Examinando por Autor "Doncel Pedrera, Luis Miguel"

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Activos financieros y riesgos por tipo de cambio en modelos de equilibrio y optimización dinámica
(2003-07-07) Doncel Pedrera, Luis Miguel
Converting Lik ting Likert Scales Int t Scales Into Behavioral Anchor al Anchored Rating Scales(Bars) F ed Rating Scales(Bars) For The Evaluation of T aluation of Teaching E eaching Effectiveness F eness For Formativ ormative Purposes e Purposes
(2019) Leguey Galán, Santiago; Matosas lópez, Luis; Doncel Pedrera, Luis Miguel
Likert scales traditionally used in student evaluations of teaching (SET) suffer from several shortcomings, including psychometric deficiencies or ambiguity problems in the interpretation of the results. Assessment instruments with Behavioral Anchored Rating Scales (BARS) offer an alternative to Likerttype questionnaires. This paper describes the construction of an appraisal tool with BARS generated with the participation of 974 students and 15 teachers. The resulting instrument eliminates ambiguity in the interpretation of results and gives objectivity to the evaluation due to the use of unequivocal behavioral examples in the final scale. However, BARS methodology presents the problem of losing behavioral information during scale construction. The BARS methodology presented by the authors introduces an additional step to the traditional procedure, which significantly reduces the loss of information during the scale construction. The authors conclude that the qualitative approach of the proposed instrument facilitates the application of the formative function of the evaluation.
Different risk-adjusted fund performance measures: a comparison
(2013-01-22) Grau Carles, Pilar; Doncel Pedrera, Luis Miguel; Sainz Gonzañez, Jorge
Traditional risk-adjusted performance measures, such as the Sharpe ratio, the Treynor index or Jensen¿s alpha, based on the mean-variance framework, are widely used to rank mutual funds. However, performance measures that consider risk by taking into account only losses, such as Value-at-Risk (VaR), would be more appropriate. Standard VaR assumes that returns are normally distributed, though they usually present skewness and kurtosis. In this paper we compare these different measures of risk: traditional ones vs. ones that take into account fat tails and asymmetry, such as those based on the Cornish-Fisher expansion and on the extreme value theory. Moreover, we construct a performance index similar to the Sharpe ratio using these VaR-based risk measures. We then use these measures to compare the rating of a set of mutual funds, assessing the different measures¿ usefulness under the Basel II risk management framework.
Effectiveness of tutoring at school: A machine learning evaluation
(Elsevier, 2023) Ballestar, María Teresa; Cuerdo Mir, Miguel; Doncel Pedrera, Luis Miguel; Sainz, Jorge
Tutoring programs are effective in reducing school failures among at-risk students. However, there is still room for improvement in maximising the social returns they provide on investments. Many factors and components can affect student engagement in a program and academic success. This complexity presents a challenge for Public Administrations to use their budgets as efficiently as possible. Our research focuses on providing public administration with advanced decision-making tools. First, we analyse a database with information on 2066 students of the Programa para la Mejora de Éxito Educativo (Programme for the Improvement of Academic Success) of the Junta de Comunidades de Castilla y Léon in Spain, in 2018–2019, the academic year previous to the pandemic. This program is designed to help schools with students at risk of failure in Spanish, literature, mathematics, and English. We developed a machine learning model (ML) based on Kohonen self-organising maps (SOMs), which are a type of unsupervised (ANN), to group students based on their characteristics, the type of tutoring program in which they were enrolled, and their results in both the completion of the program and the 4th year of Compulsory Secondary Education (ESO). Second, we evaluated the results of tutoring programs and identified and explained how different factors and components affect student engagement and academic success. Our findings provide Public Administrations with better decision-making tools to evaluate and measure the results of tutoring programs in terms of social return on investment, improve the design of these programs, and choose the students to enrol.