Description: This article shows a different form of the Black-Scholes formula for European calls and puts under risk-neutral assumptions, that permits a comfortable verbal interpretation. The derivation of this alternative form appears at the end of the article.

Description: Appendix to the Critical Review of Stochastic Simulation Literature and Applications for Health Actuaries. The Development of a Simulation Model of Primary Prevention Strategies for Coronary Heart Disease

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

Description: These files shows the Schelling Segregation model. It accompanies the report Complexity Science - an introduction and invitation for actuaries, and supports the material in Chapter six: Cellular automata.

Description: Sarah Rockhill, MPH, Geospatial Epidemiologist at CDC will discuss the latest in the Public Health 3.0 model in which leaders serve as Chief Health Strategists, partnering across multiple sectors and leveraging data and resources to address social, environmental, and economic conditions that affect health and health equity.

Description: Discusses the growing and evolving field of pricing and valuing stock option plans, and makes the case that actuaries are the professionals best qualified to serve clients in the field.

Description: How well can we predict ACA HHS Risk Adjustment Data Validation (HRADV) results? Put another way, how susceptible is the current HRADV process to small sample volatility? What potential remedies are there to the current model's shortcomings? Every plan, regardless of how many members they have above the 1000 minimum, count equally if they qualify for an HRADV with how the result is interpreted, and the subsequent HRADV risk transfer ($330M in 2023).

Description: With the unprecedented proliferation in the size and complexity of data over the past decade, actuaries have invested considerable time and energy in the development of new skills and expertise in order to be able to understand and use “big data” to its fullest potential in the development of actuarial work product.

Description: This article discusses the concept of Conservation of Mortality ("Conservation"). Conservation is the modeling principle that ensures consistency between assumptions of the total mortality of a population and mortality among population subsets. This article discusses the use cases for Conservation and the many ways that one could implement it in a model or an experience study. This article also discusses the potential issues that arise when using Conservation, and how one might solve or alleviate these issues.