Persona: Arguedas Sanz, Raquel
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Arguedas Sanz
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Raquel
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Publicación Barreras y retos de las unidades funcionales de gestión de riesgos sanitarios en los hospitales del Servicio Madrileño de Salud(Elsevier, 2014) Pardo Hernández, Alberto; Navarro Royo, Cristina; Albeniz Lizarraga, C.; Morón Merchante, J.; Arguedas Sanz, RaquelObjetivo Identificar las barreras y los retos para el desarrollo efectivo de las unidades de gestión de riesgos sanitarios en los hospitales del Servicio Madrileño de Salud. Material y métodos Estudio descriptivo transversal dirigido a los equipos directivos y a los miembros de las unidades funcionales de 31 hospitales del Servicio Madrileño de Salud. Se solicitó en forma de texto libre, dentro de un cuestionario autoadministrado, la identificación de un máximo de 5 barreras y retos y su priorización a través de la adjudicación de uno a 5 puntos de acuerdo con su importancia. Posteriormente se realizó un análisis del discurso agrupando los temas comunes y ordenándolos de acuerdo con la puntuación recibida. Resultados La tasa de respuesta global fue del 94%. Las barreras más frecuentemente identificadas fueron: falta de tiempo (21%), insuficiente cultura de seguridad (13%), escasa difusión de sus actividades (10%) y falta de formación (10%). El reto más importante fue potenciar la formación (18%), seguido de mejorar la cultura (17%), difundir las actividades de seguridad (11%) y lograr el liderazgo de los responsables de los servicios (11%). Conclusiones En las condiciones del estudio, la barrera fundamental identificada fue la falta de tiempo y el reto principal la necesidad de formación. Por ello parece necesario mejorar el apoyo organizativo a la seguridad clínica en el ámbito objeto de estudio.Publicación Climate transition risk in determining credit risk: evidence from firms listed on the STOXX Europe 600 index(Springer, 2023-04-10) Ramos García, Daniel; López Martín, Carmen; Arguedas Sanz, RaquelThis paper assesses whether a climate factor is relevant to measure default risk in a sample of main companies listed on the STOXX Europe 600 exchange from 2010 to 2020. The starting point is a factorial panel datamodel which is subsequently modified to capture the climate impact through different functional forms.We find that relevant differences in default risk exist before and after the Paris Agreement. Our analysis also indicates that this difference cannot be explained by means of traditional financial factors. Finally, we further show that a climate change risk and opportunities label is a significant factor in evaluating credit risk, both prior to and post-Paris agreement. These results are important to the extent that they suggest that companies’ market performance itself allows to measure differences in credit risk between companies and to link them with climate risk factors. This approach may be useful as a complement or in combination with the traditional use of exogenous climate factors that have been widely used in the literature in this field.Publicación Models used to characterise blockchain features. A systematic literature review and bibliometric analysis(Elsevier, 2023-05-01) Rico Peña, Juan Jesús; Arguedas Sanz, Raquel; López Martín, CarmenBlockchain has emerged as an innovative technology with potential to transform business management, through operational efficiency improvements. Nevertheless, several performance and vulnerability issues have been identified for the different typologies supporting the wide range of blockchain-based applications currently implemented in different domains. A variety of analytical and empirical models are being used to evaluate the issues associated with the different blockchain typologies, enabling systematic analyses of the corresponding efficiency impact, and technical or economic threats. A thorough systematic literature review of these models has been performed, followed by a detailed assessment on the way these models have been employed, and the target parameters and applications evaluated (336 research selected and analysed). We propose a co-classification of these models, allowing us to identify which ones are employed to a greater extent to address the different blockchain issues in scientific research. In a second step, a bibliometric analysis on the selected research is conducted, offering a complementary overview of the status of and trends in blockchain modelling, including the most prolific authors and leading contributing countries to the topic. The main outcome and contribution of the paper is the provision of a broad overview on how blockchain issues have been analytically tackled, through the synthesis and meta-analysis of the models used in the scientific literature since the inception of blockchain