Multivariate extremes and the aggregation of dependent risks: examples and counter-examples

Properties of risk measures for extreme risks have become an important topic of research. In the present paper we discuss sub- and superadditivity of quantile based risk measures and show how multivariate extreme value theory yields the ideal modeling environment. Numerous examples and counter-examples highlight the applicability of the main results obtaine

The Quantitative Modeling of Operational Risk: Between G-and-H and EVT

Operational risk has become an important risk component in the banking and insurance world. The availability of (few) reasonable data sets has given some authors the opportunity to analyze operational risk data and to propose different models for quantification. As proposed in Dutta and Perry [12], the parametric g-and-h distribution has recently emerged as an interesting candidate. In our paper, we discuss some fundamental properties of the g-and-h distribution and their link to extreme value theory (EVT). We show that for the g-and-h distribution, convergence of the excess distribution to the generalized Pareto distribution (GPD) is extremely slow and therefore quantile estimation using EVT may lead to inaccurate results if data are well modeled by a g-and-h distribution. We further discuss the subadditivity property of Value-at-Risk (VaR) for g-and-h random variables and show that for reasonable g and h parameter values, superadditivity may appear when estimating high quantiles. Finally, we look at the g-and-h distribution in the one-claim-causes-ruin paradig

Pharmacovigilance in pregnancy: adverse drug reactions associated with fetal disorders

Objective: To provide the first update on drug safety profiles and adverse drug reactions (ADRs) associated with fetal disorders from the Swiss national ADR database. Methods: We conducted a retrospective study using data from 202 pharmacovigilance reports on drug-associated fetal disorders from the Swiss national ADR database from 1990 to 2009. Evaluated aspects included administrative information on the report, drug exposure, and disorders. Results: The ADR reporting frequency on the topic of fetal disorders has increased during the last 20 years, from only 1 report in 1991 to a maximum of 31 reports in 2008. Nervous system drugs were the most frequently reported drug group (40.2%) above all antidepressants and antiepileptics. The highest level of overall drug intake could be observed for the 1st trimester (85.4%), especially for the first 6 weeks of pregnancy. The most frequently reported types of fetal disorders were malformations (68.8%), especially those of the musculoskeletal and circulatory systems. A positive association was discovered between antiepileptics and malformations in general and in particular of the circulatory system and the eye, ear, face, and neck. Conclusions: The results suggest that the nervous system drug group bears an especially high risk for malformations. The most commonly identified drug exposures can help focus pharmacoepidemiologic efforts in drug-induced birth defect

Failure Probability Under Parameter Uncertainty

In many problems of risk analysis, failure is equivalent to the event of a random risk factor exceeding a given threshold. Failure probabilities can be controlled if a decisionmaker is able to set the threshold at an appropriate level. This abstract situation applies, for example, to environmental risks with infrastructure controls; to supply chain risks with inventory controls; and to insurance solvency risks with capital controls. However, uncertainty around the distribution of the risk factor implies that parameter error will be present and the measures taken to control failure probabilities may not be effective. We show that parameter uncertainty increases the probability (understood as expected frequency) of failures. For a large class of loss distributions, arising from increasing transformations of location-scale families (including the log-normal, Weibull, and Pareto distributions), the article shows that failure probabilities can be exactly calculated, as they are independent of the true (but unknown) parameters. Hence it is possible to obtain an explicit measure of the effect of parameter uncertainty on failure probability. Failure probability can be controlled in two different ways: (1) by reducing the nominal required failure probability, depending on the size of the available data set, and (2) by modifying of the distribution itself that is used to calculate the risk control. Approach (1) corresponds to a frequentist/regulatory view of probability, while approach (2) is consistent with a Bayesian/personalistic view. We furthermore show that the two approaches are consistent in achieving the required failure probability. Finally, we briefly discuss the effects of data pooling and its systemic risk implications

Implementing Loss Distribution Approach for Operational Risk

To quantify the operational risk capital charge under the current regulatory framework for banking supervision, referred to as Basel II, many banks adopt the Loss Distribution Approach. There are many modeling issues that should be resolved to use the approach in practice. In this paper we review the quantitative methods suggested in literature for implementation of the approach. In particular, the use of the Bayesian inference method that allows to take expert judgement and parameter uncertainty into account, modeling dependence and inclusion of insurance are discussed

Pharmacovigilance in pregnancy: adverse drug reactions associated with fetal disorders.

Abstract Objective: To provide the first update on drug safety profiles and adverse drug reactions (ADRs) associated with fetal disorders from the Swiss national ADR database. Methods: We conducted a retrospective study using data from 202 pharmacovigilance reports on drug-associated fetal disorders from the Swiss national ADR database from 1990 to 2009. Evaluated aspects included administrative information on the report, drug exposure, and disorders. Results: The ADR reporting frequency on the topic of fetal disorders has increased during the last 20 years, from only 1 report in 1991 to a maximum of 31 reports in 2008. Nervous system drugs were the most frequently reported drug group (40.2%) above all antidepressants and antiepileptics. The highest level of overall drug intake could be observed for the 1st trimester (85.4%), especially for the first 6 weeks of pregnancy. The most frequently reported types of fetal disorders were malformations (68.8%), especially those of the musculoskeletal and circulatory systems. A positive association was discovered between antiepileptics and malformations in general and in particular of the circulatory system and the eye, ear, face, and neck. Conclusions: The results suggest that the nervous system drug group bears an especially high risk for malformations. The most commonly identified drug exposures can help focus pharmacoepidemiologic efforts in drug-induced birth defects