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Learning Pathway

Quant Math

Master the mathematical machinery of modern quantitative finance.

About this pathway

Quant Math covers the rigorous mathematical foundations required at top prop trading firms and quant hedge funds. From probability theory to stochastic calculus, this pathway gives you the technical depth that separates junior candidates from senior offers.

Who it's for

Candidates targeting quant researcher, quant analyst, or quant developer roles. Built from first principles — strong math background helpful but not required.

Skills covered

Probability theory & measure theory basics
Statistics & statistical inference
Stochastic processes & Brownian motion
Itô's lemma & stochastic differential equations
Partial differential equations in finance
Numerical methods & Monte Carlo simulation

Course modules

01
Probability & Random Variables
8 lessons
02
Statistics & Inference
6 lessons
03
Stochastic Processes
7 lessons
04
Itô Calculus & SDEs
6 lessons
05
PDEs & Numerical Methods
5 lessons

Example problems

A taste of what you'll work through.

1

Let X ~ Poisson(λ). Derive the variance of X from first principles using the MGF.

2

Write the SDE for geometric Brownian motion and derive the price process S(t) using Itô's lemma.

3

Use Monte Carlo simulation to price a European call option. How many paths for 2 decimal places of accuracy?

Expected outcome

You will be able to derive key results from scratch, solve novel mathematical problems under pressure, and demonstrate the mathematical maturity expected at top quant firms.

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