by Eden Gross, Francois Toerien, Ryan Kruger
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Suggested foundations for risk measurement and stress and probability and statistical reasoning. Specialist prerequisites vary by paper.
Read the distributions and expectations used in probabilistic arguments.
Distinguish a loss quantile from the average loss in the tail.
Interpret expectations after information is observed.
Compare risk estimators and their assumptions.
Check forecasts against realised losses.
Assess uncertainty rather than treating an estimate as a fact.
Connect diversification, common risk factors, investor views, and the properties of a risk measure.
Move from conditioning and expected values to timed problems with a defensible solution.