Description: Many insurers preparing market consistent financial statements encounter the issue of developing volatility assumptions for equity options and guarantees that are longer than any observable market data. This presentation develops a generalization of the classical Black Scholes option pricing model that is consistent with the European CRO Forum's framework for valuing non-hedgeable risk. The presentation argues that, with reasonable parameter choices, the model fits observed volatility surfaces well enough that it can be used to estimate implied volatilities where no market data exists.

Description: This article discusses the pending book entitled 'Dynamic Risk Modeling Handbook.' The proposed scope and outline of the book is reviewed. This is a revision of the 'DFA Handbook' which was published in 1995.

Description: The National Association of Insurance Commissioners (NAIC) is in the middle of of a project to change the real-world economic scenario generator (RW ESG) prescribed for principle-based reserve and capital calculations. The presenters will provide a brief summary of the NAIC's RW ESG project and provide a general overview of RW ESGs. In addition to that, they will explain how RW ESGs impact principle-based reserve and capital levels and consider potential differences between the currently prescribed RW ESG and the proposed RW ESG.

Description: Economic Scenario Generator - Investment Section Web Series Session #1 - Fundamentals & Hot Topics This session will cover the following points: 1. Introduction: ESG Basics, What is Risk Neutral and Real World? 2. Interest Rate Modeling 3. Equity and Private Equity Modeling 4. Example use cases facing investment professionals and actuaries today

Description: This paper analyzes the U. S. Treasury monthly interest rates from 1953 to 1992, and the daily rates from 1981 to 1992 for various forms of chaotic behavior. The primary analysis was in determining the Burst Exponent by the use of Rescaled Range Analysis. This paper also discusses other possible uses of Fractional Brownian Motion in Finance Theory, Macroeconomics, and Actuarial Science. From Actuarial Research Clearing House 1994 VOL. 1.

Description: Asset cash flow modeling and asset assumptions are growing in importance with PBR especially considering the low interest rate environment. The Academy’s Life Practice Council and Life Valuation Committee have formed a Low Interest Rate Asset Adequacy Testing Task Force which has conducted an industry survey to raise awareness and summarize the actuarial best practices for financial reporting actuaries practicing in today’s very low interest rate environment. As the scrutiny on the asset side ratchets up, actuaries must consider how best to develop the asset assumptions as well as model the reinvestment and disinvestment strategies. Coherent assumptions and modeling practices across modeling exercises are expected while respecting the purpose of each calculation.

Description: This is a presentation on computing tight bounds for insurance payments with nonlinear risk. Semi-definite Programming is defined, some examples are presented, and non-linear applications are presented. From Actuarial Research Clearing House, 2012, Vol.1.

Description: The purpose of this paper is to provide a method for calculating special contingency reserves for investment losses. The method is derived by first building a stochastic investment model and then utilizing its probabilistic structure. From Transactions of Society of Actuaries 1980, Vol. 32.

Description: 1999 SOA Annual Meeting, San Francisco. This panel expanded on earlier research to examine the potential costs of long-term guarantees, transfer risk modeling techniques, and the formulation of practical strategies to manage investment accumulation products.

Description: The method described in this paper is to allocate surplus to each category of business and reserves in proportion to its estimated effect on an insurer's surplus variation. Risk load for each category of business is then selected so that the return on allocated surplus for each category is equal to the overall return on surplus. From Actuarial Research Clearing House 1993, VOL. 3.