**Learning Objectives:**

The candidate will understand the concepts of risk modeling and be able to evaluate and understand the importance of risk models.

**Learning Outcomes:**

The candidate will be able to:

a) Demonstrate how each of the financial and non-financial risks faced by an entity can be amenable to quantitative analysis including an explanation of the advantages and disadvantages of various techniques such as Value at Risk (VaR), stochastic analysis, and scenario analysis.

b) Evaluate how risks are correlated, and give examples of risks that are positively correlated and risks that are negatively correlated.

c) Analyze and evaluate risk aggregation techniques, including use of correlation, integrated risk distributions and copulas.

d) Apply and analyze scenario and stress testing in the risk measurement process.

e) Evaluate the theory and applications of extreme value theory in the measuring and modeling of risk.

f) Analyze the importance of tails of distributions, tail correlations, and low frequency / high severity events.

g) Analyze and evaluate model and parameter risk.

h) Construct approaches to modeling various risks and evaluate how an entity makes decisions about techniques to model, measure and aggregate risks including but not limited to stochastic processes.

**Updated for Spring 2018 Sitting*