A proposal for a new specification for a conditionally heteroskedastic variance model: the Quadratic Moving-Average Conditional Heteroskedasticity and an application to the D. Mark-U.S. dollar Exchange Rate

Ever since the appearance of the ARCH model [Engle(1982a)], an impressive array of variance specifications belonging to the same class of models has emerged [i.e. Bollerslev's (1986) GARCH; Nelson's (1990) EGARCH]. This recent domain has achieved very successful developments. Nevertheless, several empirical studies seem to show that the performance of such models is not always appropriate [Boulier(1992)]. In this paper we propose a new specification: the Quadratic Moving Average Conditional heteroskedasticity model. Its statistical properties, such as the kurtosis and the symmetry, as well as two estimators (Method of Moments and Maximum Likelihood) are studied. Two statistical tests are presented, the first one tests for homoskedasticity and the second one, discriminates between ARCH and QMACH specification. A Monte Carlo study is presented in order to illustrate some of the theoretical results. An empirical study is undertaken for the DM-US exchange rate.

Regulación del proceso de secado de embutidos crudos-curados mediante la aplicación de lógica borrosa (fuzzy logic)

El presente proyecto tenía como objetivo final el desarrollo de un sistema de control basado en Lógica Fuzzy que permita que el proceso de secado tenga una regulación continua y con una menor dependencia de la experiencia del personal experto, evitando además la formación de encostrado. Asimismo, se plantearon una serie de objetivos parciales, cuya consecución permitiría, además de alcanzar el objetivo final descrito, obtener un conocimiento científico adicional. Por ello, a continuación se resumen los resultados en relación con los objetivos parciales propuestos. Como paso previo, antes de abordar los objetivos planteados se diseñó y construyó un equipo experimental de secado, donde se controló de forma precisa la temperatura, la humedad relativa y la velocidad del aire.

Co-movements between US and UK stock prices: the roles of macroeconomic information and time-series varying conditional correlations

This paper provides evidence on the sources of co-movement in monthly US and UK stock price movements by investigating the role of macroeconomic and financial variables in a bivariate system with time-varying conditional correlations. Crosscountry communality in response is uncovered, with changes in the US Federal Funds rate, UK bond yields and oil prices having similar negative effects in both markets. Other variables also play a role, especially for the UK market. These effects do not, however, explain the marked increase in cross-market correlations observed from around 2000, which we attribute to time variation in the correlations of shocks to these markets. A regime-switching smooth transition model captures this time variation well and shows the correlations increase dramatically around 1999-2000. JEL classifications: C32, C51, G15 Keywords: international stock returns, DCC-GARCH model, smooth transition conditional correlation GARCH model, model evaluation.

The Monetary policy rules and the inflation process in open emerging

This paper has three objectives. First, it aims at revealing the logic of interest rate setting pursued by monetary authorities of 12 new EU members. Using estimation of an augmented Taylor rule, we find that this setting was not always consistent with the official monetary policy. Second, we seek to shed light on the inflation process of these countries. To this end, we carry out an estimation of an open economy Philips curve (PC). Our main finding is that inflation rates were not only driven by backward persistency but also held a forward-looking component. Finally, we assess the viability of existing monetary arrangements for price stability. The analysis of the conditional inflation variance obtained from GARCH estimation of PC is used for this purpose. We conclude that inflation targeting is preferable to an exchange rate peg because it allowed decreasing the inflation rate and anchored its volatility.

Hierarchical conditional random fields for parts based models matching

A parts based model is a parametrization of an object class using a collection of landmarks following the object structure. The matching of parts based models is one of the problems where pairwise Conditional Random Fields have been successfully applied. The main reason of their effectiveness is tractable inference and learning due to the simplicity of involved graphs, usually trees. However, these models do not consider possible patterns of statistics among sets of landmarks, and thus they sufffer from using too myopic information. To overcome this limitation, we propoese a novel structure based on a hierarchical Conditional Random Fields, which we explain in the first part of this memory. We build a hierarchy of combinations of landmarks, where matching is performed taking into account the whole hierarchy. To preserve tractable inference we effectively sample the label set. We test our method on facial feature selection and human pose estimation on two challenging datasets: Buffy and MultiPIE. In the second part of this memory, we present a novel approach to multiple kernel combination that relies on stacked classification. This method can be used to evaluate the landmarks of the parts-based model approach. Our method is based on combining responses of a set of independent classifiers for each individual kernel. Unlike earlier approaches that linearly combine kernel responses, our approach uses them as inputs to another set of classifiers. We will show that we outperform state-of-the-art methods on most of the standard benchmark datasets.

