Description: This paper presents an analysis of mortality in a sample of 441adults aged 55 to 85 at baseline, who were observed for eight years. The study was initiated for the purpose of analyzing age-related changes in a variety of physical variables and their impact on functional independence. The modeling approach is discussed and the factors which were most significantly related to mortality.

Description: The purpose of this paper is to explore a methodology for choosing among techniques for managing contribution volatility in defined- benefit pension plans. A frequently used – and as often criticized – method for managing contribution volatility is to base actuarial cost on smoothed assets. Our goal in this paper is to develop a methodology for measuring and evaluating the quantitative impact of competing asset smoothing policies. We proceed by investigating a series of basic pension metrics, evaluating the characteristics of each using a simulated pension plan. We then use normalized and weighted combinations of these metrics to determine an optimal smoothing policy.

Description: This paper introduces and illustrates a new version of the Monte Carlo method that has attractive properties for the numerical valuation of derivatives. Quasi-Monte Carlo methods use deterministic sequences that are quasi-random sequences that result in better convergence and deterministic error bounds.

Description: The purpose of this paper is to explore pension plan metrics— – measuring the behavior of a defined- benefit pension plan in an uncertain environment. Our goal is to measure and evaluate the quantitative impact of competing policy choices. We proceed by investigating some basic pension metrics, evaluating the characteristics of each using a simulated pension plan. We find that some typical metrics— – such as the mean and standard deviation— – are useful only in certain circumstances and that other less traditional measurements are sometimes better suited to evaluating policy choices.

Description: The purpose of this paper is to explore pension plan dynamics— – the behavior of a defined- benefit pension plan over time in an uncertain environment. We proceed by simulating the behavior of a model plan in a stochastically varying economic environment. While both the model and its environment are simplified, the model displays interesting behavior suggesting policy considerations that should be included in the design and funding of these plans.

Description: Empirical evidence of reported losses suggests that insurance firms are interconnected in a nontrivial way, making them prone to systemic risk. Systemic risk can be viewed as the result of a cascading process, as it unravels throughout a network structure. In response, this work presents a simple analytical model that can simulate this process. The model is subsequently tested upon an empirical dataset via the means of numerical simulations. This work makes three main contributions. First, it provides a novel methodology for quantitatively and objectively assessing the systemic role of individual firms within the insurance domain. Second, it exemplifies the inability of traditional, firm-based information in serving as proxies for mapping these systemic effects. Third, it provides a practical example where network-based information (e.g., Criticality IDX, Sensitivity IDX) can outperform firm-based information (e.g., admissible assets, excess c apital) resulting in increased efficiency in the decision-making process. These findings strengthen the need to account for the interconnected nature of the domain while showcasing some of the potential benefits that can be harvested by doing so.

Description: Empirical evidence of reported losses suggests that insurance firms are interconnected in a nontrivial way, making them prone to systemic risk. Systemic risk can be viewed as the result of a cascading process, as it unravels throughout a network structure. In response, this work presents a simple analytical model that can simulate this process. The model is subsequently tested upon an empirical dataset via the means of numerical simulations. This work makes three main contributions. First, it provides a novel methodology for quantitatively and objectively assessing the systemic role of individual firms within the insurance domain. Second, it exemplifies the inability of traditional, firm-based information in serving as proxies for mapping these systemic effects. Third, it provides a practical example where network-based information (e.g., Criticality IDX, Sensitivity IDX) can outperform firm-based information (e.g., admissible assets, excess c apital) resulting in increased efficiency in the decision-making process. These findings strengthen the need to account for the interconnected nature of the domain while showcasing some of the potential benefits that can be harvested by doing so.