Análisis econométrico de la remuneración de los consejeros en las empresas del IBEX 35

Existe un creciente interés social en España (y a nivel internacional) por conocer qué variables determinan el acceso a puestos de un consejo de administración y, sobre todo, qué variables explican la remuneración de estos cargos; remuneraciones que parecen injustificadas en algunos casos. En este sentido, han surgido recientemente una serie de medidas en España, dictadas por la Comisión Nacional del Mercado de Valores (CNMV), orientadas a lograr una mayor transparencia y comunicación en lo que se refiere a la situación económica de los miembros de los consejos de administración. En la elaboración de este Trabajo Fin de Máster se ha desarrollado un análisis econométrico de la remuneración de los miembros de los consejos de administración de las empresas del IBEX 35, empleando para ello los datos publicados por la Comisión Nacional del Mercado de Valores y los otros disponibles en las páginas web corporativas de las diferentes empresas analizadas. El estudio considera una gran variedad de variables explicativas de la remuneración en metálico del consejero en España, desde variables características de la empresa hasta otras que definen el perfil del individuo. Para buscar una trazabilidad en los datos y capturar mejor la tendencia actual, se han registrado datos de los tres últimos ejercicios económicos, desde 2015 hasta 2017.Nowadays, there is a public interest to know the truly reasons that justify the salary of directors and CEOs in Spain. Besides, we use different variables to explain the type of the required profile to be in the Board of Directors and the director’s salary where some of them could be considered unfair. Because of this, several standards have appeared in order to achieve a greater transparency and communication where CNMV plays a fundamental role to achieve these objectives. The TFM consists in an econometric analysis of director’s salary in IBEX 35 companies which is based on data provided by CNMV and the corporate website of IBEX 35 companies. The study includes a wide variety of parameters about the director’s salary in Spain as characteristic variables of the company and other variables about the individual. The present work searches the traceability in the data and it captures the current trend for the last three years, from 2015 to 2017.Universidad de Sevilla. Máster en Organización Industrial y Gestión de Empresa

Background PM10 atmosphere: In the seek of a multifractal characterization using complex networks

In the literature, several epidemiological studies have already associated respiratory and cardiovascular diseases to acute exposure of mineral dust. However, frail people are also sensitive to chronic exposure to particulate matter with an aerodynamic diameter 10μm or less (PM10). Consequently, it is crucial to better understand PM10 fluctuations at all scales. This study investigates PM10 background atmosphere in the Caribbean area according to African dust seasonality with complex network framework. For that purpose, the regular Visibility Graph (VG) and the new Upside-Down Visibility Graph (UDVG) are used for a multifractal analysis. Firstly, concentration vs degree (v-k) plots highlighted that high degree values (hubs behavior) are related to the highest PM10 concentrations in VG while hubs is associated to the lowest concentrations in UDVG, i.e. probably the background atmosphere. Then, the degree distribution analysis showed that VG and UDVG difference is reduced for high dust season contrary to the low one. As regards the multifractal analysis, the multifractal degree is higher for the low season in VG while it is higher for the high season in UDVG. The degree distribution behavior and the opposite trend in multifractal degree for UDVG are due to the increase of PM10 background atmosphere during the high season, i.e. from May to September. To sum up, UDGV is an efficient tool to perform noise fluctuations analysis in environmental time series where low concentrations play an important role as wel

Wet scavenging process of particulate matter (PM10): A multivariate complex network approach

Datos de investigación disponibles en: http://www.gwadair.frThis paper reports the results of research on PM10 wet scavenging by rainfall using a new multilayer complex networks called Multiplex Visibility Graphs (MVG). To the best of our knowledge, this work is the first to assess PM10 wet deposition using multivariate time series according to African dust seasonality. We considered 11 years of daily PM10 and rainfall data from the Guadeloupe archipelago. To analyse the impact of rainfall on PM10 behaviour, two MVG parameters were computed: the average edge overlap (ω) and the interlayer mutual information (IPM). On the 1-d scale, the ω results showed that the wet scavenging process was higher during the second half of the year when the high dust season and the rainy season are juxtaposed. This highlights a greater correlation between the microscopic structure of the signal, and the impact of rainfall on PM10 concentrations is more significant when the atmosphere is loaded with dust. The joint probability computed between the PM10 and rainfall nodes confirmed this trend. The IPM results indicated a correlation between PM10 and rainfall structures throughout the year. Furthermore, IPM values were higher during the transition periods between winter and summer (and vice versa). Our study showed that MVG is a powerful technique for investigating the relationship between at least two nonlinear time series using a multivariate time series

Checking complex networks indicators in search of singular episodes of the photochemical smog

A set of indicators derived from the analysis of complex networks have been introduced to identify singularities on a time series. To that end, the Visibility Graphs (VG) from three different signals related to photochemical smog (O3, NO2 concentration and temperature) have been computed. From the resulting complex network, the centrality parameters have been obtained and compared among them. Besides, they have been contrasted to two others that arise from a multifractal point of view, that have been widely used for singularity detection in many fields: the Hölder and singularity exponents (specially the first one of them). The outcomes show that the complex network indicators give equivalent results to those already tested, even exhibiting some advantages such as the unambiguity and the more selective results. This suggest a favorable position as supplementary sources of information when detecting singularities in several environmental variables, such as pollutant concentration or temperature

Relationships between Reference Evapotranspiration and Meteorological Variables in the Middle Zone of the Guadalquivir River Valley Explained by Multifractal Detrended Cross-Correlation Analysis

