Multiplicative local linear hazard estimation and best one-sided cross-validation

This paper develops detailed mathematical statistical theory of a new class of cross-validation techniques of local linear kernel hazards and their multiplicative bias corrections. The new class of cross-validation combines principles of local information and recent advances in indirect cross-validation. A few applications of cross-validating multiplicative kernel hazard estimation do exist in the literature. However, detailed mathematical statistical theory and small sample performance are introduced via this paper and further upgraded to our new class of best one-sided cross-validation. Best one-sided cross-validation turns out to have excellent performance in its practical illustrations, in its small sample performance and in its mathematical statistical theoretical performance

Statistical modelling and forecasting of outstanding liabilities in non-life insurance

Non-life insurance companies need to build reserves to meet their claims liability cash flows. They often work with aggregated data. Recently it has been suggested that better statistical properties can be obtained when more aggregated data is available for the statistical analysis than just the classical aggregated payments. When also the aggregated number of claims is available one can define a full statistical model of the nature of the number of claims, their delay until payment and the nature of these payments. In this paper we provide a new development in this direction by entering yet another set of aggregated data, namely the number of payments and when they occurred. A new element of our statistical analysis is that we are able to incorporate inflationary trends of payments in a direct and explicit way. Our new method is illustrated on a real life data set and the conclusion are informative and useful

In-Sample Forecasting Applied to Reserving and Mesothelioma Mortality

This paper shows that recent published mortality projections with unobserved exposure can be understood as structured density estimation. The structured density is only observed on a sub-sample corresponding to historical calendar time. The mortality forecast is obtained by extrapolating the structured density to future calendar times using that the components of the density are identified within sample. The new method is illustrated on the important practical problem of forecasting mesothelioma for the UK population. Full asymptotic theory is provided. The theory is given in such generality that it also introduces mathematical statistical theory for the recent continuous chain ladder model. This allows a modern approach to classical reserving techniques used every day in any non-life insurance company around the globe. Applications to mortality data and non-life insurance data are provided along with relevant small sample simulation studies

A simple benchmark for mesothelioma projection for Great Britain

Background: It is of considerable interest to forecast the future burden of mesothelioma mortality. Data on deaths are available, whereas no measure of asbestos exposure is available. Methods: We compare two Poisson models: a response-only model with an age-cohort specification and a multinomial model with epidemiologically motivated frequencies. Results: The response-only model has 5% higher peak mortality than the dose-response model. The former performs slightly better in out-of-sample comparison. Conclusion: Mortality is predicted to peak at about 2100 deaths around 2017 among males in cohorts until 1966 and below 90 years of age. The response-only model is a simple benchmark that forecasts just as well as more complicated models

Double Chain Ladder

By adding the information of reported count data to a classical triangle of reserving data, we derive a suprisingly simple method for forecasting IBNR and RBNS claims. A simple relationship between development factors allows to involve and then estimate the reporting and payment delay. Bootstrap methods provide prediction errors and make possible the inference about IBNR and RBNS claims, separately

Continuous Chain Ladder: Reformulating and generalizing a classical insurance problem

The single most important number in the accounts of a non-life insurance company is likely to be the estimate of the outlying liabilities. Since non-life insurance is a major part of our financial industry (amounting to up to 5% of BNP in western countries), it is perhaps surprising that mathematical statisticians and experts of operational research (the natural experts of the underlying problem) have left the intellectual work on estimating this number to actuaries. This paper establishes this important problem in a vocabulary accessible to experts of operations research and mathematical statistics and it can be seen as an open invitation to these two important groups of scholars to join this research. The paper introduces a number of new methodologies and approaches to estimating outstanding liabilities in non-life insurance. In particular it reformulates the classical actuarial technique as a histogram type of approach and improves this classical technique by replacing this histogram by a kernel smoother

Molecular analysis of urban rabies case from vampire bat in Corrientes, Argentina

En abril de 2006 se detectó virus de la rabia (RABV) en un gato doméstico de la ciudad de Corrientes, Argentina. La caracterización molecular identificó al murciélago Desmodus rotundus como la fuente viral. El análisis genético de 22 cepas de RABV aisladas de D. rotundus obtenidos entre 1998–2006 en Argentina, reveló la cocirculación de dos linajes genéticos en la Provincia de Corrientes. La alteración por parte del hombre, del ecosistema del murciélago en la región, podría explicar los cambios en su comportamiento y en la circulación del virus de la rabia

Cash flow simulation for a model of outstanding liabilities based on claim amounts and claim numbers

In this paper we develop a full stochastic cash flow model of outstanding liabilities for the model developed in Verrall, Nielsen and Jessen (2010). This model is based on the simple triangular data available in most non-life insurance companies. By using more data, it is expected that the method will have less volatility than the celebrated chain ladder method. Eventually, our method will lead to lower solvency requirements for those insurance companies that decide to collect counts data and replace their conventional chain ladder method

Environment-driven reactivity of H2 on PdRu surface alloys

The dissociative adsorption of molecular hydrogen on PdxRu1−x/Ru(0001) (0 ≤ x ≤ 1) has been investigated by means of He atom scattering, Density Functional Theory and quasi-classical trajectory calculations. Regardless of their surroundings, Pd atoms in the alloy are always less reactive than Ru ones. However, the reactivity of Ru atoms is enhanced by the presence of nearest neighbor Pd atoms. This environment-dependent reactivity of the Ru atoms in the alloy provides a sound explanation for the striking step-like dependence of the initial reactive sticking probability as a function of the Pd concentration observed in experiments. Moreover, we show that these environment-dependent effects on the reactivity of H2 on single atoms allow one to get around the usual constraint imposed by the Brønsted–Evans–Polanyi relationship between the reaction barrier and chemisorption energy.Fil: Ramos Acevedo, Maximiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Instituto de Física de Rosario (i); Argentina. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura; ArgentinaFil: Minniti, M.. Universidad Autónoma de Madrid; EspañaFil: Díaz, C.. Universidad Autónoma de Madrid; EspañaFil: Farias, D.. Universidad Autónoma de Madrid; EspañaFil: Miranda, R.. Universidad Autónoma de Madrid; España. Instituto Madrileño de Estudios Avanzados en Nanociencia; EspañaFil: Martín, F.. Universidad Autónoma de Madrid; España. Instituto Madrileño de Estudios Avanzados en Nanociencia; EspañaFil: Martinez, Alejandra Elisa. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Instituto de Física de Rosario (i); Argentina. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura; ArgentinaFil: Busnengo, Heriberto Fabio. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Instituto de Física de Rosario (i); Argentin