Search Results (3)

The paper examines the valuation and hedging of life insurance obligations in the presence of mortality risk using the local risk-minimizing hedging approach. Roughly speaking, it is assumed that the lifetime of policyholders in an insurance portfolio is modeled by a point process whose stochastic intensity is controlled by a diffusion process. The stock price process is assumed to be a regime-switching Lévy process with non-zero regime-switching drift, where the parameters are assumed to depend on the economic states. Using the Föllmer–Schweizer decomposition, the main valuation and hedging results for a conditional payment process are determined. Some specific situations have been considered in which the local risk-minimizing strategies for a stream of liability payments or a unit-linked contract are presented. Full article

Estimating outstanding claims reserves in the non-life insurance business is often impaired by outlier-contaminated datasets. Widely used methods to eliminate outliers in non-life development triangles are either limiting the number of outliers by robust statistical methods or by change of development factors. However, the whole estimation process is likewise adversely affected so that: (i) the total sum of all triangle payments is not correct or (ii) the difference between the original triangle and its backward estimation via the bootstrap method is ineligible. In this paper, the properties of the heat equation are examined to obtain an outlier smoothing technique for development triangles. The heat equation in two dimensions is being applied on an outlier contaminated dataset where no individual data are available. As a result, we introduce a new methodology to (i) treat outliers in non-life development triangles, (ii) keep the total sum of all triangle payments, and (iii) provide acceptable differences between the original and the backward estimated triangle. Consequently, the outlying values are eliminated and the resulting development triangle could be used as an input for any claims reserving method without a need for further robustification or change of development factors. Additionally, the research on the application of heat equation in one dimension presented in this paper enables one to employ the bootstrap method using Pearson’s residuals in cases where the method was originally inapplicable due to development factors being lower than one. Full article

Income improvement is the primary expectation when deciding to migrate. However, due to the limited resources and urban facilities, informal sector work leads to an increasing income gap with local workers, migrant workers in big cities are considered the most vulnerable population. When there is no social policy, migrants are even more susceptible to the negative impacts of COVID-19. To identify necessary bases for short-term and long-term intervention to attract workers to return and quickly adapt to the urban life in the economic recovery process, the study surveyed to clarify the assessment of COVID-19 support packages from which the most beneficial are electricity and water exemption and reduction, food support, loan interest reduction, and loan for salary payment. The study also used survey results from two pandemic centers in the southern region to estimate factors and impacts on the workers’ income in terms of integration, the results show that the major significant factors are education, housing, work sector, self-employment, and social insurance. We take notices to enhance workers’ integration to help retain workers by short-term measurements from the support package’s assessments and long-term measurements from the income and integration estimates to attract workers after the pandemic. Full article