technology. The results have two main direct applications, firstly supporting novel vulnerability and performance analyses of existing blockchain applications by providing historical information on the models used so far, as well as the key parameters and typology of the blockchain-based applications evaluated. Secondly, in the implementation of new applications, by allowing the recognition of key issues identified that are associated with the different blockchain typologies and to determine the most suitable models to analyse the weaknesses and risks of the alternative designs under evaluation for these new implementations.Publicación Real estate industry takeover bid patterns: Spain, a case study(Elsevier, 2017-02-07) González Arias, Julio; Arguedas Sanz, Raquel; Martín García, RodrigoLa tendencia alcista del sector inmobiliario espa˜nol (2000-2007) provocó el crecimiento excesivo de muchas empresas, principalmente mediante adquisiciones. Esta investigación pretende identificar patrones de comportamiento para la realización de OPAs en el sector inmobiliario espa˜ nol, particularmente castigado por la crisis financiera. Para ello, se ha analizado un conjunto de 20 variables económico-financieras y su relación con la participación de las compa˜nías cotizadas del sector en este tipo de operaciones, para un total de 354 casos para el periodo 2000-2012, como adquirentes y adquiridas. Para ello, se ha empleado una metodología en dos etapas. En primer lugar, se ha aplicado el Método de Componentes Principales para acotar las variables de estudio consideradas con mayor capacidad explicativa. En segundo lugar, se ha construido un modelo predictivo basado en árboles de decisión, concretamente de tipo CHAID, que permite categorizar el conjunto de empresas analizadas y discriminar patrones de comportamiento. Los cinco factores principales con mayor capacidad explicativa son: a) liquidez, solvencia y capacidad de endeudamiento; b) tama˜no; c) resultado económico; d) capacidad operativa, y e) resultado financiero. De hecho, los dos primeros explican conjuntamente en torno al 70% de la variable dependiente, considerando principalmente a empresas adquirentes. El modelo propuesto cuenta con un nivel de explicación global cercano al 80%. El porcentaje restante que no explica el modelo responde fundamentalmente a cuestiones de tipo estratégico, de especulación financiera e intereses particulares, entre otros factores que concurren en la toma de decisiones.Publicación Efficiency in cryptocurrency markets: new evidence(Springer, 2021-07-26) López Martín, Carmen; Benito Muela, Sonia; Arguedas Sanz, RaquelIn this paper we carried out a comprehensive study of the efficiency in the cryptocurrency markets. The markets under study are: Bitcoin, Litecoin, Ethereum, Ripple, Stellar and Monero. To studdy the efficiency of these markets, we use a set of five test which are applied in both a static context and dynamic context. The results obtained depend on both the analysis period and the methodology used to test the predictability of the return. However, some conclusions can be drawn: first, we observe that overall, the efficiency degree tends to increase with the time. Second, although the efficiency market seems to change along the period, the changes in the Bitcoin, Litecoin and Ethereum market show a clear tendency that evolves from less to more efficiency. In the case of Ripple, Stellar and Monero, periods of efficiency alternate with periods of inefficient, which is consistent with the Adaptive Market Hypothesis.Publicación A cryptocurrency empirical study focused on evaluating their distribution functions(Elsevier, 2022-02-14) López Martín, Carmen; Arguedas Sanz, Raquel; Benito Muela, SoniaThis paper thoroughly examines the statistical properties of cryptocurrency returns, particularly focusing on studying which is the best statistical distribution for fitting this type of data. The preliminary statistical study reveals (i) high volatility, (ii) an inverse leverage effect, (iii) skewed distributions and (iv) high kurtosis. To capture the nonnormal characteristics observed in cryptocurrency data, we verified the goodness of fit of a large set of distributions, both symmetric and skewed distributions such as skewed Student-t, skewed generalized t, skewed generalized error and the inverse hyperbolic sign distributions. The results show that the skewed distributions outperform normal and Student-t distributions in fitting cryptocurrency data, although there is no one skewed distribution that systematically better fits the data. In addition, we compare these distributions in terms of their ability to forecast the market risk of cryptocurrencies. In line with the results obtained in the statistical analysis, we find that the skewed distributions provide better risk estimates than the normal and Student-t distributions, both in short and long positions, with