A comparative long-memory Analysis between Spanish, Mexican and U.S. interest rates

Evidence exists that many natural facts are described better as a fractal. Although fractals are very useful for describing nature, it is also appropiate to review the concept of random fractal in finance. Due to the extraordinary importance of Brownian motion in physics, chemistry or biology, we will consider the generalization that supposes fractional Brownian motion introduced by Mandelbrot.The main goal of this work is to analyse the existence of long range dependence in instantaneous forward rates of different financial markets. Concretelly, we perform an empirical analysis on the Spanish, Mexican and U.S. interbanking interest rate. We work with three time series of daily data corresponding to 1 day operations from 28th March 1996 to 21st May 2002. From among all the existing tests on this matter we apply the methodology proposed in Taqqu, Teverovsky and Willinger (1995).

Term structure of interest rates. European financial integration

In this paper we estimate, analyze and compare the term structures of interest rates in six different countries over the period 1992-2004. We apply the Nelson-Siegel model to obtain the term structures of interest rates at weekly intervals. A total of 4,038 curves are estimated and analyzed. Four European Monetary Union countries¿Spain, France, Germany and Italy¿are included. The UK is also included as a European non-member of the Monetary Union. Finally the US completes the analysis. The goal is to determine the differences in the shapes of the term structure of interest rates among these countries. Likewise, we can determine the most usual term structure shapes that appear for each country.*****

The development of a web page for lipid science and research. Main web sites of interest

En internet encontramos gran cantidad de información científico-técnica cuya validez no suele estar controlada por comités correctores. Para aprovechar estos recursos es necesario filtrar y facilitar el acceso del usuario a la información. En este artículo se expone la experiencia práctica en el desarrollo de una página WEB centrada en las actividades del grupo de investigación «Calidad Nutricional y Tecnología de los Lípidos». Los objetivos de esta página WEB fueron los siguientes: difusión de las actividades del grupo de investigación, aprovechar los recursos que ofrece internet y fomentar y facilitar su uso. Esta experiencia permitió presentar una metodología de trabajo eficaz para conseguir estos objetivos. Finalmente, se presentan un gran número de direcciones WEB agrupadas por apartados en el ámbito de los lípidos. Estas direcciones han sido rigurosamente seleccionadas, entre un gran número de referencias consultadas, siguiendo una serie de criterios que se discuten en este trabajo, para ofrecer aquellas que presentan un mayor interés práctico.

Intérêt de l'échographie du diamètre de l'enveloppe du nerf optique pour la détection non invasive de l'hypertension intracrânienne [Interest of optic nerve sheath diameter ultrasonography in dectecting non-invasively raised intracranial pressure].

Intracranial hypertension is an emergency suspected from clinical symptoms, imaging data and ophthalomologic signs. Intracranial hypertension is confirmed by invasive intracranial monitoring, which is the gold standard technique to measure intracranial pressure (ICP). Because of complications, hemorrhage or infection, non-invasive methods have been developed such as neuroimaging, transcranial Doppler sonography and optic nerve sheath diameter (ONSD) ultrasonography. We have reviewed ONSD technique that detects intracranial hypertension related volume variations of subarachnoid space along the retro bulbar segment of the optic nerve. Technique, indications and prospects are discussed.

Machine learning analysis and modeling of interest rate curves

The present research deals with the review of the analysis and modeling of Swiss franc interest rate curves (IRC) by using unsupervised (SOM, Gaussian Mixtures) and supervised machine (MLP) learning algorithms. IRC are considered as objects embedded into different feature spaces: maturities; maturity-date, parameters of Nelson-Siegel model (NSM). Analysis of NSM parameters and their temporal and clustering structures helps to understand the relevance of model and its potential use for the forecasting. Mapping of IRC in a maturity-date feature space is presented and analyzed for the visualization and forecasting purposes.

Emotional intelligence and social interest : are they related constructs?

In the last 15 years, a new psychological construct has emerged in the field of psychology: Emotional Intelligence. Some models of Emotional Intelligence bear ressemblence with aspects of one of the core constructs of Adlerian Psychology: Social Interest. The authors investigated, if both constructs are also empirically related and which is their capacity to predict psychiatric symptoms and antisocial behavior. Results indicate that Social Interest and Emotional Intelligence are empirically different constructs; Social Interest was negatively correlated to aspects of antisocial attitudes (but not to antisocial behavior). Social Interest also failed to predict symptoms of psychological distress. Emotional Intelligence, in change, was a better predictor for mental problems than Social Interest. The results are discussed in view of the validity of Social Interest measurement.

Structural macro factors and the affine term structure of interest rates

This work consists of three essays investigating the ability of structural macroeconomic models to price zero coupon U.S. government bonds. 1. A small scale 3 factor DSGE model implying constant term premium is able to provide reasonable a fit for the term structure only at the expense of the persistence parameters of the structural shocks. The test of the structural model against one that has constant but unrestricted prices of risk parameters shows that the exogenous prices of risk-model is only weakly preferred. We provide an MLE based variance-covariance matrix of the Metropolis Proposal Density that improves convergence speeds in MCMC chains. 2. Affine in observable macro-variables, prices of risk specification is excessively flexible and provides term-structure fit without significantly altering the structural parameters. The exogenous component of the SDF is separating the macro part of the model from the term structure and the good term structure fit has as a driving force an extremely volatile SDF and an implied average short rate that is inexplicable. We conclude that the no arbitrage restrictions do not suffice to temper the SDF, thus there is need for more restrictions. We introduce a penalty-function methodology that proves useful in showing that affine prices of risk specifications are able to reconcile stable macro-dynamics with good term structure fit and a plausible SDF. 3. The level factor is reproduced most importantly by the preference shock to which it is strongly and positively related but technology and monetary shocks, with negative loadings, are also contributing to its replication. The slope factor is only related to the monetary policy shocks and it is poorly explained. We find that there are gains in in- and out-of-sample forecast of consumption and inflation if term structure information is used in a time varying hybrid prices of risk setting. In-sample yield forecast are better in models with non-stationary shocks for the period 1982-1988. After this period, time varying market price of risk models provide better in-sample forecasts. For the period 2005-2008, out of sample forecast of consumption and inflation are better if term structure information is incorporated in the DSGE model but yields are better forecasted by a pure macro DSGE model.

Interest rates mapping

The present study deals with the analysis and mapping of Swiss franc interest rates. Interest rates depend on time and maturity, defining term structure of the interest rate curves (IRC). In the present study IRC are considered in a two-dimensional feature space - time and maturity. Exploratory data analysis includes a variety of tools widely used in econophysics and geostatistics. Geostatistical models and machine learning algorithms (multilayer perceptron and Support Vector Machines) were applied to produce interest rate maps. IR maps can be used for the visualisation and pattern perception purposes, to develop and to explore economical hypotheses, to produce dynamic asset-liability simulations and for financial risk assessments. The feasibility of an application of interest rates mapping approach for the IRC forecasting is considered as well. (C) 2008 Elsevier B.V. All rights reserved.