Description: This session from the 1993 Valuation Actuary Symposium looks at asset models and economic scenario generation.

Description: From a teaching session at the 2001 Valuation Actuary Symposium, held in Lake Buena Vista, Florida, November 29-30, 2001 Panelists analyze the modeling considerations in projecting asset cash flows and asset valuations.

Description: From a session at the 2000 Valuation Actuary Symposium held in Washington DC, September 14-15, 2000 Technical discussion of asset modeling concepts and techniques

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: From a session at the annual meeting of the Society of Actuaries held in Chicago, Illinois, October 15-18, 2000 Discussion of purposes and approaches for creating interest-rate scenarios.

Description: As the Valuation Manual continues to evolve and PBR standards for additional products are drafted and incorporated, it will become increasingly important for companies to understand where the requirements are consistent across products, as well as how they differ. This session will scan the life (VM-20) and annuity (VM-21, VM-22) PBR standards across the Valuation Manual to compare and contrast key requirements. Attendees will understand where common methods and techniques can be used across products and platforms. Attendees will also be better positioned to consider assumption and margin setting, asset and derivative modeling, and model efficiency techniques for all types of principles-based valuations. Additionally, this session will profile specific challenges that can arise when actuaries use models to project PBR reserves at future dates for internal planning, pricing, and projections across life and annuity businesses.

Description: Presented at September 1995 Valuation Actuary Symposium. This session talks about the tools and methods for asset modeling, particularly mortgages and asset-backed securities.

Description: We consider Libor market model and calibration process. We estimate some interest rate derivatives such as Caps and Swaptions. We use Monte Carlo methods with appropriate dynamics under spot measure and forward measure. Imposing martingale discretization property, the same quantities are estimated again to see a contrast or discrepancy in light of confidence interval. Based on algorithms discussed in the paper, “Arbitrage-free discretizations of lognormal forward Libor and swap rate models” by Glasserman, P and Zhao, X 2000, the algorithms are implemented in excel VBA. Starting with current market data such as FRAs and Bond Prices, we describe steps involved to estimate the price of interest rate derivatives such as Caps and Swaptions, which would be beneficial to the practitioners in the industry.

Description: 1996 Valuation Actuary Symposium. This session about asset modeling discussed securities with options and derivatives, corporate government debt, mortgage-backed securities, collateralized mortgage obligations, real estate equities, and investment and disinvestment strategies.

Description: 2002 Valuation Actuary Symposium, Lake Buena Vista, FL. In this teaching session the instructor explained how to scrutinize model results and use models to make strategic decisions. Specific topics included validation of asset models, modeling considerations for derivatives and assets with embedded options, using models to assist with portfolio management, and using models to improve portfolio yields and realized product spreads.