The Rise of the Mathematical Millionaires on Wall Street

– By Khushal Madan

The fast life at the World’s Financial Capital has never failed to invite proficient and capable finance professionals to pursue their prowesses. Until recently, there was far less penetration of professionals from the engineering fields in the finance job market. However, with the recent economic instability and the need of the hour to quantify finance in a way that aids process and functionality, a branch of engineering and quantitative data analysis has been coming up. This branch or field of study has been formalised in recent times, giving birth to the discipline of Quantitative Finance or Financial Engineering.

What is Financial Engineering?

Financial engineering, by definition, is an engineering discipline. It is a combination of a study of quantitative finance and computational mathematics. Financial engineers usually deal with the quantitative aspect of the derivatives market. These engineers are specialists who formulate financial structures to solve unconventional problems that are not routine to finance. These structures are created after delicately analysing past financial circumstances and how markets reacted to them. These models or structures describe, in mathematical terms, the relationships between financial random variables and financial assets. 

Financial data contains both important data and irregular clamour. A good financial model will extract only the meaningful information from the historic circumstance and further process it to only the relevant information that would function well with the new data from the current circumstance.

Accordingly, financial engineering enunciates robust financial economics with systemic financial renaissance and branded financial market growth. It mixes derivatives and creates a framework for a proper financial market system. These services include resource mobilisation and allocation, good governance, law, financial intermediation and foreign exchange facilitation to promote international trade.

The shift to STEM in education and jobs

Prof. VK Kamakoti, director, IIT Madras, said in a report to The Week that STEM is also leading to innovation and entrepreneurship and that is why the demand for STEM courses is slowly increasing. He also added that all mathematics based courses have a wide range. According to an IBM study released in March 2023, 66 percent of respondents believe that STEM jobs will increase over the next decade. IIT Madras’s departments of management, computer science, engineering and mathematics have jointly started offering an interdisciplinary dual degree quantitative finance program since January. The course combines technology and finance and enables students to contribute towards the quantification of finance. 

According to WorldQuant University, 2022 graduates from Berkley’s Master of Financial Engineering program have attained employment in industries like asset management and investment banking with their roles relating to portfolio management, quant research and analysis, trading and data science. Companies of all kinds are seeking financial engineers. It is not just large trading firms and financial institutions like Jane Street, Goldman Sachs, and BlackRock but also tech giants like Google and Microsoft. The skills attained from financial engineering can be applied in sectors more than just finance, like technology, economics and policy making. Financial engineers are innovators by nature as their main role is to discern the patterns in data after clearing out all the noise.

Ronald N. Khan who is the Global Head of Advanced Equity Strategies of Barclays Global Investor majored in physics as an undergraduate at Princeton in the late 1970s. He says that in graduate school, he experienced a shift in focus due to his curiosity to find interesting and solvable problems. In the late 1980s, when Wall Street was beginning to hire quants, all people who had the technical know-how of applying rigorous scientific analysis to investing whether or not they had advanced financial knowledge were getting hired. The genesis for this rise was the interest rates rise and volatility in the late 1970s and early 1980s. 

Most of the quants on Wall Street in major trading firms have had a background in the sciences, like physics, chemistry, computer science, statistics and mathematics, or arts that are closely integrated with the sciences, economics, advisory and policy making. A major reason for this is the need for the precise utilisation of mathematical methods including models and structures required for financial management and risk management, subsequently, raising demand for STEM courses.

Historic Real World Application

In a 2008 article by Steve Lohr of The New York Times, Financial Engineering was dubbed  “Wall Street’s extreme sport”. The reason for it being referred to as such a risky field was the delicacy of the utilisation of mathematical models of risk. After the 2008 Global Financial Crisis, some economists were also criticising the use of a popular mathematical model for investing in financial derivative instruments-the Black-Scholes Formula for contributing to the severity of the economic crash. 

The failure in financial engineering during the period of 2007-2008 gave it an infamous reputation in front of Wall Street. As claimed by economists, the models failed to keep up with the fast paced growth of the complex securities resulting in increased risk and severity of the crash. However, the reality was that the nature in which these risk models were applied and understood was vastly different from what should have been done. Experienced financial engineers had been pointing out the warning signs years ago. However, traders on Wall Street continued to pile up bets and make bets while the highly complex securities were booming, not releasing that a sophisticated security like a credit default swap which is a derivative would always draw its value from an underlying asset. Andrew Lo, a professor of Finance at MIT Sloan in 2008 claimed that the technology was ahead of the quants’ ability to use it responsibly. 

The future of Financial Engineering

According to a report, in the year 2022, 54% international students in the United States preferred STEM education over the fields of business, management and humanities. However, when you consider financial engineering, although quants have been around since the 1980s, it is still looked at as a new age degree. An average employer on Wall Street would prefer hiring a Computer Science undergraduate for a quant position rather than a person with a masters in financial engineering from an average school. Usually hiring for quant roles for graduates with a masters in financial engineering is primarily done from target schools. Some of these target schools being Baruch College, Columbia University, New York University, UCLA and Georgia Tech. 

A role in quantitative finance would require a person to be more proficient in applied mathematics rather than computer engineering. Therefore, it is recommended by Wall Street recruiters to pursue a degree in mathematics with electives in computer science for a person wanting to pursue a career in quantitative finance. A proficiency in softwares such as R, Matlab, C and Python is desirable for quant roles. 

Big Data is touted as the future of finance. A lot of innovation is looking to be advanced in the field of data analytics to make sense of the huge influx of such data. Big Data would be complementing the traditional statistical approach to data measurement and interpretation presenting a renewed interest in data analytic techniques. Big data means not only large volumes of data, but also a wide variety of data types and a high velocity of data streams, integrated with internal and external data. While the social media technologies show how they are capable of processing large volumes of unstructured data for analysing, it is still too early to prove that we can pull together these complex, varied and changing sources of information into usable Financial Information.

The world is becoming more competitive for basic materials and commodities; increasing expectations and needs are arising from a growing and awakened population, resulting in financial theory and practice problems. Also there is increased inequality in the countries; financial contagion, low levels of regulation and technology growth.  Greater intervention by sovereign states, seeking to bolster their revenues, is going to result in a gradual loss of control over their own financial affairs and markets. The ability of nations to implement their  agendas is being undermined by an increase in indebtedness and ineffective global finance regulations.

All these factors point towards one single thing, which is the rise in the opportunities in Financial Engineering. Quantitative Finance is going to be the pillar that is going to hold markets together in the future. Effective utilisation of predictive mathematical models in finance will be highly crucial in the coming times as sophisticated securities get even more complex and delicate. Trading firms and financial institutions would need to adapt if they want to thrive in the grand financial landscape and financial engineers will be the thread that holds it all together. 

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