Description: After more than a decade of a prolonged low interest rate environment, long-term Treasury rates have started to increase with higher volatility. While it is generally agreed that a modest increase in interest rates and inflation is beneficial to the life insurance industry, interest rate risk remains a significant challenge for life insurance industry to manage its long duration liabilities, especially under volatile interest rate environments. Learn how to proactively manage interest rate risk and improve capital efficiency through the cash flow based strategic asset allocation (SAA) framework. Discover practical examples of how to combine asset allocation with derivatives to manage tail risk and liability convexity.

Description: This is the first of a two-part article introducing and elaborating an “Adaptor” strategy for ERM. Such a strategy is intended to fulfil two purposes: first, switching among four styles of risk-coping strategies in order to track qualitative changes in a business’s risk environment; and, second, to support the business in navigating with resilience through all the seasons of a business-economic cycle, i.e., of boom, bust, moderate, uncertain. This latter requires careful study of the nature of resilience, the familiar idea of bounce back, and the less familiar idea of bounce forward. Part I of our article is underpinned therefore by a supplementary document (available from https://riskviews.wordpress.com/adaptor-exceptionalism/), which addresses the issue of structural change in a business or economy. It draws heavily on ideas taken from the discipline of control engineering, as well as some from ecology, social anthropology, and economics. The entire two-part article is thus an exercise in cross-disciplinary Systems Thinking.

Description: Analyze the market volatility behavior in context with historical extreme events during this webcast. There will be a focus on understanding volatility clustering and relationships, both contemporary and temporal, in addition to key economic and capital market variables. You'll also learn from a comprehensive attribution analysis, which uses economic data, asset data, retail investor data and event data as explanatory variables. Dive into investment-related Reddit comments used to capture features of retail investors and tree-based models, including Random Forests and Gradient Boosting Machines to justify changes in volatility modeling. Expect this webcast to end with an example of liability-driven investment optimization that illustrates the potential impact of increased volatility assumption, how to adopt stochastic volatility models, how to reflect volatility clustering and return jumps.

Description: Come discuss modeling costs and its governance, as well as introduce some platforms for more granular asset modeling.

Description: Gather with members and non-members in the China actuarial community to discuss recent topics and related issues in areas such as macroeconomic sharing, pension, investment, product strategy, and more.

Description: This is the second of a two-part article introducing and elaborating an “Adaptor” strategy for ERM. Such a strategy is intended to fulfil two purposes: first, switching among four styles of risk-coping strategies in order to track qualitative changes in a business’s risk environment; and, second, to support the business in navigating with resilience through all the seasons of a business-economic cycle, i.e., of boom, bust, moderate, uncertain. This latter requires careful study of the nature of resilience, the familiar idea of bounce back, and the less familiar idea of bounce forward. Part I of our article is underpinned therefore by a supplementary document (available from https://riskviews.wordpress.com/adaptor-exceptionalism/), which addresses the issue of structural change in a business or economy. It draws heavily on ideas taken from the discipline of control engineering, as well as some from ecology, social anthropology, and economics. The entire two-part article is thus an exercise in cross-disciplinary Systems Thinking.

Description: "Can you answer the question 'what are the chances we will lose more than $1 million next year?' without saying 'it depends'? If you miss a projection, can you quantify the chances that the miss was due to random variation vs. an incorrect projection? ten in as presenters demonstrate how to answer these questions and others using total risk analysis. Total risk analysis includes quantifying both the random variation risk and the projection risk associated with actuarial functions like pricing and reserving. After attending this session, you will be able to describe total risk analysis, apply total risk analysis to many actuarial functions."

Description: Economic Scenario Generator - Investment Section Web Series - Risk Neutral

Description: 2021 Life Meeting - Session 6D: The Importance of Joint Credit-Market Risk Modeling 8.31.21 Recording

Description: Come discuss modeling costs and its governance, as well as introduce some platforms for more granular asset modeling.