric statistics based on empirical income cumulants which are in the construction of LC and other related second-order dominance criteria. However, although attractive because of its simplicity and its apparent flexibility, this...
Institution partenaire
English / 01/01/2007
Distributional Dominance with Trimmed Data
Distributional dominance criteria are commonly applied to draw welfare inferences about comparisons, but conclusions drawn from empirical implementations of dominance criteria may be influenced by data contamination.We examine a nonparametric approach to refining Lorenz-type comparisons and apply the technique to two important examples from the Luxembourg Income Study database.
Institution partenaire
English / 01/01/2006
Bounded-Influence Robust Estimation in Generalized Linear Latent Variable Models
Latent variable models are used for analyzing multivariate data. Recently, generalized linear latent variable models for categorical, metric, and mixed-type responses estimated via maximum likelihood (ML) have been proposed. Model deviations, such as data contamination, are shown analytically, using the influence function and through a simulation study, to seriously affect ML...
Institution partenaire
English / 01/01/2006
Les générations face au marché du travail: évolution de la vie active de 1970 à 2000
L'étude des parcours professionnels apporte des éléments intéressants sur les spécificités des cohortes, définies selon l'année de naissance et le sexe. Comment celles-ci se comportent-elles tout d'abord du passage de la formation à l'entrée dans la vie active? Où se situent encore les différences entre hommes et femmes au niveau de la participation...
Institution partenaire
Français / 01/01/2005
A latent factor model for ordinal data to measure multivariate predictive ability of financial market movements
In this paper we develop a structural equation model with latent variables in an ordinal setting which allows us to test broker-dealer predictive ability of financial market movements. We use a multivariate logit model in a latent factor framework, develop a tractable estimator based on a Laplace approximation, and show its consistency and asymptotic normality. Monte Carlo...
Institution partenaire
English / 01/01/2005
A Robust Prediction Error Criterion for Pareto Modeling of Upper Tails
Estimation of the Pareto tail index from extreme order statistics is an important problem in many settings such as income distributions (for inequality measurement), finance (for the evaluation of the value at risk), and insurance (determination of loss probabilities) among others. The upper tail of the distribution in which the data are sparse is typically fitted with a model such...
Institution partenaire
English / 01/01/2005
The affect structure revisited
In affective psychology, there is a persistent controversy about the number, the nature and the definition of the affect structure dimensions. Responding to the methodological criticisms addressed to the preceding studies, we conciliated the principal theories regarding the affect structure with the same experimental setting. In particular, using the semantic items all around the...
Institution partenaire
English / 01/01/2005
Estimation of Generalized Linear Latent Variable Models
Generalized linear latent variable models (GLLVMs), as defined by Bartholomew and Knott, enable modelling of relationships between manifest and latent variables. They extend structural equation modelling techniques, which are powerful tools in the social sciences. However, because of the complexity of the log-likelihood function of a GLLVM, an approximation such as numerical...
Institution partenaire
English / 01/01/2004
A simulation study to compare competing estimators in structural equation models with ordinal variables
Structural equation models have been around for now a long time. They are intensively used to analyze data from di.erent fields such as psychology, social sciences, economics, management, etc. Their estimation can be performed using standard statistical packages such as LISREL. However, these implementations su.er from an important drawback: they are not suited for cases in which the...
Institution partenaire
English / 01/01/2004
Optimisation de portefeuille: prédire rendements et risques de manière robuste
En finance, le but d'un investisseur confronté à une construction de portefeuille est de trouver quelle combinaison d'actifs produira, dans le futur, le meilleur rendement possible, et cela pour un risque donné.
Institution partenaire
Français / 01/01/2004
Bounded-Bias Robust Estimation in Generalized Linear Latent Variable Models
This paper proposes a robust estimator for a general class of linear latent variable models (GLLVM) (Moustaki and Knott 2000, Bartholomew and Knott 1999). It is based on a weighted score function that is simple to implement numerically and is made consistent using the basic idea of indirect inference. The need of a robust estimator for these models is motivated by the study of the...
Institution partenaire
English / 01/01/2004
A Latent Variable Approach for the Construction of Continuous Health Indicators
In most health survey the state of health of individuals is measured through several different kinds of variables such as qualitative, discrete quantitative or dichotomic ones. From these variables, one aims at building univariate indices of health that summarize the information. To do so, we propose in this paper to use Generalized Linear Latent Variable Models (GLLVM) (see e.g....
Institution partenaire
English / 01/01/2004
Derivative Estimation and Testing in Generalized Additive Models
Institution partenaire
English / 01/01/2003
A Prediction Error Criterion for Choosing the Lower Quantile in Pareto Index Estimation
Successful estimation of the Pareto tail index from extreme order statistics relies heavily on the procedure used to determine the number of extreme order statistics that are used for the estimation. Most of the known procedures are based on the minimization of (an estimate of) the asymptotic mean square error of the Hill estimator for the Pareto tail index. The principal drawback of...
Institution partenaire
English / 01/01/2003
Distribution-Free Inference for Welfare Indices under Complete and Incomplete Information
The data available for estimating welfare indicators are often inconveniently incomplete data: they may be censored or truncated. Furthermore, for robustness reasons, researchers sometimes use trimmed samples. By using the statistical tool known as the Influence Function we derive distribution-free asymptotic variances for wide classes of welfare indicators not only in the complete...
Institution partenaire
English / 01/01/2003
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