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MSc Statistics for Quant Research

Hi all,

I was recently accepted into an MS in Statistics, and I am interested in which optional courses would be best for Quant Research roles.

These are my options (further module details here):
imperial_courses.PNG


Maybe paradoxically, I wasn't intending to take the intro/advanced statistical finance options, preferring to focus on statistical theory (I am also considering pursuing a PhD in Statistics after graduating).

Currently, I have considered:
- Contemporary Statistical Theory
- Bayesian Methods
- Advanced Simulation Methods
- Multivariate Analysis
- Time Series
- <unknown final module>

Which module seems best for the final spot? Do my current options seem reasonable?
 
Let me first say, it is kind of difficult to make a suggestion just based off the name of the class - the syllabus has better info.

Are you interested in ML? If so, I would recommend taking the course in deep learning. I have read several papers recently that are applying deep learning techniques to price derivative products. The graphical models may be a close second, but again, I do not really know the content that will be covered.

Since you are getting you PhD, do it really matter what you take? You will have at least another 2ish years of courses.
 
Let me first say, it is kind of difficult to make a suggestion just based off the name of the class - the syllabus has better info.

Are you interested in ML? If so, I would recommend taking the course in deep learning. I have read several papers recently that are applying deep learning techniques to price derivative products. The graphical models may be a close second, but again, I do not really know the content that will be covered.

Since you are getting you PhD, do it really matter what you take? You will have at least another 2ish years of courses.
Hi, thanks for the advice. There's more detailed syllabus information in the 'further module details' hyperlink if that's helpful.

I'm trying in part to maximise my chances of getting into a PhD program, so I don't want my module choices to appear too 'broad'. Generally what I have found most interesting so far are topics relating to statistical learning theory.
 
To add a few more comments: for a quant research role in the finance industry, you will need to be familiar with elements of multivariate analysis and time series. The methods you learn in these courses would not often be directly applicable in a trading environment, but the definitions and concepts are critical. The algorithmic trading course looks like a good possibility as well. (Disclaimer: I didn't read the syllabi, I'm just going by course titles.)

Programming skills are also important (beyond just Python familiarity), but that's not usually a strength of statistics departments. If you can supplement the statistics training with some more rigorous programming courses in the CS/Engineering school/department, that could be helpful as well.
 
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