Description: Eric Friedman’s comments on ‘The Case for Stochastic Present Values,” by Dimitry Mindlin

Description: This paper develops an option pricing model that takes cost of capital concepts as its foundation rather than dynamic replication. The resulting model, called the 'C' measure in this paper, is related to the family of Affine Jump Diffusion models that are well known in the finance literature, so it is fairly easy to understand and implement. We argue that this is a reasonable model to use for estimating equity implied volatilities that are beyond the five- to 10-year horizon that can typically be observed in today‘s capital markets. The paper concludes with a short discussion of how to grade from observable market data to the 'C' measure.

Description: We ask whether we can find support for the previously reported upper limit of the force of mortality of 0.7, i.e. about the probability of tossing a fair coin.

Description: This is an abstract for the paper, Analysis of Costs for a Chronic Disease with Acute High Cost Episodes by Marjorie Rosenberg and Philip Farrell.

Description: This paper demonstrates the calculation of the moments of the distribution of aggregate life insurance claims from seriatim inforce data, assuming that each record represents an independent Bernoulli trial with its own known probability of a claim, q. Continuous distributions matching the first three or four moments are identified.

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: Presentation from the 41st Actuarial Research Conference held on August 10-12, 2006 in Montreal, Canada. Fuzzy set theory is incorporated into times series analysis, giving fuzzy parameter estimates of models such as ARMA and GARCH. Examples are given, including returns on a stock and option valuation.

Description: This is the abstract of a paper that complements the existing research on optimal reinsurance by proposing another model for the determination of the optimal reinsurance design.

Description: When fitting a model to any data, there is some uncertainty about which model is best. Green [1995] quantifies this uncertainty through the Reversible Jump Markov Chain Monte Carlo [RJMCMC] method. When using the RJMCMC method in a regime-switching situation, the chain determines the optimal number of regimes by jumping between various possibilities. This method gives each model its posterior probability of being the best. After an overview of the methodology, the authors apply it to various datasets and discuss the applications in modern actuarial science.

Description: This is a stochastic model used to find the distribution of the discounted value of all future cash-flows.