Description: This is the second part of a 2 part series on Real options analysis (ROA). This article looks into the limitations of using financial option theory when doing real options analysis with projects that are long-dated and uncertain, such as: 1. First-degree homogeneity, 2. Uncertainty must derive from Brownian motion, and 3. Risk neutrality.

Description: This article provides an overview of behavioral economic theory as it relates to health and welfare insurance plans and provides summaries of two sample applications of the theories: enrollment in health insurance exchanges created by the Patient Protection and Affordable Care Act, and product design considerations in light of vast health illiteracy.

Description: A three-minute neuroscience-based image exercise is able to accurately unlock the emotional state of individual employees, permitting prediction of a host of specific needs. Actuaries can use this quantitative information at scale to target resources, benefits, and supports to increase the objective wellness and subjective well-being of workforces.

Description: This essay explores the role that the emerging defined contribution retirement system may be playing in the growth of wealth inequality in the United States. The current system leaves many Americans with little or no retirement savings. Those with higher accumulation levels appear to invest proportionally more in equities, which may have an exponential effect of balances over long time periods. The author hypothesizes that willingness to take investment risk involves the relationship between the amount an investor has accumulated and what she/he needs in order to cover basic costs of living. This is one reason that investors with greater accumulation levels may be able to earn higher rates of return. The essay concludes by suggesting that the U.S. defined contribution system should include all workers and provide additional fiduciary guidance. Examples reforms, both in the U.S. and other countries, are provided.

Description: Traditional predictive tools are not built to deal with the variability the world currently faces. The COVID-19 pandemic amounts to a prolonged black swan event, for which one must look past conventional assessments to arrive at any level of confident predictions. Behavioral analysis factors for biases and heuristics designed specifically for uncertain evolutionary contexts, and which are the primary drivers of market participants’ decisions at present. Through understanding the most likely behaviors of individuals, it becomes possible to arrive at an aggregate understanding of market outcomes.