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Arguedas Sanz, Raquel

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0000-0001-7368-6347
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Arguedas Sanz
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Raquel
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2020 - 202411
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Fecha de inicio: 2020 × search.filters.applied.f.itemDepartamento: Economía de la Empresa y Contabilidad ×

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Mostrando 1 - 10 de 11
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    Optimización temporal de las señales automáticas proporcionadas por indicadores técnicos bursátiles
    (Universidad del País Vasco UPV/EHU, 2020-11-27) Ventura Pérez, Enrique; Martín García, Rodrigo; Arguedas Sanz, Raquel
    Los indicadores técnicos bursátiles transmiten al analista señales de compra/venta que, en el caso de ser ejecutadas en el momento de producirse, podrían no ser óptimas desde el punto de vista del resultado de la operación. El objetivo del presente trabajo es doble. En primer lugar, analizar la idoneidad del seguimiento de una batería de indicadores para la obtención de resultados en una cartera. En segundo lugar, estudiar cómo la introducción de retardos temporales entre las señales de los indicadores y la ejecución de las operaciones puede mejorar el resultado de la misma. Se ha realizado una simulación, para el intervalo 2005-2016, con 35 títulos y un índice, sobre 7 indicadores técnicos bursátiles (ROC, RSI, Cruce SMA, Cruce EMA, MACD, Bandas de Bollinger y oscilador estocástico) y un total de 81 combinaciones de retardos de compra/venta. La definición del modelo y la división en tres periodos no solapados genera un total de 61.236 carteras. Los resultados permiten concluir que existen combinaciones de indicador y retardos de compra/venta que proporcionan mejores resultados que la ejecución inmediata de la señal. Concretamente, se identifican retardos óptimos para RSI y cruce EMA que producen mejoras estadísticamente significativas en el resultado de una cartera de valores, independientemente del periodo estudiado. Estos resultados son consistentes con una simulación alternativa en la que se excluyó a los cinco activos más líquidos y de mayor capitalización, para descartar el posible efecto generado por el peso relativo de los valores en la rentabilidad de la cartera o en su normalización.
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    Efficiency in cryptocurrency markets: new evidence
    (Springer, 2021-07-26) López Martín, Carmen; Benito Muela, Sonia; Arguedas Sanz, Raquel
    In 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.
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    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, Carmen
    Full 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.
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    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, Carmen
    Blockchain 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.
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    A comparison of market risk measures from a twofold perspective: accurate and loss function
    (Elsevier, 2023-06-04) Benito Muela, Sonia; López Martín, Carmen; Arguedas Sanz, Raquel
    Under the new regulation based on Basel solvency framework, known as Basel III and Basel IV, financial institutions must calculate the market risk capital requirements based on the Expected Shortfall (ES) measure, replacing the Value at Risk (VaR) measure. In the financial literature, there are many papers dedicated to compare VaR approaches but there are few studies focusing in comparing ES approaches. To cover this gap, we have carried out a comprenhensive comparative of VaR and ES models applied to IBEX-35 stock index. The comparison has been carried out from a twofold perspective: accurate risk measure and loss functions. The results indicate that the method based on the conditional Extreme Value Theory (EVT) is the best in estimating market risk, outperforming Parametric method and Filter Historical Simulation.
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    A cryptocurrency empirical study focused on evaluating their distribution functions
    (Elsevier, 2022-02-14) López Martín, Carmen; Arguedas Sanz, Raquel; Benito Muela, Sonia
    This 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.
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    Collaborative Learning Communities for Sustainable Employment through Visual Tools
    (MDPI, 2020-03-24) Martín García, Rodrigo; López Martín, Carmen; Arguedas Sanz, Raquel
    Higher education institutions must enable students to acquire skills and capacities that prepare them for working life and enhance their employability. This will lead to an applied learning- and teaching-enhancement-oriented sustainable Higher Education System. This research aims to contribute to that goal by analyzing student interactions in a collaborative learning community. It assesses the impact of visual tools on academic performance and student satisfaction in employment-focused blended studies, in which enrollees were geographically dispersed undergraduates with a diversity of profiles. A financial studies learning community was created to test students’ interactions in a model conducive to participation as visual content creators and users. Three surveys (pre-project, appraisal of classmates’ visual exercises, and post-project) were conducted to assess project impact. First, we used a univariate approach, focused on students’ characteristics, course and project appraisals, and the eects of the project on academic performance and expectations. Secondly, a bivariate approach was conducted to detect relationships between respondents’ appraisals and personal characteristics and to determine whether their mean scores were the same irrespective of such characteristics. The findings showed that: (1) Students’ preferences concur with those of their employers; (2) participation in innovative initiatives improves students’ perception of course procedures; (3) visual tools have a positive impact on learning, in terms of both academic performance and student satisfaction. The study concludes by providing support for educational institutions´ decision-making around courses and the overall curricula by defining the factors determining academic performance and student satisfaction.
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    Analysis of the Influence of the Moment the Internationalization Process Begins on the Internationalization Intensity of Family and Nonfamily Businesses: An Approach Using a Tobit Model
    (MDPI, 2022-10-10) Varas Fuente, Oscar Javier; Arguedas Sanz, Raquel; Rodrigo Moya, Beatriz
    The specific characteristics of family businesses as well as the internationalization path followed can influence the intensity of the internationalization process. Many studies have analyzed how family character can influence the internationalization process of family businesses, and the results obtained have not been conclusive. Nevertheless, previous research has not sufficiently addressed the influence that the moment of initiation of the internationalization process has on the levels of internationalization achieved. Based on the behavioral agency model, the unique set of business resources (familiness), and the socioemotional wealth (SEW) perspective, this study examines, the internationalization intensity of family and nonfamily businesses in two defined groups (early internationalization and internationalization from the local market). Likewise, the effect that the entry of the second generation has on the internationalization of these companies is analyzed. To perform this analysis, Tobit regression models are estimated from a data set of panel data from the Spanish Survey on Business Strategies for small and medium-sized Spanish family businesses from 2005 to 2016, finding that family ownership and management have a negative influence on the intensity of exports, regardless of the path of internationalization followed, and that the entry of new generations has a positive relationship with the level of internationalization of these businesses. Finally, implications of the findings for research and management are discussed.
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    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, Raquel
    Pneumococcal 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.
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    The extreme temperature factor in asset pricing models: Evidence from Europe
    (ELSEVIER, 2024-08) González Sánchez, Mariano; Arguedas Sanz, Raquel; Segovia San Juan, Ana Isabel
    Growing 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.