Rendimiento ex-dividendo como indicador de eficiencia en un mercado emergente: caso colombiano 1999-2007

Se evalúa el rendimiento ex-dividendo en acciones colombianas entre 1999 y 2007, período que incluye la conformación en Julio de 2001 de la Bolsa de Valores de Colombia resultado de la integración de tres bolsas previamente existentes. Contrario a la hipótesis de eficiencia de mercado, se encontraron rendimientos ex-dividendo positivos y estadísticamente significativos, similares a los evidenciados en diversos mercados internacionales. Se comprueba que los rendimientos ex-dividendo no son explicados en su totalidad por costos de transacción ni por efectos impositivos. Una estrategia limitada de captura de dividendos, substrayendo dichos costos, habría entregado rendimientos positivos y económicamente importantes entre 2006 y 2007 en las acciones más liquidas del mercado. Sin embargo, estos rendimientos tienden a disminuir en el período de estudio, consistentes con un avance hacia una mayor eficiencia en el mercado accionario colombiano después de la integración. Este estudio pone de relieve la importancia de considerar las fricciones en estudios académicos de eficiencia y de evaluación de estrategias especulativas.We study the ex-dividend return in the Colombian stock market between 1999 and 2007, period that includes the merger of the former three Colombian stock exchanges in the Bolsa de Valores de Colombia in July 2001. Contrary to the Efficient Market Hypothesis, we found positive and statistically significant ex-dividend returns in the sampled period, only in part explained by transaction cost and tax effects. Moreover, even subtracting transaction costs and tax effects, a dividend capture strategy would have got positive and economically sizable returns between 2006 and 2007 in the most liquid stocks. The decrease of those ex-dividend returns is also reported along the studied period, providing evidence of increasing informational efficiency after the merger of the three stock exchanges. Methodologically, this study highlights the importance of accounting for frictions in both academic efficiency studies and in testing speculative strategies by practitioners

Análisis cepstral y la transformada de Hilbert-Huang para la detección automática de la enfermedad de Parkinson

Most patients with Parkinson’s Disease (PD) develop speech deficits, including reduced sonority, altered articulation, and abnormal prosody. This article presents a methodology to automatically classify patients with PD and Healthy Control (HC) subjects. In this study, the Hilbert-Huang Transform (HHT) and Mel-Frequency Cepstral Coefficients (MFCCs) were considered to model modulated phonations (changing the tone from low to high and vice versa) of the vowels /a/, /i/, and /u/. The HHT was used to extract the first two formants from audio signals with the aim of modeling the stability of the tongue while the speakers were producing modulated vowels. Kruskal-Wallis statistical tests were used to eliminate redundant and non-relevant features in order to improve classification accuracy. PD patients and HC subjects were automatically classified using a Radial Basis Support Vector Machine (RBF-SVM). The results show that the proposed approach allows an automatic discrimination between PD and HC subjects with accuracies of up to 75 % for women and 73 % for men.La mayoría de las personas con la enfermedad de Parkinson (EP) desarrollan varios déficits del habla, incluyendo sonoridad reducida, alteración de la articulación y prosodia anormal. Este artículo presenta una metodología que permite la clasificación automática de pacientes con EP y sujetos de control sanos (CS). Se considera que la transformada de Hilbert-Huang (THH) y los Coeficientes Cepstrales en las frecuencias de Mel modelan las fonaciones moduladas (cambiando el tono de bajo a alto y de alto a bajo) de las vocales /a/, /i/, y /u/. La THH se utiliza para extraer los dos primeros formantes de las señales de audio, con el objetivo de modelar la estabilidad de la lengua mientras los hablantes producen vocales moduladas. Pruebas estadísticas de Kruskal-Wallis se utilizan para eliminar características redundantes y no relevantes, con el fin de mejorar la precisión de la clasificación. La clasificación automática de sujetos con EP vs. CS se realiza mediante una máquina de soporte vectorial de base radial. De acuerdo con los resultados, el enfoque propuesto permite la discriminación automática de sujetos con EP vs. CS con precisiones de hasta el 75 % para los hombres y 73 % para las mujeres

Detección de desórdenes de lenguaje de pacientes con enfermedad de Alzheimer usando embebimientos de palabras y características gramaticales

