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little_fermat


Total Posts: 1
Joined: Jul 2018
 
Posted: 2018-08-08 20:26
Hello,

First time posting, I have been reading a lot of the phorum over the past several months and the wealth of information here is incredible. I am starting a Master's in Statistics and I was hoping to get some advice from the members here on course selection.

My program offers several different "tracks" within the stats dept. Quantitative finance and machine learning are the two that I feel are most relevant to my career goals. The quantitative finance track is heavy in things like stochastic processes, and time series modeling. There are also electives in everything from numerical methods to portfolio theory. In ML there is the standard set of data mining/statistical learning classes and also things like deep learning and natural language processing.

Ideally I'd like to get a job where I could be part of a team that researches and implements automated trading strategies. Time frame/asset class aren't really that important to me I'd just like to work in a group that applies a scientific approach to trading, i.e. hypothesize strategy, research and backtest, implement and track results.

My question is whether anyone has an opinion on which track would better serve that career goal. My bias is towards ML but this only comes from analyzing keywords in job postings. I've looked at ~15 companies which seem to do what I'm interested in (mostly hedge funds and prop shops), and the job postings seem to emphasize data analysis & programming skills, and in some instances ML specifically. I see less regrading stochastic processes or portfolio theory but these postings are pretty vague.

I'd guess that both are viable options and there are a variety of firms applying all sorts of strategies. I've spoken to a few people who work adjacent to the industry and that seems to be the general consensus. One person I talked to gave the advice that I should choose the track where I was most interested in the material. Gun to my head I would say ML but honestly I think the technical aspects of both are quite interesting and I could see myself being happy with either choice.

I should add that I have some basic academic background in CS (C, python), have taken courses in databases and operating systems and my undergraduate was in pure math.

Any input would be greatly appreciated,
Thanks

TL;DR: Quantitative finance or ML for systematic trading strategies?


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