Maintaining a deep pool of talent and fostering innovation are key to the long-term success of every global bank. To help build a pipeline of highly qualified finance professionals, EFG collaborates with the Master of Science UZH ETH in Quantitative Finance offered jointly by the University of Zurich and the Swiss Federal Institute of Technology (ETH) Zurich. Established in 2009, it ranks as the top programme in its field in Europe and the 7th worldwide.
Can you tell us in a few words what Quantitative Finance is all about – and why it is important for banks like EFG?
Quantitative Finance is a field that helps us to evaluate massive volumes of financial data in a short period, which is one of today’s key challenges. Quantitative analysts develop (mathematical) models and apply them to financial markets to assist the trading and risk management units of banks and other financial institutions. Examples include the pricing of derivatives or risk management questions related mainly to portfolio management applications.
The Master of Science UZH ETH in Quantitative Finance has a strong connection with industry. Why is your collaboration with firms like EFG so valuable from an academic perspective?
Our well-established, multi-dimensional co-operation with industry has numerous benefits. Lectures are taught by world-leading scholars in our field, as well as top financial practitioners. Our students profit from the expertise of leading research groups at two top academic institutions but also from our proximity to Zurich’s financial centre. Our contact with banks, insurers and reinsurers leads to partnerships, internships and job opportunities for students. This collaboration with industry also means that our students are exposed to the latest developments in financial economics, financial markets, and asset and risk management.
And how does this collaboration benefit your industry partners?
Our partners are pleased to be able to hire talented graduates who are well equipped to take on challenging roles as specialists in quantitatively oriented areas. We have high placement rates in risk management, asset management and financial product development.
How do you keep pace with developments in the fast-moving finance industry and ensure the knowledge and insights you share with students remain highly relevant?
Our modern and flexible curriculum allows us to do this. We have a package of “core courses” covering the fundamentals of Quantitative Finance. We also offer a large number of electives that may change from year to year to reflect developments in the industry. We will, for example, run new courses on “Data Visualisation in Finance” and “Quantitative Portfolio Management with Python” in the coming months.
What do you regard as the biggest breakthrough in the field of Quantitative Finance in the last decade? How has it influenced the financial industry?
That is a difficult question to answer as Quantitative Finance is constantly evolving in line with new tech and data trends. Key developments shaping our field at present include the use of machine learning and AI, high-frequency trading, cryptocurrencies, blockchain technology, social media and alternative data, as well as ESG investing. Each of these presents opportunities and challenges for investors and financial firms, and it will be important for the industry to navigate these changes responsibly and ethically. As tech and data continue to advance, trends will change but I am quite sure that Quantitative Finance will remain a driving force in the world of finance and investing.
The emergence of new digital financial technologies in recent years has disrupted traditional business models in banking. What is your view of FinTech and what does it mean for the future of Quantitative Finance?
The intersection of finance and technology, so-called FinTech, has been transforming the financial industry for decades. Historically, technology was deployed quite early on to assist with data processing and automation. Modern Portfolio Theory emerged in the 1950s and 1960s, and the use of machines was a natural fit for those seeking to analyse stocks, assess the efficient frontier and engage in portfolio optimisation. With the rise of option pricing and quant trading in the 1970s and 1980s, computers became a cornerstone of the derivatives market. In the early 1990s, electronic trading platforms were introduced, driving the global expansion of the stock, bond and credit markets through the 2000s. For Quantitative Finance, the spectacular growth in the volume and variety of data triggered intense activity in machine learning in the 2010s, and that has continued. I am convinced Quantitative Finance skills will remain absolutely essential for the future of FinTech.
Robust risk management is vital for the sustained success of any bank. How are Quantitative Finance theories applied in practice by banks to effectively assess and mitigate risk?
Yes, risk management belongs to the core competence of banks. A risk measure indicates the amount of capital needed as a buffer against (unexpected) future losses. Banks now use an academically proposed approach to measuring risk based on loss distributions – statistical quantities describing characteristics of the loss distribution of a portfolio.
Can Quantitative Finance also be applied in the area of ESG, e.g. to measure the impact of sustainable investing?
A variety of criteria exist to determine what is or is not sustainable but it is difficult to assess the actual impact of companies and their activities on the “surrounding world”. We need to clarify what we want to measure, how we can measure it and the data we want to use. Quantitative Finance specialists can help to address these questions – but they cannot determine the outcome on their own. I recently launched a research project where scientists from UZH and ETH have begun work with the financial industry to measure the impact of sustainable investments.