Description: The purpose of this paper is to survey some new results concerning the term structure of interest rates and discuss actuarial applications. The term structure of interest rates exhibits the relationship among the yields on default free debt instruments of different maturities. Although there is a considerable volume of literature dealing with the determinants of the term structure the analysis has until recently been presented for the most part in a deterministic i.e. non- stochastic framework. This constrasts with the treatment of capital assets where equilibrium prices have been obtained under the assumption that returns on these assets are random variables.

Description: In order for actuaries to play a valuable role in the realm of enterprise risk management ERM, they must provide value-added advice and quantitative analyses. In this paper, the authors use stochastic simulation technology to present a risk metric for defined benefit pension plans that provides improved measures of the plan’s solvency and provides a tool for pension plan managers to determine the value of risk mitigation activities.

Description: Are Your Scenarios on Target?From Risks and Rewards Newsletter, August 2005, Issue No. 47. Actuaries are faced with the dilemma of how to incorporate advances in insurance products and modeling technology into their work. Increasingly, this means looking at a large number of potential outcomes using stochastic simulations.

Description: This article presents a case study that examines the implication of using real-world interest rate scenario generators with a block of fixed deferred annuities. We contrast cash flow testing results based on New York 7 deterministic scenarios to stochastic scenarios generated with the Academy Interest Rate Generator , as well as an alternative economic scenario generator designed explicitly to capture the risk of a persistently low interest rate environment and the transition to a rising interest rate environment.

Description: Principle-based reserving requires modeling assets and liabilities across a range of scenarios to assess the sufficiency of assets when determining reserves, a major shift from the current formulaic framework. These changes will require valuation actuaries to evolve their skill set by heightening their focus on creative analysis, gaining deeper understanding of complex projections and clearly communicating drivers of reserve movements to stakeholders in order to influence strategic decision-making. The panelists will discuss the way that they see the role of the valuation actuary changing in response to the change in focus in reserving requirements. They will also discuss successful characteristics along with best practices for understanding and explaining results in the new paradigm. The audience will be given the opportunity to interact through polling and facilitated discussion of their stories, experiences and observations.

Description: Annual reports of the U.S. Social Security Trustees present 75-year financial projections of the system under three different deterministic sets of economic and demographic assumptions or scenarios. The extent of the divergence between these scenarios provides useful information concerning the range of possible outcomes, but, in the absence of stochastic model projections, no probability measure can be assigned to the three scenarios, apart from being described as intermediate, low-cost and high-cost. Demographic research and stochastic model forecasts of U.S. population suggest plausible hypotheses for analysis of the divergence characteristics of the actuarial solvency ratios implied by the three deterministic scenarios. Available data from the 2002 Trustees’ report are presented and various statistical measures are developed to aid in the assessment of plausible associated probability measures for the scenario projections.

Description: This paper introduces the symbolic valuation, a stochastic valuation which allows flexible interest rate and cash flow assumptions, and provides an illustration which values a simple SPDA product. From Actuarial Research Clearing House 1992, Vol. 1.

Description: This research report on the effect of deflation or high inflation has six sections: 1. The first section provides background on inflation, describes some problems in measuring inflation, and explains some of its effects on an economy. 2. The second section reviews historical inflation rates. 3. The third section examines the effect of inflation or deflation on the property-liability and life insurance industries. 4. The fourth section proposes risk mitigation strategies for insurers to cope with either deflation or high inflation rates. 5. The fifth section describes a publicly available model that can be used to develop inflation/deflation projections under a regime switching format that can readily be adjusted to reflect current financial uncertainty. 6. The sixth section provides conclusions.

Description: This paper introduces a rich stochastic modeling framework for understanding risks in multiple-decrement contracts. The example in the paper is a 20-year Term insurance contract. Not only are mortality and lapsation considered stochastic, but the parameters governing them are. For example, mortality risk is composed of four risk elements, including error generated in the underwriting process, volatility around the best estimate, catastrophic events that impact mortality, and the trend in mortality improvement or deterioration. When stochastically modeled, the relative contribution and risk profile of each risk element can be evaluated. Generating stochastic mortality results provides a distribution of results that an organization faces and the severity and incidence of the tail events.

Description: From a session at the Spring regional meeting of the Society of Actuaries held in Atlanta, Georgia, May 24-25, 1999 Equity-indexed products require an asset strategy that matches the equity options embedded in the liability. The panel discusses the following: A. Two asset strategies 1. Purchasing equity options that match the liability options: Is this a perfect match or are there still unhedged risks? 2. Dynamic hedging using the mathematics of “the Greeks”: Is it self-insuring? B. Accounting issues with these strategies