by Tim J. Boonen, Xia Han
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Suggested foundations for risk measurement and stress and optimisation and numerical methods. Specialist prerequisites vary by paper.
Represent losses as a distribution rather than one forecast.
Distinguish a loss quantile from the average loss in the tail.
Read the linear algebra used to define a numerical problem.
Identify the objective, constraints and conditions for an optimum.
Compare risk estimators and their assumptions.
Check forecasts against realised losses.
Understand identifiability and fitted model parameters.
Connect diversification, common risk factors, investor views, and the properties of a risk measure.