by Aakhil Anvar, Adarsh Sajeev Kumar, Aryan Singh, Daim Sharif, Eoghan McCarthy, Patrick Haughey, Paul O Reilly, Sathvika Thorali Suresh
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Suggested foundations for volatility models and surfaces and risk measurement and stress. Specialist prerequisites vary by paper.
Follow diffusion-based models and their assumptions.
Separate conditional volatility from observed returns.
Represent losses as a distribution rather than one forecast.
Distinguish a loss quantile from the average loss in the tail.
Study a correlated stochastic-variance model.
Interpret prices across strikes and expiries.
Compare risk estimators and their assumptions.
Start in discrete time, move to Brownian motion, then read the original pricing argument and simulate it.
Connect diversification, common risk factors, investor views, and the properties of a risk measure.