This dataset contains records of the solar spectral energy irradiance (W m<sup>-2</sup&g... more This dataset contains records of the solar spectral energy irradiance (W m<sup>-2</sup> nm<sup>-1</sup>) in the understorey of forest stands at Lammi Biological Station, southern Finland (61◦ 3.24' N, 25◦ 118 2.23' E) during the spring of 2015. These spectra allow the change in spectral energy irradiance to be followed through the period of canopy leaf flush. Records are the average of recorded spectra from four points recorded at 40-cm above the forest floor using a Maya 2000 Pro array spectrometer. Spectra were recorded from exactly the same location on three dates, 2015-04-25, 2015-05-22, and 2015-06-05, before, during and after leaf flush. Data were recorded from the understorey of a young Betula stand, an old Betula stand, an old mixed Betula stand, a Quercus stand, and a Picea stand, in three positions: shade, semi-shade from leaves, and full sun in a sunfleck. On each occasion control measurements of spectral energy irradiance in full sun of an open field were also recorded at the beginning, middle and end of each measurement period. All measurements were made during the 2 hours either side of solar noon, on clear-sky days. Details of the sampling method and interpretation are given in the paper, Hartikainen et al., (2018) in Ecology and Evolution, which showcases the use of Thick Pen Transform to compare spectra.
This study compares the share of male/female as first authors, the growth of authors per paper, a... more This study compares the share of male/female as first authors, the growth of authors per paper, and the differences in publication productivity in the last decade of the most cited authors versus the field of communication (i.e., a representative sample of papers published in the field of communication). Results indicate that there are significantly more female first authors in the field than a decade ago, but their proportion among the most cited authors has not grown at a similar pace. Likewise, the number of authors per paper has significantly increased in the field, but not among the most cited authors, who, in turn, publish significantly more papers than the field, both in 2009 and 2019. And not only that, the productivity gap between the most cited authors and the field has substantially increased between the span of this decade. Theoretical implications of these findings and suggestions for future studies are also discussed.
In this work, we design a protocol to obtain global indicators of health and well-being from weig... more In this work, we design a protocol to obtain global indicators of health and well-being from weighted and longitudinal heterogeneous multivariate data. First, we consider a set of thematic sub-indicators of interest observed in several periods. Next, we combine them using the Common Principal Component (CPC) model. For this purpose, we put a new straightforward CPC model to cope with weighted and longitudinal data and develop a new statistic to test the validity of the CPC-longitudinal model, whose distribution is obtained by stratified bootstrap. To illustrate this methodology, we use data from the last three waves of the Survey of Health, Ageing and Retirement in Europe (SHARE), which is the largest cross-European social science panel study data set covering insights into the public health and socio-economic living conditions of European individuals. In particular, we first design four thematic indicators that focus on general health status, dependency situation, self-perceived he...
In this study, we propose a hyper-simplified indicator of health and well-being for data visualiz... more In this study, we propose a hyper-simplified indicator of health and well-being for data visualization purposes in large datasets and apply it to SHARE survey data, the largest macro survey on health, ageing and retirement for 18 European countries. The indicator is based on four thematic sub-indicators, each focussing on a particular issue, which are obtained from more than twenty mixed variables measured on more than 60,000 respondents; Next, PCA is used to summarize their information in order to find and visualize profiles of “healthy ageing” across Europe. As a result, EU countries are classified in three groups, that segment the database into the least to the most individuals at risk of health and well-being. The methodology we propose is wide enough to be extended to other surveys or disciplines.
More than two years after the great outbreak of COVID suffered in almost the whole world, and in ... more More than two years after the great outbreak of COVID suffered in almost the whole world, and in particular in Europe, we have gradually learned about the direct effects of this virus on our health and what consequences it can have if we become infected. However, this pandemic also had great economic and social consequences that affected people in an indirect way, which we can call COVID side effects. In this work we carried out an innovative type of analysis based on the concept of archetypoids in order to find extreme observations in a database of mixed-type data and used them to classify individuals yielding to different health and behavioural profiles in coping with the COVID outbreak in the EU. We use data from the first COVID-19 Survey of the SHARE project (Survey on Health, Aging and Retirement in Europe). The resulting profiles are easier to interpret than others based on central observations, and help to understand how the situations of restrictions and lock-downs affected ...
