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mimerimi
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This is from there website:

Listed below is an outline of the mathematical background that is desirable to have in order to be successful in the most challenging of courses in the program.

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: Basic programming experience and readiness to learn new tools and features; for example, familiarity with programming in MATLAB, Python, Java, or C++. Basic experience with Microsoft Office business tools, especially use of Excel for data analysis and presentation.


They also have a self-assessment section if you are still having doubts. IMO, if you have the stats to apply and have a decent amount of math in your background you can augment it with some community college classes. I've known a number of successful applicants who have done this. Additionally, while you want to go into the program with a background like this, don't assume the program is effectively a MFE type degree. You can customize your classes in whatever fashion you please. The program can be as quant or as non-quant as you like. For those so inclined, the school now offers a financial engineering concentration. Food for thought if this is what you really enjoy.
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AmoyV
mimerimi
I'm interested in applying to MIT's MFin program next year. My concern is that my mathematical background is not that strong.

I'm an Economics undergraduate and have only completed what I consider the most basic of Calculus (Differentiation, Integration but not that much Series - No differential equations at all), Linear Algebra (Basic Matrix Operations, Gauss Elimination etc. but not Vector Spaces, Eigenvalues etc.), Statistics/Probability/Econometrics (Descriptive Statistics, Inferential Statistics, Linear Regressions & Estimations etc. but nothing Stochastic, or calculus-based).

The truth is that I consider myself inclined towards mathematics and capable of learning new concepts. My question would be whether I will adequately learn the mathematical concepts that are needed, during the math preparation modules of the program, or I will be more or less expected to already know such concepts beforehand.

Any input from former/current students of the program would be very appreciated.

Hey sent you a PM.
Hi, could you please send that also to me? :)
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MSFHQ
This is from there website:

Listed below is an outline of the mathematical background that is desirable to have in order to be successful in the most challenging of courses in the program.

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: Basic programming experience and readiness to learn new tools and features; for example, familiarity with programming in MATLAB, Python, Java, or C++. Basic experience with Microsoft Office business tools, especially use of Excel for data analysis and presentation.


They also have a self-assessment section if you are still having doubts. IMO, if you have the stats to apply and have a decent amount of math in your background you can augment it with some community college classes. I've known a number of successful applicants who have done this. Additionally, while you want to go into the program with a background like this, don't assume the program is effectively a MFE type degree. You can customize your classes in whatever fashion you please. The program can be as quant or as non-quant as you like. For those so inclined, the school now offers a financial engineering concentration. Food for thought if this is what you really enjoy.

Don't the program expect any knowledge in corp/quant finance?
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Tourist1703
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This is from there website:

Listed below is an outline of the mathematical background that is desirable to have in order to be successful in the most challenging of courses in the program.

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: Basic programming experience and readiness to learn new tools and features; for example, familiarity with programming in MATLAB, Python, Java, or C++. Basic experience with Microsoft Office business tools, especially use of Excel for data analysis and presentation.


They also have a self-assessment section if you are still having doubts. IMO, if you have the stats to apply and have a decent amount of math in your background you can augment it with some community college classes. I've known a number of successful applicants who have done this. Additionally, while you want to go into the program with a background like this, don't assume the program is effectively a MFE type degree. You can customize your classes in whatever fashion you please. The program can be as quant or as non-quant as you like. For those so inclined, the school now offers a financial engineering concentration. Food for thought if this is what you really enjoy.

Don't the program expect any knowledge in corp/quant finance?

If they want that, it would be listed on their website. The program isn't as quant as a MFE program.