Description: Update on issues, priorities and key messages from the Joint CAS / CIA / SOA Risk Management Section Council.

Description: This article explores the impact of the tsunamis which hit the shorelines of nine countries in Southeast Asia on December 26, 2004.

Description: Discussion of an inaugural survey of the International Network of Actuarial Risk Managers to identify their view of the top five emerging risks.

Description: This article deals with enterprise risk management and how the techniques contained within the discipline can help prevent unforeseen large mistakes in strategy, product design, and product management

Description: This article describes risk modeling and how to build a risk intelligence system.

Description: In this article, the author discusses earthquake modeling.

Description: Listing and description of key articles in August 2011 issue of Risk Management. Topics include Predictive Modeling, Risk management and Solvency II.

Description: Book review of Extreme Risk Management: Revolutionary Approaches to Evaluating and Measuring Risk by author Christina Ray.

Description: Note from Editor introducing the articles in this issue.

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.