One of the consequences of the big data revolution is that data are more heterogeneous than ever.... more One of the consequences of the big data revolution is that data are more heterogeneous than ever. A new challenge appears when mixed-type data sets evolve over time and we are interested in the comparison among individuals. In this work, we propose a new protocol that integrates robust distances and visualization techniques for dynamic mixed data. In particular, given a time t∈T={1,2,…,N}, we start by measuring the proximity of n individuals in heterogeneous data by means of a robustified version of Gower’s metric (proposed by the authors in a previous work) yielding to a collection of distance matrices {D(t),∀t∈T}. To monitor the evolution of distances and outlier detection over time, we propose several graphical tools: First, we track the evolution of pairwise distances via line graphs; second, a dynamic box plot is obtained to identify individuals which showed minimum or maximum disparities; third, to visualize individuals that are systematically far from the others and detect po...
International Journal of Environmental Research and Public Health
Measuring the health and wellbeing of the population is the first step in visualizing the real ne... more Measuring the health and wellbeing of the population is the first step in visualizing the real needs of the population in order to promote healthy habits, as well as effective health and social policy responses [...]
The aging of population is perhaps the most important problem that developed countries must face ... more The aging of population is perhaps the most important problem that developed countries must face in the near future. Dependency can be seen as a consequence of the process of gradual aging. In a health context, this contingency is defined as a lack of autonomy in performing basic activities of daily living that requires the care of another person or significant help. In Europe in general and in Spain in particular this phenomena represents a problem with economic, political, social and demographic implications. The prevalence of dependency in the population, as well as its intensity and its evolution over the course of a person's life are issues of greatest importance that should be addressed. The aim of this work is to estimate life expectancy free of dependency (LEFD) using categorical data and individual dependency trajectories that are obtained using the whole medical history concerning the dependency situation of each individual from birth up to 2008, contained in database ...
Survey data are usually of mixed type (quantitative, multistate categorical, and/or binary variab... more Survey data are usually of mixed type (quantitative, multistate categorical, and/or binary variables). Multidimensional scaling (MDS) is one of the most extended methodologies to visualize the profile structure of the data. Since the past 60s, MDS methods have been introduced in the literature, initially in publications in the psychometrics area. Nevertheless, sensitivity and robustness of MDS configurations have been topics scarcely addressed in the specialized literature. In this work, we are interested in the construction of robust profiles for mixed-type data using a proper MDS configuration. To this end, we propose to compare different MDS configurations (coming from different metrics) through a combination of sensitivity and robust analysis. In particular, as an alternative to classical Gower’s metric, we propose a robust joint metric combining different distance matrices, avoiding redundant information, via related metric scaling. The search for robustness and identification ...
Outliers in financial data can lead to model parameter estimation biases, invalid inferences and ... more Outliers in financial data can lead to model parameter estimation biases, invalid inferences and poor volatility forecasts. Therefore, their detection and correction should be taken seriously when modeling financial data. This paper focuses on these issues and proposes a general detection and correction method based on wavelets that can be applied to a large class of volatility models. The effectiveness of our proposal is tested by an intensive Monte Carlo study for six well known volatility models and compared to alternative proposals in the literature, before applying it to three daily stock market indexes. The Monte Carlo experiments show that our method is both very effective in detecting isolated outliers and outlier patches and much more reliable than other wavelet-based procedures since it detects a significant smaller number of false outliers.
