Master of Finance

Suggested Background

Mathematical Background and Programing Skills

  • Linear algebra:

    Basic topics, including: matrix/vector notation, operations on matrices and vectors, determinants, eigenvalues and eigenvectors, quadratic forms, and systems of linear equations.

  • Calculus:

    Multivariable differentiation and integration, series expansions, and function approximation and maximization.

  • Probability:

    Sample spaces and random variables, common distributions and densities, moments of distributions, conditional probability and Bayes’ theorem, law of large numbers, central limit theorem, joint distributions, covariance, correlation, and stochastic independence.

  • Stochastic processes:

    Random walks, Bernoulli trials, Markov processes, basic properties of linear time series models, continuous-time processes, and Ito’s lemma.

  • Statistics/econometrics:

    Parameter estimation, confidence intervals, hypothesis tests, linear regression models, ordinary least squares, and likelihood principle.

  • Computer literacy:

    Students entering the MIT MFin program are expected to possess basic programming skills needed for processing and analyzing data. As part of the degree requirements, all students are required to sit for and pass the Programming Literacy Test. Entering students will take the PLT at the beginning of the summer term using any of the following programming languages: R or Python. Those who do not successfully pass the test will be encouraged to attend coding office hours and required to retake the PLT. Coding office hours will be held throughout the summer term.


To assess the adequacy of your mathematical background, please use the following self-assessment test. If you experience difficulties in any particular area, we strongly recommend that you strengthen your skills through self-study or formal coursework prior to enrolling in the MFin program.

Self-study Resources