Description: The 2024 Dangerous Risks survey shows respondents react to recent increases in "old favorite" risks as technology evolves and the environment moves away from the pandemic.

Description: Joint Risk Management Section chairperson's corner, June 2023

Description: In this article, the section chairperson talks about the importance of actively promoting actuarial skills and value to lead the evolution of risk management.

Description: In this article, the author discusses the International interest in working toward a global ERM credential similar to the CERA designation from the SOA.

Description: In this article, the Editor talks about the changes to the newsletter and discusses prizes available for articles.

Description: This article departs from the usual GMWB pricing approach by assuming that the policyholder is always smart enough to act in his/her own best interest.

Description: In this article, the author examines Nassim Taleb’s work and writings and discusses its relevance to the future of the actuarial profession.

Description: This article provides some insights in how to bring risk management into product development for VA guarantees.

Description: Feature article discussing the four main perspectives of ERM.

Description: Economic risk analysis has two dimensions: time and frequency. Asset return varies by time because of economic cycles and economic structural changes. Risk is higher during economic recessions and smaller during economic expansions. In addition, different economic structures may exist at different time scales. Risk measures calculated based on daily, weekly, monthly and yearly historical data can be very different. The appropriate frequency depends on the time horizon of the analysis. Therefore, it is important to measure economic risk at both the time level and the frequency level. However, time series analysis and statistical analysis that have been widely adopted in economic risk analysis focus on only one of the two dimensions. In this paper, wavelet models are used to enhance both time‐invariant analysis and time‐variant analysis. Wavelet models can systematically analyze risk by time and frequency and provide richer information than time series models. Using wavelet models, risk measurement can easily be adjusted based on time horizon in a consistent way. Equity VaR estimation is selected to demonstrate the application of wavelet analysis in risk management.