Alzheimer's Disease (AD) is a progressive neurodegenerative disorder that affects the language production and thinking capabilities of patients. The integrity of the brain is destroyed over time by interruptions in the interactions between neuron cells and associated cells required for normal brain functioning. AD comprises deterioration of the communicative skills, which is reflected in deficient speech that usually contains no coherent information, low density of ideas, and poor grammar. Additionally, patients exhibit difficulties to find appropriate words to structure sentences. Multiple ongoing studies aim to detect the disease considering the deterioration of language production in AD patients. Natural Language Processing techniques are employed to detect patterns that can be used to recognize the language impairments of patients. This paper covers advances in pattern recognition with the use of word-embedding and word-frequency features and a new approach with grammar features. We processed transcripts of 98 AD patients and 98 healthy controls in the Pitt Corpus of the Dementia-Bank database. A total of 1200 word-embedding features, 1408 Term Frequency—Inverse Document Frequency features, and 8 grammar features were extracted from the selected transcripts. Three models are proposed based on the separate extraction of such feature sets, and a fourth model is based on an early fusion strategy of the proposed feature sets. All the models were optimized following a Leave-One-Out cross validation strategy. Accuracies of up to 81.7 % were achieved using the early fusion of the three feature sets. Furthermore, we found that, with a small set of grammar features, accuracy values of up to 72.8 % were obtained. The results show that such features are suitable to effectively classify AD patients and healthy controls.La enfermedad de Alzheimer es un desorden neurodegenerativo-progresivo que afecta la producción de lenguaje y las capacidades de pensamiento de los pacientes. La integridad del cerebro es destruida con el paso del tiempo por interrupciones en las interacciones entre neuronas y células, requeridas para su funcionamiento normal. La enfermedad incluye el deterioro de habilidades comunicativas por un habla deficiente, que usualmente contiene información inservible, baja densidad de ideas y habilidades gramaticales. Adicionalmente, los pacientes presentan dificultades para encontrar palabras apropiadas y así estructurar oraciones. Por lo anterior, hay investigaciones en curso que buscan detectar la enfermedad considerando el deterioro de la producción de lenguaje. Así mismo, se están usando técnicas de procesamiento de lenguaje natural para detectar patrones y reconocer las discapacidades del lenguaje de los pacientes. Por su parte, este artículo se enfoca en el uso de características basadas en embebimiento y frecuencia de palabras, además de hacer una nueva aproximación con características gramaticales para clasificar la enfermedad de Alzheimer. Para ello, se consideraron transcripciones de 98 pacientes con Alzheimer y 98 controles sanos del Pitt Corpus incluido en la base de datos Dementia-Bank. Un total de 1200 características de embebimientos de palabras, 1408 características de frecuencia de término inverso vs. frecuencia en documentos, y 8 características gramaticales fueron calculadas. Tres modelos fueron propuestos, basados en la extracción de dichos conjuntos de características por separado y un cuarto modelo fue basado en una estrategia de fusión temprana de los tres conjuntos de características. Los modelos fueron optimizados usando la estrategia de validación cruzada Leave-One-Out. Se alcanzaron tasas de aciertos de hasta 81.7 % usando la fusión temprana de todas las características. Además, se encontró que un pequeño conjunto de características gramaticales logró una tasa de acierto del 72.8 %. Así, los resultados indican que estas características son adecuadas para clasificar de manera efectiva entre pacientes de Alzheimer y controles sanos

Thermodynamic properties of binary HCP solution phases from special quasirandom structures

Three different special quasirandom structures (SQS) of the substitutional hcp $A_{1-x}B_x$ binary random solutions ($x=0.25$, 0.5, and 0.75) are presented. These structures are able to mimic the most important pair and multi-site correlation functions corresponding to perfectly random hcp solutions at those compositions. Due to the relatively small size of the generated structures, they can be used to calculate the properties of random hcp alloys via first-principles methods. The structures are relaxed in order to find their lowest energy configurations at each composition. In some cases, it was found that full relaxation resulted in complete loss of their parental symmetry as hcp so geometry optimizations in which no local relaxations are allowed were also performed. In general, the first-principles results for the seven binary systems (Cd-Mg, Mg-Zr, Al-Mg, Mo-Ru, Hf-Ti, Hf-Zr, and Ti-Zr) show good agreement with both formation enthalpy and lattice parameters measurements from experiments. It is concluded that the SQS's presented in this work can be widely used to study the behavior of random hcp solutions.Comment: 15 pages, 8 figure

Low-cost multi-spectral camera platform for in-flight near real-time vegetation index computation and delivery.

Agricultural optimization and increased productivity is always a growing concern, due to the increasing population. Crops susceptible to a wide variety of hindering conditions, need to be carefully observed and managed to guarantee maximum production. Many diseases, weather changes, soil variances and other in?uencing factors are only visible after the plant has reached a deplorable state and its neighbors closely trailing behind. Ongoing research is enhancing an observation model that can better prevent such factors, but many still present a variety of limiting factors that are still being studied. Vegetation indices is a long dated studied concept that has proven to be able to show plant response to stress before visible signs are present. To take advantage of this we propose a multi-spectral camera, aimed at mass use, to provide the needed observation with top of the line, reliable results. The built prototype was put through two different tests, both showing it capable of displaying plant health. The ?ne control test showed the camera capable of displaying difference in plant health after only two days of stress. The results were reached with out the use of expensive lenses/?lters, and provide easy to interpret results. All while being able to send data to a nearby portable device

Real-time Atomistic Observation of Structural Phase Transformations in Individual Hafnia Nanorods

High-temperature phases of hafnium dioxide have exceptionally high dielectric constants and large bandgaps, but quenching them to room temperature remains a challenge. Scaling the bulk form to nanocrystals, while successful in stabilizing the tetragonal phase of isomorphous ZrO2, has produced nanorods with a twinned version of the room temperature monoclinic phase in HfO2. Here we use in situ heating in a scanning transmission electron microscope to observe the transformation of an HfO2 nanorod from monoclinic to tetragonal, with a transformation temperature suppressed by over 1000°C from bulk. When the nanorod is annealed, we observe with atomic-scale resolution the transformation from twinned-monoclinic to tetragonal, starting at a twin boundary and propagating via coherent transformation dislocation; the nanorod is reduced to hafnium on cooling. Unlike the bulk displacive transition, nanoscale size-confinement enables us to manipulate the transformation mechanism, and we observe discrete nucleation events and sigmoidal nucleation and growth kinetics