In this paper we estimate, for several investment horizons, minimum capital risk requirements for... more In this paper we estimate, for several investment horizons, minimum capital risk requirements for short and long positions, using the unconditional distribution of three daily indexes futures returns and a set of GARCH-type and stochastic volatility models. We consider the possibility that errors follow a t-Student distribution in order to capture the kurtosis of the returns distributions. The results suggest that an accurate modeling of extreme returns obtained for long and short trading investment positions is possible with a simple autoregressive stochastic volatility model. Moreover, modeling volatility as a fractional integrated process produces, in general, excessive volatility persistence and consequently leads to large minimum capital risk requirement estimates. The performance of models is assessed with the help of out-of-sample tests and p-values of them are reported.
RE-TREAT project aims to boost changes in the criminal proceedings within the justice systems in ... more RE-TREAT project aims to boost changes in the criminal proceedings within the justice systems in order to improve their responsiveness to the particular needs of victims of sexual crimes. This report examines the obstacles that victims of sexual violence in Spain may face when reporting and the eventual criminal proceedings at different stages.
This dataset contains records of the solar spectral energy irradiance (W m<sup>-2</sup&g... more This dataset contains records of the solar spectral energy irradiance (W m<sup>-2</sup> nm<sup>-1</sup>) in the understorey of forest stands at Lammi Biological Station, southern Finland (61◦ 3.24' N, 25◦ 118 2.23' E) during the spring of 2015. These spectra allow the change in spectral energy irradiance to be followed through the period of canopy leaf flush. Records are the average of recorded spectra from four points recorded at 40-cm above the forest floor using a Maya 2000 Pro array spectrometer. Spectra were recorded from exactly the same location on three dates, 2015-04-25, 2015-05-22, and 2015-06-05, before, during and after leaf flush. Data were recorded from the understorey of a young Betula stand, an old Betula stand, an old mixed Betula stand, a Quercus stand, and a Picea stand, in three positions: shade, semi-shade from leaves, and full sun in a sunfleck. On each occasion control measurements of spectral energy irradiance in full sun of an open field were also recorded at the beginning, middle and end of each measurement period. All measurements were made during the 2 hours either side of solar noon, on clear-sky days. Details of the sampling method and interpretation are given in the paper, Hartikainen et al., (2018) in Ecology and Evolution, which showcases the use of Thick Pen Transform to compare spectra.
This study compares the share of male/female as first authors, the growth of authors per paper, a... more This study compares the share of male/female as first authors, the growth of authors per paper, and the differences in publication productivity in the last decade of the most cited authors versus the field of communication (i.e., a representative sample of papers published in the field of communication). Results indicate that there are significantly more female first authors in the field than a decade ago, but their proportion among the most cited authors has not grown at a similar pace. Likewise, the number of authors per paper has significantly increased in the field, but not among the most cited authors, who, in turn, publish significantly more papers than the field, both in 2009 and 2019. And not only that, the productivity gap between the most cited authors and the field has substantially increased between the span of this decade. Theoretical implications of these findings and suggestions for future studies are also discussed.
In this work, we design a protocol to obtain global indicators of health and well-being from weig... more In this work, we design a protocol to obtain global indicators of health and well-being from weighted and longitudinal heterogeneous multivariate data. First, we consider a set of thematic sub-indicators of interest observed in several periods. Next, we combine them using the Common Principal Component (CPC) model. For this purpose, we put a new straightforward CPC model to cope with weighted and longitudinal data and develop a new statistic to test the validity of the CPC-longitudinal model, whose distribution is obtained by stratified bootstrap. To illustrate this methodology, we use data from the last three waves of the Survey of Health, Ageing and Retirement in Europe (SHARE), which is the largest cross-European social science panel study data set covering insights into the public health and socio-economic living conditions of European individuals. In particular, we first design four thematic indicators that focus on general health status, dependency situation, self-perceived he...
