This is the second in a series of three short courses on financial mathematics that take participants from pre-calculus to stochastic calculus. Like all three courses of the series, Math 2 combines self-study with three days of lectures.

Self study focuses on reviewing and mastering concepts learned in Math 1—differentiation, integration and practical applications. These concepts are fundamental to finance, but they are not enough on their own. It is only when we combine calculus with probability theory that we can address serious financial applications. The purpose of Math 2 is to get students to this next level.

Lectures delve into linear algebra and probability theory. Linear algebra allows us to extend calculus to multiple dimensions, which is essential for

modeling asset prices over multiple time steps or

modeling risk for multi-asset portfolios.

Probability is even more important, opening the door to statistics, time series analysis and stochastic calculus, which are covered in Math 3. Numerous financial applications depend on probability. Math 2 explores a number of these, including

different models for returns,

portfolio theory,

Siegel's paradox,

the "Greeks,"

value-at-risk.

Value-at-risk is a wonderful application for illustrating applications of multi-dimensional calculus and probability, so it arises several times in the lectures. It is a unifying theme for the entire course.

Prerequisites for Math 2 are either completion of Math 1 or knowledge of the math covered in that course.

This is an extremely popular course. Most attendees have already taken Math 1. Many go on to take Math 3.