Engineering… in Finance?
There may be a plethora of reasons for someone to be interested into the world of finance, while primarily pursuing an engineering degree. As such, this post might be a little click-baity, and we apologize early on for this generality. While this does not mean we want to discourage you from reading further, we just want to clarify, that this post is intended for those who are pursuing engineering, don’t loathe engineering, and appreciate the importance for intelligent management of wealth — essentially an inclination toward finance, with a penchant for numbers.
“I believe those who think scientifically often perform the best in this field. Often the best quants are those with a background in math, computer science, engineering or a natural science (i.e., physics). There is a reason funds like Renaissance Technologies only hire scientists (at least for their research side). They are not interested in MBAs or those with degrees in finance/business or economics, as would be the case with your more traditional Wall Street analyst role. Often, those schools of thought teach reliance on models that are too “academic” and rely on too many assumptions, creating unnecessary fragility.”
–Micah Spruill, co-founder and quantitative analyst at Aurora Investment Advisors
What initially began as thought experiments and pass-time research for mathematicians and physicists suddenly gave birth to an entire industry with one key paper. Albeit what started out as a way to price financial instruments soon evolved into a variety of ways mathematics could be intelligently used to mitigate financial risk.
As an engineer, you add value to the financial field with your keen aptitude at tackling problems logically, and you’d know you’re a good fit if you already have experience dealing with burdensome deadlines and efficiently searching for ways to complete compulsory courses that might not be interesting to you at first. These may include all of those courses that you may feel will add no real value to your professional life, should you choose to pursue finance (although several computer science and electrical courses like Database Management, Signal processing, Communication Networks etc could add direct value to your skills). No matter what your stream, with the correct selection of courses in your undergrad, you’ll be able to unlock a variety of options for higher studies revolving vaguely around the term — ‘Quant Finance’.
Recruiters always prefer to hire people in the financial industry who are ready to face adverse situations adeptly — and by tackling core subjects for over 3 years, you will definitely get to test yourself at this integral quality — which brings us to the question of GPA.
“Quantitative professions require a high GPA, we only hire people who were at the top 1% of their class” — while this may be true for some firms, it might not necessarily be true that these are the top firms. On the contrary, it does not make sense to expect undergrad to be the end of your life as a student if you want to go far in this industry. It values people who stick around for higher studies to really master the subject.
So what to do now? Now that you are in your freshman, sophomore, junior or senior year undergrad, maybe a graduate, maybe an industry professional looking to switch careers, how exactly does one “dip their feet in the waters” of financial engineering? Well, the most important resources are people. People who can point you to the right things. While the following section highlights some popular resources and forums to discuss quantitative finance, it is by no means meant to be exhaustive — rather it has been kept purposefully concise to ensure quality as well as generality for you to find resources that suit your level of comfort. The best way to grow in this field is to find a mentor, explore the seas after an initial swim, pick a specification and start getting your hands dirty with personal projects and/or internships.
“Alright enough talk, how do I get started?” Again, this list is meant to be a concise way for you to get started, and soon find your own way into this wonderful field — be it the hardcore mathematics that goes into modeling complex financial data or the software development and computer skills required to optimize high-latency algorithms efficiently.
So here are some resources to get started with QFin:
> Blogs and Forums —
1. EP Chan: https://epchan.blogspot.com/ — EP Chan is a pioneer in the industry and his takes on several strategies are really eye opening
2. Nuclear Phynance: https://www.nuclearphynance.com/ — A great forum with a dedicated community for resource sharing and idea generation
3. Quantocracy: https://quantocracy.com/ — With a very active user base and a huge list of resources
> Online Courses —
1. Financial Engineering and Risk Management Parts 1 and 2, Columbia University: https://www.coursera.org/learn/financial-engineering-1
2. Finance and Quantitative modeling for Analysts, UPenn: https://www.coursera.org/specializations/finance-quantitative-modeling-analysts
3. Practical Time Series Analysis, SUNY: https://www.coursera.org/learn/practical-time-series-analysis
> Research communities—
1. SSRN: https://www.ssrn.com/index.cfm/en/ — General research community for all things finance. You can find all major landmark papers here.
2. arXiv: https://arxiv.org/search/q-fin — Most updated research community for quant finance. You’ll be able to find new and disruptive research here.
Extra → awesomequant on github — Great repo on github with a list of libraries and resources and a few open-source “papers with code”, which are becoming increasingly valuable due to the huge black-box nature of the industry.
All the best!
