• C++ Programming for Financial Engineering
    Highly recommended by thousands of MFE students. Covers essential C++ topics with applications to financial engineering. Learn more Join!
    Python for Finance with Intro to Data Science
    Gain practical understanding of Python to read, understand, and write professional Python code for your first day on the job. Learn more Join!
    An Intuition-Based Options Primer for FE
    Ideal for entry level positions interviews and graduate studies, specializing in options trading arbitrage and options valuation models. Learn more Join!

PhD in Stats vs Applied Maths vs Pure Math

The_Saint

Joined
8/24/15
Messages
1
Points
11
sorry for the short body, but my laptop is on the fritz and i have to use the on-screen keyboard to type. so basically my question is which would be most beneficial to acquire to enter the field? I am at a crux between my desire to do the modelling, but i also want to be able to use the models as well (i.e trade).
 
Quant finance is really at the cross roads between stats, applied maths and pure maths. Stats: time series models, stat arbitrage. Applied maths: partial differential equations, stochastic differential equations. Pure maths: probability, real analysis. measure theory.

I would suggest picking a supervisor who is in the field, and not a specific specialisation of PhD, since in the end, it is not the label of your PhD, but what courses you took, your actual thesis and your supervisor, that matters.
 
Back
Top