The multifractal relationship between reference evapotranspiration (ET0), computed by the Penmann-Monteith equation (PM), relative humidity (RH) and mean surface temperature (Tmean) was studied in the middle zone of the Guadalquivir River Valley (south Spain) in a previous study. This work extends that study to the average wind speed (U2) and solar radiation (SR), focusing on more recent years. All agro-meteorological variables were analyzed by multifractal detrended cross-correlation analysis (MFCCA) and multifractal detrended fluctuation analysis (MFDFA). The outcomes revealed persistent long-term autocorrelations, with Tmean and RH having the highest persistence (H>0.75). More precise results of multifractal properties than in the previous study were obtained for ET0, Tmean, and RH due to the elimination of trends in the signals. Only medium and large fluctuations in ET0 showed multifractal cross-correlations with its controlling factors, except for U2. Moreover, joint scaling exponents differed from individual exponents. These phenomena contrast with what has been observed in previous cross-correlation studies, revealing that some differences exist in the dynamics of multifractality among the analyzed variables. On the other hand, the Tmean–ET0 relation showed that extreme events in ET0 are mainly ruled by high temperature fluctuations, which match conclusions drawn in the previous study

Multifractal analysis application to the study of fat and its infiltration in Iberian ham: Influence of racial and feeding factors and type of slicing

This paper explores the multifractal features of different commercial designations of Iberian ham (acorn 100% Iberian ham, acorn Iberian ham, feed/pasture Iberian ham and feed Iberian ham). This study has been done by taking as input the fatty infiltration patterns obtained from digital image analysis of ham cuts comparing mechanic and manual slicing. The yielded results show the multifractal nature of fatty connective tissue in Iberian ham, only when knife cutting is applied, confirming the differences between the designations according to their genetics and feeding. Thus, the multifractal parameters presented in this work could be considered as additional information for checking Iberian ham quality by using non-destructive methods based on the combination of image analysis and predictive techniques. Meat industry can take advantage of these methods to evaluate meat products, especially when fat-connective tissue with complex pattern distribution is involved

Multifractal characterisation of particulate matter (PM10) time series in the Caribbean basin using visibility graphs

Datos de investigación disponibles en: http://www.gwadair.frA good knowledge of pollutant time series behavior is fundamental to elaborate strategies and construct tools to protect human health. In Caribbean area, air quality is frequently deteriorated by the transport of African dust. In the literature, it is well known that exposure to particulate matter with an aerodynamic diameter of 10 μm or less (PM10) have many adverse health effects as respiratory and cardiovascular diseases. To our knowledge, no study has yet performed an analysis of PM10 time series using complex network framework. In this study, the so-called Visibility Graph (VG) method is used to describe PM10 dynamics in Guadeloupe archipelago with a database of 11 years. Firstly, the fractal nature of PM10 time series is highlighted using degree distribution for all data, low dust season (October to April) and high dust season (May to September). Thereafter, a profound description of PM10 time series dynamics is made using multifractal analysis through two approaches, i.e. Rényi and singularity spectra. Achieved results are consistent with PM10 behavior in the Caribbean basin. Both methods showed a higher multifractality degree during the low dust season. In addition, multifractal parameters exhibited that the low dust season has the higher recurrence and the lower uniformity degrees. Lastly, centrality measures (degree, closeness and betweenness) highlighted PM10 dynamics through the year with a decay of centrality values during the high dust season. To conclude, all these results clearly showed that VG is a robust tool to describe times series properties

Visibility graphs of ground-level ozone time series: A multifractal analysis

A recent method based on the concurrence of complex networks and multifractal analyses is applied for the first time to explore ground-level ozone behavior. Ozone time series are converted into complex networks for their posterior analysis. The searched purpose is to check the suitability of this transformation and to see whether some features of these complex networks could constitute a preliminary analysis before the more thorough multifractal formalism. Results show effectively that the exposed transformation stores the original information about the ozone dynamics and gives meaningful knowledge about the time series. Based on these results, the multifractal analysis of the complex networks is performed. Looking at the physical meaning of the multifractal properties (such as fractal dimensions and singularity spectrum), a relationship between those and the degree distribution of the complex networks is found. In addition to all the promising results, this novel connection between time series and complex networks can deal with both stationary and non-stationary time series, overcoming one of the main limitations of multifractal analysis. Therefore, this technique can be regarded as an alternative to give supplementary information within the study of complex signals

Multifractal fluctuations of the precipitation in Spain (1960–2019)

Datos de investigación disponibles en: http://www.aemet.es/es/datos_abiertos/AEMET_OpenDataIn this work, an analysis of multifractal parameters of daily precipitation series over the Iberian Peninsula was performed in two 30-year periods to explore whether these properties follow any pattern. Fluctuations of precipitation series show three different scaling regions. Only two distinct regimes for small and large timescales can be confirmed, while intermediate scales are part of a transition region. It is also observed a certain degree of multifractality, which is higher for small timescales. At these scales, there is a high persistence which follows the spatial gradient of the annual precipitation. Moreover, multifractal parameters of the precipitation are modified according to complex spatial and temporal patterns. Only persistence uniformly decreases in the last period. Other relevant findings are the changes in the asymmetry of multifractal spectra in the eastern belt at larger timescales, which might be related to the change in the behavior of the Mediterranean cyclones.Datos de investigación disponibles en: http://www.aemet.es/es/datos_abiertos/AEMET_OpenDaDatos de investigación disponibles en: http://www.aemet.es/es/datos_abiertos/AEMET_OpenD