Description: The SOA's Committee on Finance Research is please to make available the results of this research project, jointly sponsored by the SOA and CAS, that explores economic series and provides and Excel based tool for generating future economic scenarios. This is an Excel Spreadsheet for Appendix C showing Simulated Financial Scenario Data of inflation rates and interest rates from this research project. Please see the SOA website for the full report and other related spreadsheets.

Description: This 1997 presentation from the 32nd Actuarial Research Conference develops a stochastic generator for the generation of scenarios of the S&P 500 index, dividend yield, consumer price index, and U.S. Treasury yields. The authors first create a set of 'stylized facts' for these series. They estimate statistical models for these series. These in-sample statistical models are themselves not suitable for generation of scenarios for decision making, but instead are additional 'stylized facts' that assist in model development. The 'best' statistical model according to standard statistical model selection criteria can easily lead to a model that is highly unsuitable for generation of scenarios for decision making. The authors develop a stochastic generator that is suitable for decision making under uncertainty.

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: Appendix E is round 2 on comments on application of judgmental methods from the Delphi study. See the SOA Website Research section for the full Delphi Study of Economic Variables Report along with all the variables.

Description: This is the User's Guide that accompanies the Inflation Generator Excel spreadsheet which is associated with the research report entitled 'The Effect of Deflation or High Inflation on the Insurance Industry.'

Description: The SOA's Committee on Finance Research is please to make available the results of this research project, jointly sponsored by the SOA and CAS, that explores economic series and provides and Excel based tool for generating future economic scenarios. This is an Excel Spreadsheet for Appendix C showing Simulated Financial Scenario Data of inflation rates and interest rates from this research project. Please see the SOA website for the full report and other related spreadsheets.

Description: Appendix D is round 2 - reasons for projections from the Delphi study. See SOA website Research section for the full report of the Delphi Study of Economic Variables Report along with all the appendices.

Description: The primary focus of this 1997 presentation from the 32nd Actuarial Research Conference is the adaptation of the representative scenario method such that the distribution of the primary rates used for product pricing, are consistent, regardless of the initial random number seed. A preliminary question is how many stochastically generated scenarios are required for consistency. This presentation looks at the implications of: the use of antithetic random normal deviates upon the scenario process, ways of modifying the candidate list, and the choice function within the representative scenario process.

Description: On October 30, 2006, the UK government's Stern Review on the Economics of Climate Change made startling claims about the present value today of climate change effects predicted to emerge primarily 150 years or more in the future. The ensuing debate included challenges to and defenses of the particular methodology used and parameter values selected to perform the discounting of future values. Noticing an overlooked faux pas in the Stern Review, this presentation uncovers the likely motivation for choosing the most mystifying of the parameters values, and provides a lesson on the underpinnings of the basic tool of actuarial science.