by Ali Jadbabaie, Arnab Sarker, Manuel Quintero, Sean R. Sinclair, Tamara Broderick, Vanessa Lin
Continue on SelfMadeQuant
Suggested foundations for risk measurement and stress and stochastic processes and 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.
Understand what it means to condition on current information.
Follow Brownian dynamics and the second-order term in Itô calculus.
Compare risk estimators and their assumptions.
Check forecasts against realised losses.
Connect stochastic dynamics to no-arbitrage prices.
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.