In this study, we propose a hyper-simplified indicator of health and well-being for data visualiz... more In this study, we propose a hyper-simplified indicator of health and well-being for data visualization purposes in large datasets and apply it to SHARE survey data, the largest macro survey on health, ageing and retirement for 18 European countries. The indicator is based on four thematic sub-indicators, each focussing on a particular issue, which are obtained from more than twenty mixed variables measured on more than 60,000 respondents; Next, PCA is used to summarize their information in order to find and visualize profiles of “healthy ageing” across Europe. As a result, EU countries are classified in three groups, that segment the database into the least to the most individuals at risk of health and well-being. The methodology we propose is wide enough to be extended to other surveys or disciplines.
More than two years after the great outbreak of COVID suffered in almost the whole world, and in ... more More than two years after the great outbreak of COVID suffered in almost the whole world, and in particular in Europe, we have gradually learned about the direct effects of this virus on our health and what consequences it can have if we become infected. However, this pandemic also had great economic and social consequences that affected people in an indirect way, which we can call COVID side effects. In this work we carried out an innovative type of analysis based on the concept of archetypoids in order to find extreme observations in a database of mixed-type data and used them to classify individuals yielding to different health and behavioural profiles in coping with the COVID outbreak in the EU. We use data from the first COVID-19 Survey of the SHARE project (Survey on Health, Aging and Retirement in Europe). The resulting profiles are easier to interpret than others based on central observations, and help to understand how the situations of restrictions and lock-downs affected ...
One of the consequences of the big data revolution is that data are more heterogeneous than ever.... more One of the consequences of the big data revolution is that data are more heterogeneous than ever. A new challenge appears when mixed-type data sets evolve over time and we are interested in the comparison among individuals. In this work, we propose a new protocol that integrates robust distances and visualization techniques for dynamic mixed data. In particular, given a time t∈T={1,2,…,N}, we start by measuring the proximity of n individuals in heterogeneous data by means of a robustified version of Gower’s metric (proposed by the authors in a previous work) yielding to a collection of distance matrices {D(t),∀t∈T}. To monitor the evolution of distances and outlier detection over time, we propose several graphical tools: First, we track the evolution of pairwise distances via line graphs; second, a dynamic box plot is obtained to identify individuals which showed minimum or maximum disparities; third, to visualize individuals that are systematically far from the others and detect po...
International Journal of Environmental Research and Public Health
Measuring the health and wellbeing of the population is the first step in visualizing the real ne... more Measuring the health and wellbeing of the population is the first step in visualizing the real needs of the population in order to promote healthy habits, as well as effective health and social policy responses [...]
The aging of population is perhaps the most important problem that developed countries must face ... more The aging of population is perhaps the most important problem that developed countries must face in the near future. Dependency can be seen as a consequence of the process of gradual aging. In a health context, this contingency is defined as a lack of autonomy in performing basic activities of daily living that requires the care of another person or significant help. In Europe in general and in Spain in particular this phenomena represents a problem with economic, political, social and demographic implications. The prevalence of dependency in the population, as well as its intensity and its evolution over the course of a person's life are issues of greatest importance that should be addressed. The aim of this work is to estimate life expectancy free of dependency (LEFD) using categorical data and individual dependency trajectories that are obtained using the whole medical history concerning the dependency situation of each individual from birth up to 2008, contained in database ...
Survey data are usually of mixed type (quantitative, multistate categorical, and/or binary variab... more Survey data are usually of mixed type (quantitative, multistate categorical, and/or binary variables). Multidimensional scaling (MDS) is one of the most extended methodologies to visualize the profile structure of the data. Since the past 60s, MDS methods have been introduced in the literature, initially in publications in the psychometrics area. Nevertheless, sensitivity and robustness of MDS configurations have been topics scarcely addressed in the specialized literature. In this work, we are interested in the construction of robust profiles for mixed-type data using a proper MDS configuration. To this end, we propose to compare different MDS configurations (coming from different metrics) through a combination of sensitivity and robust analysis. In particular, as an alternative to classical Gower’s metric, we propose a robust joint metric combining different distance matrices, avoiding redundant information, via related metric scaling. The search for robustness and identification ...
