by Dong-Hyun Ahn, Jacob Boudoukh, Matthew Richardson, Robert F. Whitelaw
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Suggested foundations for risk measurement and stress and options and derivatives pricing. 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.
Build replication and risk-neutral probabilities in a tractable model.
Distinguish pricing probabilities from physical forecasts.
Compare risk estimators and their assumptions.
Check forecasts against realised losses.
Connect the pricing equation, closed-form value and implied volatility.
Connect diversification, common risk factors, investor views, and the properties of a risk measure.
Start in discrete time, move to Brownian motion, then read the original pricing argument and simulate it.