Copulas in finance and insurance

Copulas provide a potential useful modeling tool to represent the dependence structure among variables and to generate joint distributions by combining given marginal distributions. Simulations play a relevant role in finance and insurance. They are used to replicate efficient frontiers or extremal values, to price options, to estimate joint risks, and so on. Using copulas, it is easy to construct and simulate from multivariate distributions based on almost any choice of marginals and any type of dependence structure. In this paper we outline recent contributions of statistical modeling using copulas in finance and insurance. We review issues related to the notion of copulas, copula families, copula-based dynamic and static dependence structure, copulas and latent factor models and simulation of copulas. Finally, we outline hot topics in copulas with a special focus on model selection and goodness-of-fit testing

From Teasing to Torment: School Climate Revisited - A Survey of U.S. Secondary School Students and Teachers

From Teasing to Torment: School Climate Revisited, A Survey of U.S. Secondary School Students and Teachers provides an in-depth look at the current landscape of bias and peer victimization as reported by students and teachers from across the nation. In addition to examining various types of bias, including those based on race/ethnicity, religion, body size, and ability, this report provides a focused look at LGBTQ issues in secondary schools. Comparing findings to a similar survey we conducted in 2005, the report discusses the progress that has been made over the past ten years, as well as highlights the challenges that remain. It also offers recommendations and strategies to improve school climate for all students.Specifically, the research report addresses:Student and teacher perceptions of school climate; Student experiences of safety, bullying, and harassment, including biased incidents based on race/ethnicity, sexual orientation, body size, gender, religion, ability, economic status, and gender expression;Teacher intervention in bullying and incidents of bias; LGBT-supportive teacher practices, such as advising GSA or including LGBT content in teaching;Teacher professional development (pre-service and in-service) in bullying, diversity, and LGBT issues; andDifferences in students' school experiences based on race/ethnicity, LGBTQ status, gender nonconformity, and geography (i.e., urbanicity, region), among others

Practical volatility and correlation modeling for financial market risk management

What do academics have to offer market risk management practitioners in financial institutions? Current industry practice largely follows one of two extremely restrictive approaches: historical simulation or RiskMetrics. In contrast, we favor flexible methods based on recent developments in financial econometrics, which are likely to produce more accurate assessments of market risk. Clearly, the demands of real-world risk management in financial institutions - in particular, real-time risk tracking in very high-dimensional situations - impose strict limits on model complexity. Hence we stress parsimonious models that are easily estimated, and we discuss a variety of practical approaches for high-dimensional covariance matrix modeling, along with what we see as some of the pitfalls and problems in current practice. In so doing we hope to encourage further dialog between the academic and practitioner communities, hopefully stimulating the development of improved market risk management technologies that draw on the best of both worlds

Copulas in finance and insurance

Copulas provide a potential useful modeling tool to represent the dependence structure among variables and to generate joint distributions by combining given marginal distributions. Simulations play a relevant role in finance and insurance. They are used to replicate efficient frontiers or extremal values, to price options, to estimate joint risks, and so on. Using copulas, it is easy to construct and simulate from multivariate distributions based on almost any choice of marginals and any type of dependence structure. In this paper we outline recent contributions of statistical modeling using copulas in finance and insurance. We review issues related to the notion of copulas, copula families, copula-based dynamic and static dependence structure, copulas and latent factor models and simulation of copulas. Finally, we outline hot topics in copulas with a special focus on model selection and goodness-of-fit testing.Dependence structure, Extremal values, Copula modeling, Copula review

Relations Between Dispositional Expressivity and Physiological Changes During Acute Positive and Negative Affect

The aim of the present study is to examine the relations between emotional expressivity measured by Berkeley Expressivity Questionnaire and physiological response in situations where positive and negative affects were induced. On 65 participants four physiological parameters, including finger pulse amplitude, heart rate, skin conductance level and amplitude of skin conductance response were measured. In situations in which negative affect was induced, individuals higher in negative expressivity showed higher skin conductance level, higher amplitude of skin conductance response and higher heart rate compared to individuals low on negative expressivity, whereas finger pulse amplitude did not differ between these two groups. The same results were obtained even when controlling for five factor personality traits and recorded participants’ facial expression. In situation where a positive affect was induced, no differences in sympathetic responses between participants high and low in positive expressivity have been found. The results are explained in the context of Coactivation theory and possible consequences of the results on health outcomes are discussed