Outliers in financial data can lead to model parameter estimation biases, invalid inferences and ... more Outliers in financial data can lead to model parameter estimation biases, invalid inferences and poor volatility forecasts. Therefore, their detection and correction should be taken seriously when modeling financial data. This paper focuses on these issues and proposes a general detection and correction method based on wavelets that can be applied to a large class of volatility models. The effectiveness of our proposal is tested by an intensive Monte Carlo study for six well known volatility models and compared to alternative proposals in the literature, before applying it to three daily stock market indexes. The Monte Carlo experiments show that our method is both very effective in detecting isolated outliers and outlier patches and much more reliable than other wavelet-based procedures since it detects a significant smaller number of false outliers.
In this paper we estimate, for several investment horizons, minimum capital risk requirements for... more In this paper we estimate, for several investment horizons, minimum capital risk requirements for short and long positions, using the unconditional distribution of three daily indexes futures returns and a set of GARCH-type and stochastic volatility models. We consider the possibility that errors follow a t-Student distribution in order to capture the kurtosis of the returns distributions. The results suggest that an accurate modeling of extreme returns obtained for long and short trading investment positions is possible with a simple autoregressive stochastic volatility model. Moreover, modeling volatility as a fractional integrated process produces, in general, excessive volatility persistence and consequently leads to large minimum capital risk requirement estimates. The performance of models is assessed with the help of out-of-sample tests and p-values of them are reported.
RE-TREAT project aims to boost changes in the criminal proceedings within the justice systems in ... more RE-TREAT project aims to boost changes in the criminal proceedings within the justice systems in order to improve their responsiveness to the particular needs of victims of sexual crimes. This report examines the obstacles that victims of sexual violence in Spain may face when reporting and the eventual criminal proceedings at different stages.
New points can be superimposed on a Euclidean configuration obtained as a result of a metric Mult... more New points can be superimposed on a Euclidean configuration obtained as a result of a metric Multidimensional Scaling at coordinates given by Gower’s interpolation formula. The procedure amounts to discarding a, possibly non-null, coordinate along an additional dimension. We compute this error term, assessing
its influence on distance-based predictions.
Distance-based regression allows for a neat implementation of the Partial Least Squares recurrenc... more Distance-based regression allows for a neat implementation of the Partial Least Squares recurrence. In this paper we address practical issues arising when dealing with moderately large datasets (n ~ 104) such as those typical of automobile insurance premium calculations.
In a previous paper (Grané and Fortiana 2006) we studied a flexible class of goodness-of-fit test... more In a previous paper (Grané and Fortiana 2006) we studied a flexible class of goodness-of-fit tests associated with an orthogonal sequence, the Karhunen-Loève decomposition of a stochastic process derived from the null hypothesis. Generally speaking, these tests outperform Kolmogorov-Smirnov and Cramér-von Mises, but we registered several exceptions. In this work we investigate the cause of these anomalies and, more precisely,
In Fortiana and Grané (2002) we study a scale-free statistic, based on Hoeffding's maximum co... more In Fortiana and Grané (2002) we study a scale-free statistic, based on Hoeffding's maximum correlation, for testing exponentiality. This statistic admits an expansion along a countable set of orthogonal axes, originating a sequence of statistics. Linear combinations of a given number p of terms in this sequence can be written as a quotient of L-statistics. In this paper we propose
In this paper we estimate, for several investment horizons, minimum capital risk requirements for... more In this paper we estimate, for several investment horizons, minimum capital risk requirements for short and long positions, using the unconditional distribution of three daily indexes futures returns and a set of GARCH-type and stochastic volatility models. We consider the possibility that errors follow a t-Student distribution in order to capture the kurtosis of the returns distributions. The results suggest
Outliers in financial data can lead to model parameter estimation biases, invalid inferences and ... more Outliers in financial data can lead to model parameter estimation biases, invalid inferences and poor volatility forecasts. Therefore, their detection and correction should be taken seriously when modeling financial data. This paper focuses on these issues and proposes a general detection and correction method based on wavelets that can be applied to a large class of volatility models. The effectiveness
In this paper, we estimate minimum capital risk requirements for short, long positions and three ... more In this paper, we estimate minimum capital risk requirements for short, long positions and three investment horizons, using the traditional GARCH model and two other GARCH-type models that incorporate the possibility of asymmetric responses of volatility to price changes; and, ...
