Who are the Quants?
We are a group of students deeply interested in quantitative finance. We are a thirteen-person team, of mostly mathematics and computer science major, hailing from wide a geographic range of four continents spanning a logistically inconvenient eleven time zones. We’re a mixed coalition, but our team is founded by bringing together seasoned investing experience, academic excellence and the spirit of collaboration. Together, we develop algorithmic trading models (algos), promote the education of quantitative finance here on campus and forge a social and human capital community between students and industry professionals.
How long have you been established?
Even though the group was officially formed in February 2017 some of our members have a long-standing interest in quant finance. Several of us possess a first-hand experience of quantitative trading through the internships in hedge funds. Only a few of our members knew each other before joining the group, as we targeted a large audience and put effort into recruiting the very best through our rigorous three round technical and motivational interviews process. However, through our collaborations, our group have been able to become a cohesive bunch.
What is a quantitative analyst?
A quantitative analyst, or “quant”, to put simply, is someone who uses mathematics in the context of finance. There is a very wide range of strategies and techniques that quants utilise. Frequently they incorporate statistical analysis, data mining and machine learning in the development and execution of their strategies. However, the exact tasks mostly depend on what time frame and what financial instruments a quant works with. This year, we actually have a few of our graduating members going into quant finance.
What is algorithmic trading?
While it might sound a bit intimidating, algorithmic trading is just a means of placing trades based on some pre-defined set of instructions (which are sometimes dynamically updated) which are usually tested by means of a backtester. The extent of the algorithm’s participation could be anything from identifying trade ideas to functioning almost autonomously. What algorithms allow for though is a far more efficient manner of analysing large sets of data and identifying complex pattern in the data. Importantly, algo trading helps an investor to be consistent with their strategies and prevents from some of the behavioural biases if handled correctly. Algorithms allow for a much wider range of deployable strategies due to the computational capabilities. An algo could screen and analyse millions of data points and execute thousands of trades within milliseconds.
What is the key selling point behind your society?
As such, we are the first student group of this type in Scotland and still one of the only in the entire UK and Europe. Our aim is to gather bright minds and explore financial markets using a more systematic and scientific approach to investing rather than the traditional fundamental analysis.
Our small size of highly dedicated members lets us stay focused, perform work comprehensively and communicate efficiently. We appreciate the importance of the professional expertise as well as infrastructure which is why we established a partnership with academics on/off the campus and hedge funds. Educational webinars and continuous support of our advisors allow us to navigate our learning more efficiently. Additionally, the supervision we get from our partner firms is especially valuable as they have already successfully accomplished what we aspire to achieve. Furthermore, it helps us to offer students an opportunity to engage in what is becoming an ever increasingly more important factor in the world of finance.
This article was written by Nikita Fadeev, Dillon Yeh and Aizhan Meldebek.