by Jirô Akahori, Maho Nishida, Shuji Tamada, Yuuki Ida
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Suggested foundations for stochastic processes and pricing and risk measurement and stress. Specialist prerequisites vary by paper.
Understand what it means to condition on current information.
Follow Brownian dynamics and the second-order term in Itô calculus.
Represent losses as a distribution rather than one forecast.
Distinguish a loss quantile from the average loss in the tail.
Connect stochastic dynamics to no-arbitrage prices.
Translate continuous dynamics into a numerical experiment.
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.