In this paper we focus on the impact of additive level outliers on the calculation of risk measur... more In this paper we focus on the impact of additive level outliers on the calculation of risk measures, such as minimum capital risk requirements, and compare four alternatives of reducing these measures' estimation biases. The first three proposals proceed by detecting and correcting outliers before estimating these risk measures with the GARCH(1,1) model, while the fourth procedure fits a Student’s
Multidimensional scaling (MDS) techniques are initially proposed to produce pictorial representat... more Multidimensional scaling (MDS) techniques are initially proposed to produce pictorial representations of distance, dissimilarity or proximity data. Sensitivity and robustness assessment of multivariate methods is essential if inferences are to be drawn from the analysis. To our knowledge, the literature related to MDS for mixed-type data, including variables measured at continuous level besides categorical ones, is quite scarce. The main
In this paper we study the goodness-of-fit test introduced by Fortiana and Grané (2003) and Grané... more In this paper we study the goodness-of-fit test introduced by Fortiana and Grané (2003) and Grané (2012), in the context of randomly censored data. We construct a new test statistic under general right-censoring, i.e., with unknown censoring distribution, and prove its asymptotic properties. Additionally, we study a special case, when the censoring mechanism follows the well-known Koziol-Green model. We present an extensive simulation study on the empirical power of these two versions of the test statistic. We show the good performance of these statistics in detecting symmetrical alternatives and their advantages over the most famous Pearson-type test proposed by Akritas (1988). Finally, we apply our test to the head-and-neck cancer data.
The interaction between mathematicians, statisticians and econometricians working in actuarial sc... more The interaction between mathematicians, statisticians and econometricians working in actuarial sciences and finance is producing numerous meaningful scientific results. This volume introduces new ideas, in the form of four-page papers, presented at the international conference Mathematical and Statistical Methods for Actuarial Sciences and Finance (MAF), held at Universidad Carlos III de Madrid (Spain), 4th-6th April 2018.
The book covers a wide variety of subjects in actuarial science and financial fields, all discussed in the context of the cooperation between the three quantitative approaches. The topics include: actuarial models; analysis of high frequency financial data; behavioural finance; carbon and green finance; credit risk methods and models; dynamic optimization in finance; financial econometrics; forecasting of dynamical actuarial and financial phenomena; fund performance evaluation; insurance portfolio risk analysis; interest rate models; longevity risk; machine learning and soft-computing in finance; management in insurance business; models and methods for financial time series analysis, models for financial derivatives; multivariate techniques for financial markets analysis; optimization in insurance; pricing; probability in actuarial sciences, insurance and finance; real world finance; risk management; solvency analysis; sovereign risk; static and dynamic portfolio selection and management; trading systems.
This book is a valuable resource for academics, PhD students, practitioners, professionals and researchers, and is also of interest to other readers with quantitative background knowledge.
