Ph.D. Prep – Got Math?

Both math and economics are important in preparing for doctoral studies in Finance.  Statistics training is also a very good alternative to economics.  One of the first professors I talked to about getting a Ph.D. post-MBA gave me a list of courses to have under my belt.  I wasn’t able to take all of them, but I ascribe a significant portion of my success in getting into school to following his advice (and doing very well in the courses).

Students planning on getting a doctorate degree in Finance or Economics should choose one or two math-heavy majors.  Math, Economics, and Statistics are probably the best, but there are others that could also work.  John Cochrane, Professor of Finance at the University of Chicago, studied Physics before doing his Ph.D. in Economics at U.C. Berkeley.    The most useful courses include:


  • Math – Full Calculus sequence (three-semester sequence for me)
  • Math – Linear/Matrix Algebra
  • Econ – undergraduate-level Price Theory (two-semester sequence for me)
  • Econ – undergraduate-level Financial Economics
  • Econ – graduate-level Price Theory
  • Econ – Statistics for Economists (there may be a comparable stats course)
  • Econ – undergraduate-level Econometrics (my school offered two of these, and I took them both)
  • Econ – graduate-level Econometrics

A good measure of whether you’ll survive graduate school is enjoying and succeeding in the grad-level courses, Econometrics, and Financial Economics.  I took many of these “critical” courses as an undergraduate in Economics.  I squeezed the rest into my MBA schedule:  Multivariable Calculus, Linear Algebra, grad-level Price Theory, undergrad-level Applied Econometrics, and grad-level Econometrics.

Good to Have

  • Math – undergraduate-level Real Analysis (Stanford specifically mentions “analysis” in skills they want applicants to have)
  • Math – graduate-level Real Analysis
  • Math – Ordinary Differential Equations
  • Math – Partial Differential Equations
  • Math – Mathematical Finance
  • Math – graduate-level Advanced Probability
  • Econ – Game Theory
  • Econ – graduate-level Mathematical Economics
  • Stats – SAS Certification (see post “Ph.D. Prep – Stata vs. SAS”)
  • Stats – Statistical Computing
  • Stats – Statistical Theory
  • Stats – Stochastic Processes
  • Stats – Bayesian Methods
  • Stats – Time Series
  • Stats – Multivariate Analysis

The only course I took of these was Ordinary Differential Equations.  I will probably want to take more during my Ph.D.

Also, Consider a Minor

  • Economics
  • Statistics
  • Mathematics (I completed the equivalent of a Math Minor, but I won’t actually get it since it’s not part of the MBA program)
  • Computer Science

I added Computer Science to this list.  Many successful researchers are also proficient computer programmers, who are good at collecting and processing large quantities of data.  The most common programs/languages I hear are SAS, Stata, MatLab, and Python.

Ph.D. Prep – Introduction

In these first few posts, I want to discuss what goes into preparing for Ph.D. studies.  After I started my MBA, my preparation path went something like this:

  1. Consider investment banking vs. academia
  2. Decide on an academic career and sign up for math/econ courses
  3. Work as a research assistant
  4. Read academic research
  5. Apply to schools
  6. Learn to program

I-banking prep basically meant networking and studying valuation techniques 2-3 hours/day for about three months and traveling to New York and San Francisco, on top of 17.5 credits of first-year required classes.  Around December of my first year, I determined that a Ph.D. was still definitely attainable with enough effort, and that’s all I’ve worked on since.

The biggest attraction to an academic career for me is the intellectual freedom.  Sure, you have to work really hard and publish, but you don’t have an Associate, Vice President, Managing Director or Partner always looking over your shoulder to make sure your ideas are “right.”  Professors aren’t required to be at the office (unless they’re teaching a class), and they aren’t forced to stay up all night working on somebody else’s project.  It’s not only a very stimulating career; it’s also incredibly entrepreneurial–success means coming up with your own unique ideas, communicating them well, and getting peers around the world to “buy in.”  The pay can also be very good, unlike in many other academic fields.

For more information on getting a Ph.D. in Finance, check out this link that one of my future classmates put together before he started his Ph.D.:

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