Description: A look at the COVID-19 crisis in 2020, and how it differs from both prior financial crises and pandemics. The COVID-19 pandemic gives actuaries an opportunity to assess different ways risk may interact, and thereby adjust the profession’s work for the future.

Description: While many know that machine learning is a big deal and even have a general idea of what it is, many do not know what machine learning can do for them. As an alternative to citing achievements or explaining algorithms, this article outlines the challenges that occur in statistics and the solutions that machine learning offers. Some of those challenges include correlated predictors, missing data, data interaction, and prediction intervals. Corresponding solutions include regularization technics, missing value imputation with KNN, tree based models, and cluster analysis for backtesting.

Description: The author discusses the review of a recent 2001 Wall Street Journal’s semiannual survey of economists’ forecasts, starting by asking if there is a simple way to summarize the results and to extract a consensus forecast, and from this extraction, determine when an individual forecast is significantly different from that of the consensus.This article is reprinted with permission. It last ran in the Jan. 10, 2001 issue of The La Jolla Economics newsletter.