Existe abundante evidencia, y es cada vez más reconocido, que la solución a los problemas a los q... more Existe abundante evidencia, y es cada vez más reconocido, que la solución a los problemas a los que se enfrentan las sociedades en el siglo XXI va a requerir enfoques interdisciplinarios, donde la mezcla de conocimientos de expertos de distintos campos genere formas nuevas de abordar viejos problemas. En particular, la digitalización de la información, la capacidad creciente de recoger datos con bajo coste y de transmitirlos y analizarlos a gran velocidad, el llamado entorno Big Data, está aportando nueva evidencia empírica para transformar muchas facetas de nuestra sociedad. Este cambio, sin embargo, no se producido aún en el terreno de la justicia, que tiene hondas raíces ancladas en la tradición. Sin embargo, es patente la necesidad de transformar nuestro sistema legal para adaptarlo a las necesidades actuales: según el Barómetro Externo encargado por el Consejo General de la Abogacía Española, la mayoría de los ciudadanos creen que la Administración de Justicia funciona mal, siendo lenta e ineficaz. Cualquier propuesta sensata para modificar nuestro sistema legal debe partir de los datos que describan su funcionamiento actual, y este libro es especialmente bienvenido al representar un avance pionero en esta dirección.
Los resultados del estudio que describe esta obra ilustran cómo la colaboración entre juristas y estadísticos puede desvelar las deficiencias y sugerir soluciones en problemas legales de gran importancia social.
Este trabajo contiene los resultados de la investigación sobre la eficacia de la ejecución de las... more Este trabajo contiene los resultados de la investigación sobre la eficacia de la ejecución de las indemnizaciones a favor de las víctimas contenidas en las sentencias penales de condena. Se ha realizado un estudio de campo de las ejecutorias en los Juzgados de lo Penal y la Audiencia Provincial de Madrid. El objetivo principal es evaluar la eficacia de la reparación económica a la víctima. El estudio de campo se realizó en dos etapas, octubre de 2015 y octubre de 2016, y la población objetivo está formada por todos los expedientes de ejecutorias en la Comunidad de Madrid desde 2012 hasta 2015, excluyendo delitos menores y delitos relacionados con delitos de tránsito y violencia de género, así como aquellos donde no hay víctima. Los principales hallazgos son que, en su mayoría, las indemnizaciones dictadas en sentencia en los procedimientos penales no son pagadas por los condenados: a pesar de que los tribunales establecen altas indemnizaciones, tanto en los Juzgados de lo Penal como en la Audiencia Provincial, la mayoría de las víctimas y los maltratados reciben menos de 300 € en concepto de indemnización. Por otro lado, la ayuda económica de la Administración española a las víctimas es casi inexistente. Otros hallazgos relevantes son: Primero, para aquellas personas que acaban cobrando al menos una parte de la indemnización, el período entre la comisión del ilícito y el pago es de aproximadamente 5 años en promedio; En segundo lugar, es más probable que la indemnización se pague cuando la persona condenada no ingresa en prisión; En tercer lugar, en general, no se utilizan mecanismos de seguro de responsabilidad civil; En la fase de investigación, solo se adoptan medidas cautelares en el 15% de los casos. Todas estas situaciones reflejan la violación de los parámetros de justicia europeos con respecto a la reparación a las víctimas.
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its influence on distance-based predictions.
The book covers a wide variety of subjects in actuarial science and financial fields, all discussed in the context of the cooperation between the three quantitative approaches. The topics include: actuarial models; analysis of high frequency financial data; behavioural finance; carbon and green finance; credit risk methods and models; dynamic optimization in finance; financial econometrics; forecasting of dynamical actuarial and financial phenomena; fund performance evaluation; insurance portfolio risk analysis; interest rate models; longevity risk; machine learning and soft-computing in finance; management in insurance business; models and methods for financial time series analysis, models for financial derivatives; multivariate techniques for financial markets analysis; optimization in insurance; pricing; probability in actuarial sciences, insurance and finance; real world finance; risk management; solvency analysis; sovereign risk; static and dynamic portfolio selection and management; trading systems.
This book is a valuable resource for academics, PhD students, practitioners, professionals and researchers, and is also of interest to other readers with quantitative background knowledge.
Los resultados del estudio que describe esta obra ilustran cómo la colaboración entre juristas y estadísticos puede desvelar las deficiencias y sugerir soluciones en problemas legales de gran importancia social.