Aim of the structured doctoral program
Our program’s ambition is to train the next generation of finance scholars. As such, the central question we ask ourselves when selecting a candidate for an interview (and in the ultimate admission decision) is whether it is clear that he or she wishes to, and has the ability to, pursue an academic research career. Therefore, your statement of purpose should clearly describe your professional goals and how these are in accordance with your existing scholastic and professional achievements.
Characteristics of successful candidates
Here are some guidelines for what you should bring with you:
- A masters degree ideally in Economics or Finance (though computer science, mathematics, physics, statistics, or related fields might be considered) with a
a) clear emphasis on both qualitative and quantitative courses,
b) exceptional grades,
c) outstanding letters of recommendation from at least two professors from the school where you finished your most relevant degree.
- Strong core mathematical skills. Please make sure that this key prerequisite is clearly demonstrated in your transcripts or other records. For those students wishing to concentrate in quantitative topics, this requirement is obviously crucial and will be highly weighted. For those students wishing to concentrate in corporate finance, the emphasis in the program will be more on economic thinking and empirical model building than on pure mathematical methods per se. All students take first-year coursework in a range of subjects, including asset pricing, corporate finance, financial econometrics, and mathematical finance, which must be passed in order to proceed in the program.
- Excellent command of spoken and written English; very mature soft-skills; refined presentation skills.
- The more exposure you have had to the core fields of finance, the better. Thus, a significant understanding of issues in Corporate Finance (even if your master's degree is not in economics or finance) is as useful as an exposure to Mathematical Finance and Stochastic Calculus, graduate level (fully calculus-based) Microeconomics and Financial Economics, Statistical Distribution Theory and graduate level Econometrics.
Your application will stand out if you have a strong background in all of these areas. If you are lacking a background in one of these areas due to the focus of your studies so far, you can make this up on your own, in which case you should be prepared to demonstrate your progress during the interview. On the other hand, no matter how highly refined their training in quantitative methods, the best candidates demonstrate a distinguished ability to speak intelligently, coherently, and diplomatically about various financial matters of significant relevance to society at large.
- Finally, your application gets an additional edge if you have some experience with at least one statistical / mathematical computing package (Matlab, R, Splus, Maple, Mathematica, etc.).
Students with ambitions for entering our program may wish to look at the recommended reading list which we give to newly accepted students.
Graduate Management Admission Test (GMAT) Graduate Record Examination (GRE)
We recommend to do an "at home" test for either GMAT or GRE for candidates who are in areas with limited on-site testing due to the local pandemic situation. In exceptional cases where this is not possible, please contact our PhD Program Coordinator Sarah Wikus (email@example.com).
GMAT or GRE is recommended for all applicants. It is required for applicants with master degrees from non-Bologna states or with master degrees in fields other than economics, finance or business administration ("fachfremd"). Standardized tests can not be waived and scores must be no older than five years. Scores for tests taken after the deadline will not be considered in our evaluation.
The GMAT is expected to surpass 660 points. The GMAT institution code for the University of Zurich, Doctoral Program in Finance is: 7382.
The GRE is expected to surpass 165 for Verbal Reading and 153 for Quantitative Reasoning. The University of Zurich's institution code for GRE ist 7136.
A note on industry work experience
Industry work experience, no matter if it was in the banking industry or other fi nancial institutions, in the area of consulting, the public sector, your own company, a hedge fund, etc., is certainly not required. It can be a useful asset. However, if you have industry experience, it becomes particularly important for you to explain, first, why you are wishing to become an academic (for this is the explicit goal of our doctoral program) and, second, what precise and explicit benefit your experience has had to pursuing genuine academic research.
What to do if your previous degree is not from a top internationally recognized school
Obviously, candidates from internationally renowned universities will have an advantage. Please note, however, that our students come from all over the world. No university is categorically ruled out, but candidates from less well-known universities will have a correspondingly higher burden with respect to demonstrating that their background is commensurate with the desired level. Those students who took the effort to augment their studies with a (possibly second) master's degree from a distinctly higher-ranked university will have considerably better chances.
Another, very smart option is the following. You should consider applying for our M.Sc. degree in Quantitative Finance. That program is also highly competitive and - given its joint degree status with the renowned ETH - is highly visible in both industry and academics. Indeed, students who have successfully completed it are often in an excellent position for pursuing a strong career in the financial services industry and potentially also primed for further studies at a doctoral level. As usual, however, students are not financially supported in this program. If you do exceptionally well in this program, and can also demonstrate the other skills mentioned above, then your chances of entering our doctoral program are quite high.