Interview Process | Master's in Quantitative Finance ETH UZH

Official Timeline

• November 22, 2023: Submission of application. My references submitted the reference letters later, but I do not exactly know when.
• February 29, 2024: Received an invitation for the interview, I scheduled this on 26th of March.
• March 26, 2024: Conducted my interview.
• March 28, 2024: Received provisional admission & accepted it.
• September 16, 2024: Official start date of the Master’s program.

Admission Process

As I received a lot of information and help from my peers, it’s only fair for me to share my complete admission process.

Preparation

Before you start applying, approach the people you want to put in as your reference. I asked my Bachelor’s thesis supervisor and also the professor of whom I was a teaching assistant for.

There are three different outcomes for the admission process

1. Direct admission based on a strong profile
2. Invitation for an interview, and based on that acceptance or rejection
3. Direct rejection.

To be honest, when I applied I knew my chances for direct admissions were rather slim, as I lacked a direct finance and mathematics background. It was likelier for me to be invited to an interview (or not), since I had good reference letters and a strong (but not complete) mathematical foundations. So not long after I applied, around January, I already started preparing for the entrance exam, since I was working full time and did not have much time left otherwise if I were to get an invite. I knew if I were to get an interview, I would not want to risk being unprepared. Is it necessary for you to do this? Maybe not, I know many people who did not prepare much and got accepted. This is something for you to decide based on your situation.

During my preparation I mostly focussed on probability theory, especially on Martingales and Finance. I did briefly look into macroeconomics and microeconomics, but in the end it was not important anyway and it’s not that complicated.

Linear Algebra & Calculus

Most of the questions you can expect here are rather basic things:

• Formal definition of derivatives, integrals, limits, etc.
• Eigenvector, eigenvalues
• Properties of determinants and traces

Probability Theory & Statistics

I would generally recommend to go through the book “Probability Essentials by Jacod and Protter”. It will cover all the probability theory material you need. For statistics I just depended on the lecture notes from my bachelor’s.

• Martingales
• Filtration
• Emphasis on normal distributions
• p-stats, (un)biased estimators, power, p-value, confidence interval, etc.

Finance

There weren’t any questions on Economics for me at least and everyone I have spoken to, but I think it does not hurt to be familiar with some basic economic concepts. Most of the stuff you can find within online sources and books, I did not really have direct sources.

• Efficient Market Hypothesis and how it translates into the general assumptions of many models
• CAPM, Binomial Option Pricing Model, Black Scholes
• Behaviour of option prices if you consider volatility, time to maturity, etc. (Greeks)
• General stylized facts of financial returns, volatility clustering, uncorrelated returns, etc.
• Distributions of returns and asset prices, and generally ask yourself why we make these assumptions.

Questions

During the interview there were questions across finance, linear algebra, probability theory and statistics. I also gathered some questions from the internet, previous students, and others who also did the interview.

Finance

• What is arbitrage and what is arbitrage in a mathematical form?
• What is the put-call parity?
• What are the assumptions in Black Scholes?
• What is an European Option?
• Explain diversification and its purpose, are there any downsides?
• Explain Efficient Market Hypothesis. Does it hold, why or why not?
• Describe the setup of a binomial model and its no abitrage condition.
• How does the price of an European option behave when volatility is high or low?

Linear Algebra

• Given a square matrix A, with the property that $AA = A$. Show that the eigenvalues are either 0 or 1.
• Explain what an eigenvalue and eigenvector is, in words and mathematical form.
• Given a symmetric matrix, what are the properties of the determinant and trace?

Statistics

• What is a p-value?
• What does power mean in a statistical test?
• Given we flipped a coin 10000 times, we noticed we got 5200 times heads. Is it a fair coin?
• What is the difference between a biased and unbiased estimator? Can biased estimators be useful?

Probability Theory

• Given two independent binomial distributions, as $Bin(n_1, p)$ and $Bin(n_2, p)$, what can we say about the distribution of the sum?
• Draw the PDF and CDF of a standard normal distribution.
• What is the value of the CDF of a standard normal distribution at 0?
• State the Central Limit Theorem.
• Let $X$ and $Y$ be two random variables, what is variance of $X + Y$?
• Suppose you have two independent random variables, with zero mean. What is the variance of $XY$?
• Define a martingale and provide a stochastic process that is not a martingale.
• Given $Z$ as a standard normal distribution, what is the distribution of $aZ +b, a,b \in \mathbb{R}$.

Calculus

• Let $f$ be real valued on an open interval $\mathcal{I}$. What is the definition of a derivative at point $x \in \mathcal{I}$?
• Solve $\int_0^1 log(x)dx$