Impact of Returns Time Dependency on the Estimation of Extreme Market Risk

The estimation of Value-at-Risk generally used models assuming independence. However, financial returns tend to occur in clusters with time dependency. In this paper we study the impact of negligence of returns dependency in market risk assessment. The main methods which take into account returns dependency to assess market risk are: Declustering, Extremal index and Time series-Extreme Value The- ory combination. Results shows an important reduction of the estimation error under dependency assumption. For real data, methods which take into account returns dependency have generally the best performances.Value-at-Risk, Market risk, Dependency, Declustering, Extremal index, Time Series-EVT Combination.

On the Prequential Approach for Testing Exponentiality

We present a prequential (predictive-sequential) approach for testing the goodness-of-fit of an exponential distribution when the parameter $\lambda$ is unknown. Instead of using all the available observations, $\lambda$ is estimated by a prequential approach where at each step $i$, only the $i\!-\!1$ first observations are used. We show that this approach provides a sequence of \ks type distances whose expressions do not depend on $\lambda$ and which converge in distribution (under the null hypothesis) to the \ks distribution. This leads to a simple technique for testing the goodness-of-fit of exponential distributions with unknown parameter using standard quantile tables of the \ks distribution. Even if Monte~Carlo simulations show that the prequential test is less powerful than the standard exponentiality test, the developed results represent a first step in the theoretical study of the {\it u-plot} which is a prequential empirical tool commonly used for the validation of reliability-growth models

Mapping Real Time Applications on NoC Architecture with Hybrid Multi-objective Algorithm

International audienceThe work presented in this paper is a contribution to solving a widespread problem in the field of system design, embedded the placement of a large application on an architecture (NOC). Application is represented by a set of tasks that communicate with each other by sending message via bus on a heterogeneous architecture. Our role is to place the tiles (task) on different elements (core) of architecture with the objectives of minimizing time execution and the energy consumption under the constraints of load balancing, bandwidth, available memory and size of the queue waiting processors. To solve this problem, we used in the context of our present work, a new meta-heuristic algorithm Particle Swarm. it has proved its effectiveness in many fields such as optimization of networks, image processing and even control of industrial systems but it was never applied in our domain

Business Simulation Games : introducción de un simulador de aerolíneas en los estudios de Gestión aeronáutica

BibliografiaEl principal objetivo es el de hacer una propuesta de aplicación de un simulador de aerolíneas en el Grado en Gestión Aeronáutica. Para ello es necesario conocer en qué consisten los Business Simulation Games y cuáles son sus aportaciones en términos de aprendizaje. El resultado de esta investigación ha sido que los Business Simulation Games contribuyen de forma considerable en el aprendizaje, por lo que es una herramienta que puede ser aprovechada en el Grado Gestión Aeronáutica para integrar la formación multidisciplinar de los alumnos de este Grado.El principal objectiu es el de fer una proposta d'aplicació d'un simulador d'aerolínies en el Grau en Gestió Aeronàutica. Per això es necessari conèixer en què consisteixen els Business Simulation Games i quines son les seves aportacions en termes d'aprenentatge. El resultat d'aquesta investigació a sigut que els Business Simulation Games contribueixen de forma considerable en l'aprenentatge, per la qual cosa, es una eina que pot ser aprofitada en el Grau Gestió Aeronàutica per tal d'integrar la formació multidisciplinar dels alumnes d'aquest Grau.The main objective is to make a proposal for implement an airline simulator in Aeronautical Management Degree. Therefore it is necessary to know what Business Simulation Games are and what their contributions in terms of learning are. The result of this research has been that Business Simulation Games contribute significantly in learning, so it is a tool that can be used in Aeronautical Management Degree to integrate the multidisciplinary training of students in this Degree

Quasi-conjugate Bayes estimates for GPD parameters and application to heavy tails modelling

We present a quasi-conjugate Bayes approach for estimating Generalized Pareto Distribution (GPD) parameters, distribution tails and extreme quantiles within the Peaks-Over-Threshold framework. Damsleth conjugate Bayes structure on Gamma distributions is transfered to GPD. Bayes credibility intervals are defined, they provide assessment of the quality of the extreme events estimates. Posterior estimates are computed by Gibbs samplers with Hastings-Metropolis steps. Even if non-informative priors are used in this work, the suggested approach could incorporate informative priors, it brings solutions to the problem of estimating extreme events when data are scarce but expert opinion is available. It is shown that the obtained quasi-conjugate Bayes estimators compare well with the GPD standard estimators on simulated and real data sets

Fault diagnosis and comparing risk for the steel coil manufacturing process using statistical models for binary data

[EN] Advanced statistical models can help industry to design more economical and rational investment plans. Fault detection and diagnosis is an important problem in continuous hot dip galvanizing. Increasingly stringent quality requirements in the automotive industry also require ongoing efforts in process control to make processes more robust. Robust methods for estimating the quality of galvanized steel coils are an important tool for the comprehensive monitoring of the performance of the manufacturing process. This study applies different statistical regression models: generalized linear models, generalized additive models and classification trees to estimate the quality of galvanized steel coils on the basis of short time histories. The data, consisting of 48 galvanized steel coils, was divided into sets of conforming and nonconforming coils. Five variables were selected for monitoring the process: steel strip velocity and four bath temperatures. The present paper reports a comparative evaluation of statistical models for binary data using Receiver Operating Characteristic (ROC) curves. A ROC curve is a graph or a technique for visualizing, organizing and selecting classifiers based on their performance. The purpose of this paper is to examine their use in research to obtain the best model to predict defective steel coil probability. In relation to the work of other authors who only propose goodness of fit statistics, we should highlight one distinctive feature of the methodology presented here, which is the possibility of comparing the different models with ROC graphs which are based on model classification performance. Finally, the results are validated by bootstrap procedures.The authors are indebted to the anonymous referees whose suggestions improved the original manuscript. This work was supported by a grant from PAID-06-08 (Programa de Apoyo a la Investigacion y Desarrollo) of the Universitat Politecnica de Valencia.Debón Aucejo, AM.; García-Díaz, JC. (2012). Fault diagnosis and comparing risk for the steel coil manufacturing process using statistical models for binary data. Reliability Engineering and System Safety. 100:102-114. https://doi.org/10.1016/j.ress.2011.12.022S10211410

Outils statistiques pour la construction et le choix de modèles en fiabilité des logiciels

This work is mainly concerned with the use of statistical tools for the assessment of software reliability. It provides statistical techniques for the construction and the validation of models taking into account the specific properties of each software. For this, we mainly use Generalized Linear Models (parametric and non-parametric) and Bayesian methods. The final part studies the mathematical problems of validation and choice of Software Reliability models. The predictive-sequential approach is shown to give a simple way of testing the fit of Poisson process models. The obtained predictive-sequential test seems to be usable for many Software Reliability models.Ce travail est consacré à l'étude de méthodes statistiques pour l'évaluation de la fiabilité des logiciels. Son but principal est de fournir des outils statistiques permettant de construire et ensuite valider des modèles en tenant compte des spécificités des logiciels étudiés. Pour ce faire deux outils sont utilisés : les modèles linéaires généralisés (paramétriques et non-paramétriques) et l'analyse statistique bayésienne. La deuxième partie de ce travail est consacrée à l'ètude mathématique des problèmes de validation et de choix de modèles en fiabilité des Logiciels. On y étudie entre autres une approche dite "préquentielle" (prédictive-séquentielle) bien adaptée aux tests d'adéquation aux processus de Poisson. Cette approche semble pouvoir se généraliser à un grand nombre de modèles de fiabilité des logiciels