SGED being the distribution that provides better results.Publicación Innovation in the University: Perception, Monitoring and Satisfaction(IEEE, 2018-08-03) Vicente Vírseda, Juan Antonio; Arguedas Sanz, Raquel; Martín García, Rodrigo; González Arias, JulioA blended learning teaching experience conducted at Spain's National Distance University is described. The project consisted of integrating technology (a virtual learning platform) and teaching methodologies (multimedia contents, weekly deliverables, continuous self-assessment, mentoring, a four-month timetable, and webinars) to enhance student engagement, performance, and satisfaction. A statistical study showed that self-assessment and professor monitoring are key issues in students' initial perception and ultimate satisfaction as well as the most effective tools for preventing dropout. Project participants had a lower dropout rate and higher grades than non-participants.Publicación The student as a prosumer of educational audio–visual resources: a higher education hybrid learning experience(Taylor & Francis, 2022-06-09) Navío Marco, Julio; Ruiz Gómez, Luis Manuel; Arguedas Sanz, Raquel; López Martín, CarmenFull Article Figures & data References Citations Metrics Reprints & Permissions Read this article ABSTRACT The rise of the student as prosumer (producer–consumer) of educational content is a novel development that has hitherto been the subject of very little research, especially in relation to the generation of digital contents and materials for online and hybrid education in particular. This article analyses whether there are patterns of behaviour and different perceptions associated with different groups of students in their role as producers and/or users in the field of active learning in hybrid university education systems. To this end, the research has been conducted with a group of engineering students at one of the largest blended learning universities in Europe. The results indicate higher levels of involvement in, and appreciation of, the experience in content producers compared with mere content consumers, but the students’ environment and personal attitudes (such as their availability and degree of professional dedication) in relation to this type of education, the profile of which is often quite distinct from that of traditional learning, may differentiate their interest and appreciation of these activities, which are more creative and probably more demanding.Publicación Burden of Hospitalizations Related to Pneumococcal Infection in Spain (2016–2020)(MDPI, 2023-01-14) Gil Prieto, Ruth; Allouch, Nizar; Jimeno, Isabel; Hernández Barrera, Valentín; Gil de Miguel, Ángel; Arguedas Sanz, RaquelPneumococcal infection strongly contributes to morbidity and mortality in Spain. A total of 253,899 hospitalizations related to pneumococcal infection occurred from 2016 to 2020. Fifty-eight percent were men, the mean age was 67 years old, and the average length of hospitalization was 12.72 days. The annual hospitalization rate was 10.84 hospitalizations per 10,000 population, increasing significantly with age, reaching 65.75 per 10,000 population in those aged >85 years. The hospitalization rates for pneumococcal pneumonia, sepsis, and meningitis were 2.91, 0.12, and 0.08 hospitalizations per 10,000, respectively, and reached the highest value in those aged >85 for pneumococcal pneumonia and sepsis, with 22.29 and 0.71 hospitalizations per 10,000, respectively, and in children up to 1 year old for pneumococcal meningitis, with 0.33 hospitalizations per 10,000. The total number of deaths during the study period was 35,716, with a case-fatality rate of 14.07%. For pneumococcal pneumonia, sepsis, and meningitis, the case-fatality rates were 8.47%, 23.71%, and 9.99%, respectively. The case-fatality rate increased with age and did not vary by sex. The annual cost of these hospitalizations was more than EUR 359 million. There is therefore a high burden of disease and mortality caused by pneumococcal infection in our country, especially in elderly individuals.Publicación The extreme temperature factor in asset pricing models: Evidence from Europe(ELSEVIER, 2024-08) González Sánchez, Mariano; Arguedas Sanz, Raquel; Segovia San Juan, Ana IsabelGrowing concern about climate change has led to increased research into the effects of climate on markets. One of the weather variables studied is temperature. The previous studies considered that the temperature influences on asset returns through changes in investor mood. There are few studies that incorporate a risk factor to analyze the effects of temperature changes on asset returns. We extract positive and negative extreme temperature changes to design three temperature factors. By a cross-section asset pricing model, we find evidence that temperature shocks (hot and cold) show a significant monthly risk premium and skewness for temperature changes.