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Quantitative finance is a branch of investment management that employs mathematical and statistical methods to analyze investment opportunities across a range of asset classes. Practitioners in quantitative finance (quants) work in equities, fixed income and structured products, commodities, foreign exchange, and all varieties of derivatives. Areas of specialization include asset pricing, trading, hedging, portfolio analysis and optimization, risk management, and regulatory compliance. Quants are also entering the world of artificial intelligence and machine learning, where the demand for data scientists is growing dramatically.
The quant finance community intersects with many aspects of the investment landscape, whether it is in developing and selling complex derivatives, performing risk analytics, or advising buyers on asset pricing and portfolio allocation. Quants work in a variety of roles in investment banks and asset managers, hedge funds, prop trading firms, insurance companies, technology firms, and consultancies. Traditional job categories include roles in portfolio management, risk management, research, trading, and technology. In recent years, interest in data science and machine learning has grown significantly, intersecting with each of these categories. The data science revolution has impacts on the technology groups at financial firms, due to the infrastructure, programming support, and data management requirements that are part of a data science and machine learning environment.
When studying the many facets of the financial industry, some of the most active areas for quants entails investment banks and large asset managers. For these types of employers, a key aspect for job candidates to consider is the division between the “buy side” and the “sell side” – a distinction that places emphasis on similar quantitative skill sets, but with different objectives.
The buy side is comprised of mutual funds, pension funds, foundations, endowments, and hedge funds (institutional investors), as well as high-net-worth individuals. These entities are focused on investing in securities and managing very large funds or substantial individual or family resources, including those overseen by private wealth managers and family offices.
The sell side is comprised of investment banks, market makers, and individuals who develop the products and services that the buy side is seeking. This entails the creation, promotion, and sale of stocks, bonds, foreign exchange, derivatives, structured products, and other financial instruments to the buy side and in the public markets.
Inside these firms, quants are found in the so-called front, middle, and back offices. The front office (FO) is closest to trading and clients, and quants in the FO will often be involved in creating financial products, conducting research, and assisting with portfolio management as it intersects with strategies and trading in the market. The middle office (MO) is focused on supporting the front office directly, including functions of risk management, finance, accounting, model validation, price verification, and compliance. The back office (BO) handles trade processing, clearing, and accounting. The BO also tends to maintain the technology systems that support the firm’s activities. Technologists may work in any of these offices, supporting the essential activities within them. Data scientists often work in the research area of the firm and may interact across the offices due to the nature of their work.
Outside of the investment banks and large asset managers, quants will find roles in prop trading firms, where roles in research and trading will be prominent. In insurance companies, they may be involved in portfolio and risk management, and at tech firms and consultancies, there are roles in technology, research, and niche areas, such as alternative data analytics and regulatory tech and compliance. The emergence of FinTech has created a new set of opportunities for quants, including roles in high-frequency trading, machine learning, cryptocurrencies, and distributed ledger technology, all of which require strong programming skills. For those seeking a job in quant finance, familiarity with the general industry structures, terminology, and relationships within and between firms can help shape their perspective on where the most desirable opportunities are.
Quants work across all areas of finance, and are particularly known for their work in pricing, trading, asset allocation, IT, product development, and risk management. There are quants who work on derivatives pricing models, such as exotic options, and quants who work on structured products (“structurers”). Model validation quants focus on meeting regulatory requirements regarding pricing models, as well as supporting the trading and risk management functions of the firm. Finally, there are quant traders and quants involved in asset management, risk management, investment strategies, quant development, IT, and research. While the financial domain knowledge varies in each of these specializations, the core skills required always entail mathematics and programming as part of the quant package.
If you are interested in becoming a lead software engineer, explore the CQF Careers Guide to Quantitative Finance. Learn more about the skills needed and average salary you can earn in North America, Asia, and Europe for key career paths in quantitative finance.