Description: Session 1F: The Math Behind The Machine - A Review of First Principles

Description: Modeling Approaches and Challenges focuses on approaches to real world simulation and the challenges and considerations in real world simulation. Topics include: A frequency domain approach to build realistic multi-horizon scenarios. (Ortec approach) Cascade models structure linking models for major asset classes and economic variables. (Moody’s approach) Overview of models, calibrations & approaches within the context of different use cases. Deterministic & stochastic approaches. Importance of model re-calibration flexibility. We will also discuss specific insights into considerations and challenges in real world simulation, which include topics like: Setting capital market assumptions and/or calibration targets. Assumptions about correlation and causality. Calibrating the model to capital markets assumptions. Validating the model against capital market assumptions. Role of history, market data and stylized facts. Importance of back testing. Calibrating the model to multiple investment horizons. Inclusion of alterative asset classes such as private equity, infrastructure, and direct real estate. Associated issues of limited data, illiquidity and greater uncertainty about calibration targets.

Description: Emerging Applications of ESG Methods offers ground-up insights on cutting edge applications of economic scenario generation. The course will focus on the incorporation of climate change risk in scenario modeling and investment applications of ESGs. The following topics will be covered: Approaches to climate risk modeling. Climate risk is very different than classical financial economic risk. Radical uncertainty is amenable to scenario analysis and lack of data. Building special deterministic scenarios that go beyond NGFS requirements as well as bespoke scenarios. Holistic Approach to Climate Risk Modeling. Overview of different Climate Risk Modeling Applications. Use of ESG scenarios for Strategic Asset Allocation (SAA). Liquidity risk management.

Description: This report evaluates the long-term mortality consequences of the COVID-19 pandemic from a cohort-based perspective using historical mortality data.

Description: This report analyzes insurance product design, morbidity trends, and pricing models for individuals with pre-existing illnesses in China to improve coverage for substandard health populations.

Description: Credibility is a mechanism for estimating a quantity of interest by combining subject experience and relevant experience to improve the estimate.

Description: This project enhances the current understanding of cyber risks in the smart home ecosystem from the insurance industry's perspective. In particular, the quantitative framework and pricing strategies developed in this project can be immediately adopted/adapted by actuaries to price the cyber risks for smart homes, a fast-growing insurance market.

Description: This is the disclaimer for the Economic Scenario Generators tool available from the SOA / AAA on the SOA Website.

Description: This paper shows that the Esscher transform is also an efficient technique for valuing derivative securities if the logarithms of the prices of the primitive securities are governed by certain stochastic processes with stationary and independent increments. Two applications are presented, the first for valuing a European call option and the second for pricing derivative securities of multiple risky assets.

Description: Most actuaries deal with model development at some point in their career. However, very few of us have proper training in programming, software engineering or software shop operations. Explore topics, techniques, and practices from the FinTech and IT industries that can be applied to building robust, high-quality actuarial models. This session will be of particular interest to actuaries engaged in 'in-house' model development, managers of modeling teams, and actuaries interested in software development.