Track 18

Quantitative Prerequisites

Mathematical foundations for pricing models: optimization methods, gradient ascent, convexity, probability distributions, and Bayes' rule.

Topics

Gradient ascent, convexity, KKT conditions

Visualize gradient ascent on pricing objective functions, explore why convexity guarantees a global optimum, and see KKT conditions in action.

Distributions, expectations, Bayes' rule

Explore the probability distributions that underpin pricing models — Normal, Poisson, Binomial — and see how they connect to demand forecasting.