Persona: López Martín, Carmen
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Publicación Collaborative Learning Communities for Sustainable Employment through Visual Tools(MDPI, 2020-03-24) Martín García, Rodrigo; López Martín, Carmen; Arguedas Sanz, RaquelHigher 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.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 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, RaquelUnder 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.Publicación An application of extreme value theory in estimating liquidity risk(Elsevier, 2017-12) Benito Muela, Sonia; López Martín, Carmen; Arguedas Sanz, RaquelThe last global financial crisis (2007–2008) has highlighted the weaknesses of value at risk (VaR) as a measure of market risk, as this metric by itself does not take liquidity risk into account. To address this problem, the academic literature has proposed incorporating liquidity risk into estimations of market risk by adding the VaR of the spread to the risk price. The parametric model is the standard approach used to estimate liquidity risk. As this approach does not generate reliable VaR estimates, we propose estimating liquidity risk using more sophisticated models based on extreme value theory (EVT). We find that the approach based on conditional extreme value theory outperforms the standard approach in terms of accurate VaR estimates and the market risk capital requirements of the Basel Capital Accord.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 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 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.