A Classification of Tools for Learning Logic

A table showing a comparison and classification of tools (intelligent tutoring systems) for e-learning of Logic at a college level.

Conditional compositional biplots: theory and application

The biplot has proved to be a powerful descriptive and analytical tool in many areasof applications of statistics. For compositional data the necessary theoreticaladaptation has been provided, with illustrative applications, by Aitchison (1990) andAitchison and Greenacre (2002). These papers were restricted to the interpretation ofsimple compositional data sets. In many situations the problem has to be described insome form of conditional modelling. For example, in a clinical trial where interest isin how patients’ steroid metabolite compositions may change as a result of differenttreatment regimes, interest is in relating the compositions after treatment to thecompositions before treatment and the nature of the treatments applied. To study thisthrough a biplot technique requires the development of some form of conditionalcompositional biplot. This is the purpose of this paper. We choose as a motivatingapplication an analysis of the 1992 US President ial Election, where interest may be inhow the three-part composition, the percentage division among the three candidates -Bush, Clinton and Perot - of the presidential vote in each state, depends on the ethniccomposition and on the urban-rural composition of the state. The methodology ofconditional compositional biplots is first developed and a detailed interpretation of the1992 US Presidential Election provided. We use a second application involving theconditional variability of tektite mineral compositions with respect to major oxidecompositions to demonstrate some hazards of simplistic interpretation of biplots.Finally we conjecture on further possible applications of conditional compositionalbiplots

Modelling world investment markets using threshold conditional correlation models

In this paper we propose a parsimonious regime-switching approach to model the correlations between assets, the threshold conditional correlation (TCC) model. This method allows the dynamics of the correlations to change from one state (or regime) to another as a function of observable transition variables. Our model is similar in spirit to Silvennoinen and Teräsvirta (2009) and Pelletier (2006) but with the appealing feature that it does not suffer from the course of dimensionality. In particular, estimation of the parameters of the TCC involves a simple grid search procedure. In addition, it is easy to guarantee a positive definite correlation matrix because the TCC estimator is given by the sample correlation matrix, which is positive definite by construction. The methodology is illustrated by evaluating the behaviour of international equities, govenrment bonds and major exchange rates, first separately and then jointly. We also test and allow for different parts in the correlation matrix to be governed by different transition variables. For this, we estimate a multi-threshold TCC specification. Further, we evaluate the economic performance of the TCC model against a constant conditional correlation (CCC) estimator using a Diebold-Mariano type test. We conclude that threshold correlation modelling gives rise to a significant reduction in portfolio´s variance.

The Decision on Turkish EU accession in December 2002: The logic of anarchy, collective action problems and rhetorical action

Studies of the EU accession of the East and Central European Countries have stressed the importance of neo-liberal institutionalism as an explanation for Member State preferences. In this paper it is argued that Member States’ preferences over Turkish EU accession are better explained by power politics and neo-realism. It seems therefore that Turkey’s way to the EU follows another path than the East and Central Countries. Turkish accession raises the question of the EU’s role in a uni-polar world order – whether the EU should develop into an independent actor on the world stage or not. However, when it comes to the interaction among the Member States in order to decide on when to open accession negotiations with Turkey the constitutive values of the EU seriously modify the outcome that pure power politics would have let to.

The Ins and Outs of Unemployment: A Conditional Analysis

We analyze how unemployment, job finding and job separation rates react to neutral and investment-specific technology shocks. Neutral shocks increase unemployment and explain a substantial portion of unemployment volatility; investment-specific shocks expand employment and hours worked and mostly contribute to hours worked volatility. Movements in the job separation rates are responsible for the impact response of unemployment while job finding rates for movements along its adjustment path. Our evidence qualifies the conclusions by Hall (2005) and Shimer (2007) and warns against using search models with exogenous separation rates to analyze the effects of technology shocks.

The ins and outs of unemployment: An analysis conditional on technology shocks

We analyze how unemployment, job finding and job separation rates reactto neutral and investment-specific technology shocks. Neutral shocks increaseunemployment and explain a substantial portion of it volatility; investment-specificshocks expand employment and hours worked and contribute to hoursworked volatility. Movements in the job separation rates are responsible for theimpact response of unemployment while job finding rates for movements alongits adjustment path. The evidence warns against using models with exogenousseparation rates and challenges the conventional way of modelling technologyshocks in search and sticky price models.

Elaboració d'indicadors sobre SAGE Logic Class

El treball desenvolupat ha consistit en analitzar el sistema d'informació Logic Class sota la perspectiva de la necessitat de construir un sistema d'indicadors (quadre de comandament operatiu) que integri informació de les diferents fonts de dades.