A career in quantitative finance can be extremely rewarding both intellectually and financially. However, competition is fierce for positions within hedge funds and investment banks. Having straight As and a first class science degree is not sufficient anymore, especially since the downsizing of the industry that followed the 2007/2008 economic turmoil. So what qualities does a good candidate need to possess and what can you do to get that elusive role as a quantitative analyst?
The term “quant” covers a broad spectrum of roles. Areas such as quantitative trading, quantitative research, risk management, derivatives pricing and numerical software development all fit within the term. Hence, the first step is to identify your core skill set. Once you know where your skills lie, you’ll be in a much better position to apply for the correct type of role. These days, investment banks are hiring less, while private funds are hiring more. Hence there is a shift away from derivatives pricing (due to the backlash over the mortgage securities models) towards statistical trading methods.
There are three main entry routes into quantitative finance. The more traditional method is to gain a PhD in Mathematics, Physics, Engineering or Computer Science. Useful areas of research include Probability, Statistics, Stochastic Calculus, Machine Learning/Pattern Recognition and of course, Mathematical Finance. A PhD program lets an employer know that you are confident researching material independently and do not require “spoon-feeding”. This is especially important in some of the research-led “collegiate” atmospheres of the top tier hedge funds.
The second, and more recent, route into quantitative finance is through a Masters of Financial Engineering (MFE) program. These courses are often taken by individuals who may lack specific numerical skills in the financial area, but are nonetheless mathematically confident. They are particularly well suited to individuals who wish to make a career change. A good MFE program from a top school will prepare the student in areas such as derivatives, probability/stochastic calculus, risk management and programming (likely C++). The professors will have good links to firms looking to hire and the network alone can be worth the high fees (often in excess of $50,000).
The third route is more suited for talented software developers, particularly those with advanced object-oriented experience – C++ or Java being preferable. These “quantitative developers” will work closely with the quantitative analysts to implement the models (often a prototype) in a robust and optimised manner. The required skills can be varied in nature. A high-frequency trading fund may require low-level operating system and concurrency skills, while a systematic pattern recognition firm may be interested in your machine learning talents. One thing is certain though – programming skills are rapidly becoming the differentiating factor in interviews, so the better your C++/Java/Python/Matlab/R skills, the more likely you are to receive that lucrative job offer.