Description: This presentation, session number 83CS at the 1999 Spring Meeting of the Society of Actuaries, held June 16-18 in Seattle, is a preview of an actual Course 7. The presenters, two experienced researchers, lead the discussion and a demonstration of a case study from the modeling Course 7. Discussion from participants is included. From the Record of the Society of Actuaries, Vol. 25, No. 2.

Description: Presented at May 2005 Spring Meeting. Panelists discuss strategies for increased modeling speed as risk management, valuation and product development activities have been requiring increasingly complex financial models.

Description: 1988 Valuation Actuary Symposium, In this session, the presenter suggests the value of the Reg 126 testing is a function of the attitude of the company toward the process. He also explored the differences in results by product of using deterministic versus stochastic scenarios.

Description: This document provides answers to the exercises in the report titled Complexity Science – an introduction and invitation for actuaries:.

Description: Summary of the SOA's research report Modern Deterministic Scenarios for Interest Rates, which developed interest rate scenarios for use in cash flow testing.

Description: Identifying and submitting all appropriate ICD-9 diagnosis codes to CMS will result in a higher risk score for the member and increased payments to Medicare Advantage plans. Milliman's HCC prevalence study illustrates the significant variations in HCC prevalence rates by age/gender, geography, and population type and will assist plans in benchmarking the effectiveness of their own diagnosis code capture efforts.

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: 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.