Lacking skills in HF/PE/IB after studies

What do you think are great skills in top jobs at HF/PE/IB besides your current study/studies?
I'm doing MSc in Real Estate Management and Development and MSc in Finance, but increasingly see the added value of in-depth mathematics, statistics, programming (combined with AI) and the general (international) management skills.
I guess you guys also must have thought during your master/bachelor studies: ''how to develop myself further to become the perfect candidate for a job''.
What did you do? Is a certificate valuable or just follow some quant courses? Then again, by following some quant courses I may not have any advantage to the ones that did a full-time quant study. So, what to do?

 
Best Response

well it depends on what sort of HF place you want to work at where supplemental skills becomes even a discussion--you'll be hard-pressed to justify learning stochastic processes for work at an event-driven shop. i realize you essentially want optionality or the appearance of being a multi-faceted candidate, but the premium you have to pay is ridiculous in this case (time and tuition dollars and sanity). that being said, i got a bachelor's in applied math along with another softer major that was secondary, and I still don't feel like I got enough perfect quant training, so it never really ends with regards to quant.

If anything, I would actually consider a bit of philosophy or history--understanding the difference between a priori and a posteriori arguments is crucial before getting into the nitty-gritty of a fundamental model or a quant model. The reason why I find the very smart history majors interesting people to talk to at work is because they understand that most data you stare at boil down to the basic questions of

-why are things the way they are? -where should things be going?

History majors can come up with good analysis for the first question, and appreciate the challenges of the second. The dependence between those two questions is the devil--how much of your forecast or thesis is actually influenced by the past, and should it be influenced by the past at all? Do you really know how your model is going to behave a priori under certain scenarios? Quant attacks this through several higher-level statistical methods, but learning how to come up with an acceptable answer to the dynamic between these two questions for more normal HF work is critical.

I really can't speak for PE/IB though.

 

Thank you syntheticshit. I have never looked at philosophy and history in that way. Have had a course on philosophy and ethics, but always thought: ''just read the book once, pass the exam and be done with this course in the least amount of time''. Those courses give a deeper understanding, which is beneficial for all kinds of jobs. However, I don't think that HF recruiters specifically value courses like these. I want to just have a little advantage over other candidates in my CV when applying for a job. I understand that 1 course will not help, so I am considering a certificate on in financial modeling. At school I also can choose subjects in areas such as econometrics, mathematical economics, international management, marketing, accounting, strategic management, psychology, law, etc. Just don't know if soft skills are better than the quant skills

 

For IBD: all you really need is accounting, a very little bit of programming, and common sense.

As you mentioned, programming is very useful; you don't have to know every language or even know programming to any deep degree, it just helps to understand that style of logic and translates much more easily into newer languages (what i mean by this is that it's generally much easier to learn a second programming language than it was to learn your first). Even very basic programming knowledge goes a long way.

As far as humanities vs hard sciences/quantitative courses, I (and most people) would put more weight on the more quantitative stuff, and with good reason- most topics in the humanities can be understood through logic and reasoning, so there's no prerequisite knowledge, unlike courses in other subjects; for example, in econ, for any given argument supported by a quantitative model, you might have to know muitlvar calc, linear algebra, metrics, or statistics.

For what syntheticshit mentioned, yes it's important to understand whats endogenous and exogenous to a model, but you don't really need to have any special knowledge to figure that stuff out besides reasoning skills. I will say that it is very beneficial to take courses in different ares, if only to complement your knowledge in your major area of study.

 

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