Publications des institutions partenaires
Valuation and Bidding of Hydro Power Plants in the EEX
Institution partenaire
English / 27/08/2007
Regime Switching based Portfolio Selection for Pension Funds
This paper shows how a mean variance criterion can be applied to a multi period setting in order to obtain efficient portfolios in an asset and liability context. The optimization model allows for rebalancing activities, transaction costs, stochastic volatilities for both assets and liabilities. Furthermore, a general framework for the projection of pension fund liabilities as well...
Institution partenaire
English / 01/08/2007
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
Dynamic modelling and optimization of non-maturing accounts
The risk management of non-maturing account positions in a bank's balance like savings deposits or certain types of loans is complicated by the embedded options that clients may exercise. In addition to the usual interest rate risk, there is also uncertainty in the timing and amount of future cash flows. Since the corresponding volume risk cannot directly be hedged, the account...
Institution partenaire
English / 01/01/2007
Risk Measurement in Electricity Markets
Electricity contracts differ substantially from financial contracts making traditional derivatives inapplicable. The main difference lies in the inability to store electricity causing the production to cover demand instantaneously. Therefore, electricity prices often jump to a multiple of their current value only to come back to normal level within a few hours. Spot price volatility...
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
Dynamic Replication of Non-Maturing Assets and Liabilities
Non-maturing assets and liabilities (NoMALs) are those positions in a bank's balance that have no contractual maturity such as traditional savings deposits. For the calculation of transfer prices and the quantification of interest rate risk, a fix maturity profile must be assigned to a NoMAL position. Usually a replicating portfolio of fixed-income instruments with constant...
Institution partenaire
English / 07/09/2005
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
Numerical Techniques in Applied Multistage Stochastic Programming
Institution partenaire
English / 01/01/2005
Refinancing Mortgages in Switzerland
This paper presents a multistage stochastic programming model for refinancing mortgages with non-contractual maturity under liquidity restrictions in the market. An extension to the management of other products such as savings accounts is straightforward. The evolution of interest rates is modelled by principal components for short-term and a two-factor mean reversion model with long...
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
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
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