Math for quant
3 readings
Connect probability, linear algebra and stochastic calculus to the quantities a quant model must estimate or price.
- Who this is for
- Readers with school algebra who want a practical route into the mathematical core.
- What you will work towards
- Explain an expected payoff, solve a small least-squares problem, and identify the assumptions behind a stochastic pricing model.
Before you start
Use these SMQ lessons to check the ideas the readings assume. Lesson pages show the outline and how to access the full lesson.
- Conditional Expectation
Read conditional reasoning and expected payoffs.
- Vectors, Matrices and Linear Systems
Work with vectors and matrix operations before fitting a model.
Read in this order
Introduction to Probability and Statistics
Learn probability as a language for uncertain outcomes.
Introduction to Applied Linear Algebra: Vectors, Matrices, and Least Squares
Connect matrix operations to estimation and portfolio risk.
Mathematics for Machine Learning
Connect calculus and optimisation to fitted models.
Continue your study on SMQ
- Stochastic Processes, Brownian Motion and Itô's Lemma
Connect probability and calculus to a financial model.
- Constrained and Convex Optimisation
Translate a financial objective and constraints into an optimisation problem.
Follow the connected lessons, worked examples, and exercises in the app. Full lesson access depends on the topic and your membership.
Continue with the mathematical core