Description: Derives appropriate hedge ratios for CPPI strategies, taking into account discrete hedge times and market dislocations (gap risk).

Description: Investment Fallacies: Mathematical modeling of social phenomena

Description: Investment Fallacies: The Myth of Time Diversification

Description: This is a concluding and encompassing part of our research on the project entitled \Weighted Premium Calculation Principles and Risk Capital Allocations, which has been supported by the Actuarial Education and Research Fund AERF and the Society of Actuaries Committee on Knowledge Extension Research CKER. We explore the concept of weighted distributions and their role in various phenomena occurring in insurance and finance. In particular, we relate weighted distributions to actuarial and economic premium calculation principles, and also to the capital asset pricing model CAPM. Imitating the latter, we propose a weighted insurance pricing model WIPM. Although general in formulation, we show that the WIPM can successfully be evaluated in a variety of situations, which we illustrate with a number of examples.

Description: This paper develops credibility using a longitudinal data framework. In a longitudinal data framework, one might encounter data from a cross-section of risk classes towns with a history of insurance claims available for each risk class. For the marginal claims distributions, we use generalized linear models, an extension of linear regression that also encompasses Weibull and Gamma regressions. Copulas are used to model the dependencies over time specifically, this paper is the first to propose using a t-copula in the context of generalized linear models. The t-copula is the copula associated with the multivariate t-distribution like univariate t-distributions, it seems especially suitable for empirical work. Moreover, we show that the t-copula gives rise to easily computable predictive distributions that we use to generate credibility predictors. Like Bayesian methods, our copula credibility prediction methods allow us to provide an entire distribution of predicted claims, not just a point prediction.

Description: Panel discussion focused on the Effective Use of Capital. Topics included: 1. Definition of capital 2. Appropriate level of capital and surplus in a life insurance company 3. Alternatives for deploying capital 4. Returns a life company should demand on invested capital 5. How much a company should charge for lending its capital in reinsurance transactions

Description: Panel discussion focused on the Effective Use of Capital. Topics included: 1. Definition of capital 2. Appropriate level of capital and surplus in a life insurance company 3. Alternatives for deploying capital 4. Returns a life company should demand on invested capital 5. How much a company should charge for lending its capital in reinsurance transactions