Tourist1703 wrote:

Hello there! I am a student at a top Kazakhstani school, joint degree with LSE( math&econ), sophomore and considering to apply in 2 years to the Ivy league or equivalent for Quantitative Finance( Mathematical Finance, Financial Engineering).

Age: 18

GPA: 3.95/4.0 (expected to be 3.8+ by the final year)

GRE : 170/170 - quant

157/170 - verbal

This is the coursework I take based on our predetermined curriculum :

The Kazakhstani University subjects:

Math -Linear Algebra, Further Linear Algebra, Calculus, Further Calculus (think they are 2-dimensional), Stochastic Calculus, Abstract Mathematics, Optimization theory, Game Theory

Statistics - Statistics( think that it's exhaustive), Econometrics

Economics - Intro to Econ, Microeconomics, Macroeconomics, Labour Economics, Industrial Economics, International Economics

LSE subjects : Linear Algebra, Further Linear Algebra, Calculus, Further Calculus, Stochastic Calculus, Abstract Mathematics, Optimization theory, Game Theory

Statistics, Econometrics, Intro to Econ, Microeconomics, Macroeconomics, Labour Economics, Industrial Economics

1) I am concerned about the amount of mathematics. Is that sufficient? I am also planning to take Differential equations, Probability, Calculus III from other department. What kind of mathematics should I also take?

2) I am also wondering if I need to take Corp/Quant Finance. Do the mentioned programs require this and will I have any competitive edge if I take them?

3) I am also learning R and Python. Differential Equation course offers Matlab also. Could you please elaborate on the extent I need to know the languages. What languages are also essential in the industry, also with the level of expertise?

4) In what entities it would be best to have internship in? I am considering the National Bank of Kazakhstan for now. Could you please tell other places to have internship in? Is it tough for interning in the Wall Street companies?

5) What can I do on top of my current studies to be competitive?

+100 to the karma of a person who answers

Hello

Tourist1703Good for you, I know exactly what Quant Finance is...no need for explanation in brackets

Your GPA is great.

You nailed quant section on GRE, that is what counts the most, verbal is not that important for your intended studies especially since you are not a native speaker, your verbal is more than fine, you are better than 76% of test takers

Don't know why did you put all the same subjects two times, it was enough to say that they are mutual for bot universities, since it is double degree program.

You should not be concerned, math is sufficient.

It is always good to take extra classes such as Differential equations, Probability, Calculus III etc. just to make yourself more competitive, however I don't think is necessary condition as prerequisite, here is example of already mentioned LSE :

"The mathematics used in the programme includes basic calculus and statistics, so applicants are also required to have studied a minimum of A level Mathematics (or its equivalent)."

Since you desire to go to Ivy League school, lets pick another example, for instance Columbia...I don't see any special and stated requirements for their MS in Financial Engineering program.

If we get more serious and check MA Mathematics of Finance at Columbia, we come to this :

Prerequisites:

Applicants should have a very good working knowledge of calculus, linear algebra, elementary differential equations, probability, and statistics, and a programming language.

Exposure to advanced calculus and mathematical analysis, including measure theory, is desirable but not required.Texts recommended for self-study:

Ross: “A First Course in Probability”

Mood, Graybill & Boes: “Introduction to the Theory of Statistics”

Rudin: “Principles of Mathematical Analysis”

I would say this is serious as it can be in terms of prerequisites that you are asking, and you can see that you are mostly already set with appropriate LSE curriculum, the rest is up to you if you want to go extra mile.

In general, all programs will have math boot camp course that will start before your studies where they will make sure you did recheck all necessary math/stat concepts that will be foundations of your future studies.

If you are in the mood for hardcore prep

I can provide you with recommendation :

Calculus: An introduction to differential and integral calculus of functions of one variable, with applications and an introduction to transcendental functions. Techniques of integration; applications of integration. Infinite sequences and series. First-order ordinary differential equations. Second-order ordinary differential equations; oscillation and damping; series solutions of ordinary differential equations.

Multivariable or Multivariate Calculus: Parametric equations and polar coordinates. Vectors in 2- and 3-dimensional Euclidean spaces. Partial derivatives. Multiple integrals. Vector calculus. Theorems of Green, Gauss, and Stokes.

Linear Algebra & Differential Equations: Basic linear algebra; matrix arithmetic and determinants. Vector spaces; inner product as spaces. Eigenvalues and eigenvectors; linear transformations. Homogeneous ordinary differential equations; first-order differential equations with constant coefficients. Fourier series and partial differential equations. Matrices, vector spaces, linear transformations, inner products, determinants. Eigenvectors. QR factorization. Quadratic forms and Rayleigh's principle. Jordan canonical form, applications. Linear functionals.

Partial Differential Equations: Classification of second order equations, boundary value problems for elliptic and parabolic equations, initial value problems for hyperbolic equations, existence and uniqueness theorems in simple cases, maximum principles, a priori bounds, the Fourier transform.

Statistics :

Probability: Random variables and their distributions, expectation, univariate models, central limit theorem, statistical applications, dependence, multivariate normal distribution, conditioning, simulation, and other computer applications. Conditional expectation, independence, laws of large numbers. Discrete and continuous random variables. Central limit theorem. Poisson process, Markov chains, characteristic functions.

Theory of Statistics: Least squares estimates, t tests, F tests, and the application of these procedures to the design and analysis of experiments. Maximum likelihood estimates, Wald test and likelihood ratio tests in the context of logistic regression and Poisson regression. Computer-based applications. Descriptive statistics, maximum likelihood estimation, goodness-of-fit tests, analysis of variance, and least squares estimation. The laboratory includes computer-based data-analytic applications to science and engineering.

Econometrics: Introduction to problems of observation, estimation, and hypothesis testing in economics. Linear regression model and its application to empirical problems in economics.

Numerical Analysis: Programming for numerical calculations, round-off error, approximation and interpolation, numerical quadrature, and solution of ordinary differential equations.

Corporate and Quantitative Finance are not the same. I would always recommend you to take any course related to Quant Finance.

Python (advanced) and R (advanced) are way to go, you can add Matlab (basic) and C++ (basic) to that in order to be even more competitive, if you like.

National Bank of Kazakhstan is certainly good place for internship in your country...I am not familiar what other companies may be present in Kazakhstan but any well know international company will do, especially FinTech these days.

Dont worry much, it is great that you will have basically LSE undergraduate degree and they did really fine job in preparing you for MFE or MAFM studies....when we add on that your GRE quant score, your extra courses, future internship...you will be in great position to be accepted at any master in Quantitative Finance.

Good Luck

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Your kudos are much appreciated