Getting a quant role with bsc in economics and msc in finance and accounting

[AlphaExpl]

Good morning everyone,

I am writing with a question regarding my background and wheather it is sufficient to break into a quantitative analyst/risk analyst role.

My background is the following:

Currently I am working in corporate finance role at F500 company in Europe, but I would like switch my career more into quantiatative finance role/risk analysis.

I hold a bsc degree in Economics from decent regional university in Europe where I studied some possibly relevant courses like mathematics, econometrics, micro/macroeconomics.

Later I graduated from well ranked European business school with master's in Finance and Accounting (with specialization track in finanacial markets and a master thesis in department of quantitative economics regarding risk in financial markets)
So despite my generalist finance degree I did some courses in financial markets, derivatives and financial engineering, although less than in a specialized MFE degree.

I do like programming in R and I've done a lot of courses online (ex DataCamp specializations) so I would say I have some intermediate coding skills (I've also built my own blog with R econometric analyses)
I do know calculus and algebra, statistics and I can possibly refresh and grab new concepts like stochastic caluculus or PDE on my own if necessary. I am quite good at self-learning.

Do you think my background is good enough to be fairly good candidate and break into quant finance/ risk analyst role?

Thanks for your comments,
Peter

 

[Daniel Duffy]

Your background may be too diffuse, as you say yourself.
For economics stuff, more hard mathematics/analytic thinking in maths is probably _very_ necessary.

As regards programming, R is easy to learn but C++ is a real skill. Python is a useful side-kick.

 

[AlphaExpl]

My background reflects my interests, which are unfortunatelly quite wide-spread. But I feel like corporate finance job is too easy and not intellectually challenging. I know my background is not perfect but I hope it is enough to break in with a lot of self studying, which I really enjoy doing. When I look at quantitataive analyst job postings online some of them say they require hard science and STEM candidates, but others only briefly mentions requirements for numerical degree (ex.maths, statistics, finance, economics etc.). I know C++ is the most serious language for quant finance, but I would probably start with a combination of R + Python.

 

[AlphaExpl]

Also is having a traditional finance degree a no for quantitative finance career? (given that a candidate acquires the right skillset which I think is doable with so many good books, open source statistical software and even MOOCs available)

I've read mixed opinions on that topic for example that the industry is more meritocratic when it comes to hiring than other business careers like investment banking/consulting (where the hiring is mostly done only from target univesity), so the degree of a candidate does not matter as much as the skillset. On the other hand I've read that some quant roles are only open to physics/mathematics Phds.

 

[xinlung]

no one has perfect background, at the end of the day its the skills that matter, hard work and persistance

 

[binomial-torrent]

Also is having a traditional finance degree a no for quantitative finance career? (given that a candidate acquires the right skillset which I think is doable with so many good books, open source statistical software and even MOOCs available)

I've read mixed opinions on that topic for example that the industry is more meritocratic when it comes to hiring than other business careers like investment banking/consulting (where the hiring is mostly done only from target univesity), so the degree of a candidate does not matter as much as the skillset. On the other hand I've read that some quant roles are only open to physics/mathematics Phds.

true and not true. depends on the firm

 

[AlphaExpl]

My plan is to have a detailed review of calculus, linear algebra, statistics and probability (by reading a separate book on each topic). Then move to learn how these are applied in quantitative finance (I plan to read 'First Course in Quantitative Finance' by Mazzoni) and also follow MIT OCW mathematics for finance lecture series.
At the same time I will learn python with financial applications to be at least intermediate level.
After all this I think I should be ready to start searching for a quant role particularly in risk management.

 

[AlphaExpl]

Particularly for risk management (I think it is a back office quant), model validation roles, what is the level of mathematics required? Which topics are the most relevant? Is FRM a good qualification to obtain for a risk quant?

 

[Liam]

Also is having a traditional finance degree a no for quantitative finance career? (given that a candidate acquires the right skillset which I think is doable with so many good books, open source statistical software and even MOOCs available)

I've read mixed opinions on that topic for example that the industry is more meritocratic when it comes to hiring than other business careers like investment banking/consulting (where the hiring is mostly done only from target univesity), so the degree of a candidate does not matter as much as the skillset. On the other hand I've read that some quant roles are only open to physics/mathematics Phds.

That's usually based on the experience of the person, but it varies from firm to firm.

Many will be looking explicitly for a PhD, others won't. There are other routes in e.g. risk roles with the aim to then move into QF once you cut your teeth. It's not the best advice as someone suited to QF might not be suited to risk, but it's a damn sight better than some of the claptrap ideas I'd heard from some people, especially people with no finance experience. At the time wondered if their ideas might be good (e.g. become an accountant then "work your way up") but realise now it would end any possibility of a quant role, or at least made it harder. 2-3 years in a role you hate + making it harder than it is now is a horrible trade off for your current situation. You need to be in and around the trading area for starters. That's how working your way up works, not getting any old role than moving around.

Probably also helped that I went through agencies, who were a damn sight better back then, knew my plans and forwarded me to any quant roles that didn't require a PhD. Very simple 2 pronged approach and I started getting joy. If I was graduating nowadays they wouldn't be able to place me. Different market. Or maybe that's changed, been a while since I was in finance.

Point is not the ins and outs of my experience but to be aware that there will be other routes. Just take Einstein's advice on doing the same thing that doesn't work 1000 times i.e. not to and keep fishing ideas out.

In terms of what to do - skill up and get on any intern/open source projects you can. And try and get feedback from quant managers if possible. Even with the shiny PhD and a bunch of quantlib publish it's easy to wind up getting a wall of silence.