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Transitioning into Quant Roles from Enterprise Risk

lax_milgram

New Member
Hi All.

To give a bit of background - I have a bachelor's degree in engineering and I recently completed a master's degree in computational fluid dynamics where I wrote a thesis on designing and optimizing new numerical non-linear PDE discretizations (energy/entropy-stable methods). During my master's I coded mostly in MATLAB, FORTRAN, bash, and some C++.

After I graduated I obtained a position in enterprise risk for a large bank in Toronto, Canada doing model implementation for regulatory stress-testing credit risk models i.e. estimating PD, LGD, EAD (been here for about 10 months). This doesn't intersect with the front-office at all and is primarily about the bank's loan/credit portfolios - I spend most of my day doing model testing, UAT, coding in SAS and bash, ad-hoc stress-testing runs with our platform, investigating bugs, looking through the models and communicating with model development. Most of the models are statistical models: linear/nonlinear regression, Markov chains, Gaussian copulas, hazard models etc.

I'd like to transition to a front-office quant role in capital markets or market risk at one of the large Canadian banks (my current bank for example) doing model development. In my current role I found I'm more interested in something which is a bit more mathematical and related to my Master's research. I've already found some groups in my bank that are doing exactly what I want to do i.e. developing models for pricing exotics, IR derivatives, XVA etc. or working with these groups to develop risk models. However, I realize that I'm lacking some skills (mostly in stochastic calculus) so have the following tentative plan for the next year:
  1. Refresh linear algebra (since I've forgotten a lot since undergrad and only used basic numerical linear algebra during my master's research)
  2. Refresh probability: Introduction to Probability by Blitzstein and Hwang
  3. Options, Futures, and Other Derivatives by Hull
  4. Financial Calculus by Baxter and Rennie
  5. Stochastic Calculus for Finance II by Shreve
  6. Code up some derivative pricing models in C++/Python
I was wondering if anyone any suggestions about how to make myself competitive for these types of roles or any other things I should be working on? I don't really have any interest in getting an MFE degree since they're extremely expensive and I feel confident that I can learn most of these things on my own. If anyone currently works in Toronto in a quant role I'd be happy to hear from you.

Thanks.
 
Last edited:

KillingField

Active Member
Instead of asking random, anonymous people identifying or aspiring to be quants (whatever their definition of the term may be), I would encourage you to network internally. You're going to get much better colour on your locale, and a better understanding of what the teams you wish to join expect of an entry level candidate. The sooner you express your interest and start making moves, the better: It is easy to get pigeonholed.

While having the basics nailed down with something like Shreve is beneficial, knowing and understanding models actually used by practitioners is even more so. You may already have or be able to gain access to the internal model documentation or if not the full thing in detail, it is likely some presentations have been circulated to a wider group. They may be written well enough and be detailed enough that you can learn out of them, and maybe even implement some of the models yourself. Network, and find out.
 

lax_milgram

New Member
Instead of asking random, anonymous people identifying or aspiring to be quants (whatever their definition of the term may be), I would encourage you to network internally. You're going to get much better colour on your locale, and a better understanding of what the teams you wish to join expect of an entry level candidate. The sooner you express your interest and start making moves, the better: It is easy to get pigeonholed.

While having the basics nailed down with something like Shreve is beneficial, knowing and understanding models actually used by practitioners is even more so. You may already have or be able to gain access to the internal model documentation or if not the full thing in detail, it is likely some presentations have been circulated to a wider group. They may be written well enough and be detailed enough that you can learn out of them, and maybe even implement some of the models yourself. Network, and find out.
Good advice, thanks. I think I will plan to network internally after I build a bit of a foundational knowledge in the subject (as given by my study plan). Unfortunately, I don't think I have access to our internal financial engineering libraries - that would be a great resource to have. I know that they are primarily developed in C# server applications. I'd imagine it's probably something quite similar to quantlib. The desk quants happen to be on the capital markets side of the bank which is a different branch from where I sit, which is on the enterprise risk side.
 
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